Rのデータセット
R で標準的に使用できるデータセットは以下の通り. 説明は随時追加する.
データセット一覧
| Item | Title | |
|---|---|---|
| 1 | AirPassengers | Monthly Airline Passenger Numbers 1949-1960 |
| 2 | BJsales | Sales Data with Leading Indicator |
| 3 | BJsales.lead (BJsales) | Sales Data with Leading Indicator |
| 4 | BOD | Biochemical Oxygen Demand |
| 5 | CO2 | Carbon Dioxide Uptake in Grass Plants |
| 6 | ChickWeight | Weight versus age of chicks on different diets |
| 7 | DNase | Elisa assay of DNase |
| 8 | EuStockMarkets | Daily Closing Prices of Major European Stock Indices, 1991-1998 |
| 9 | Formaldehyde | Determination of Formaldehyde |
| 10 | HairEyeColor | Hair and Eye Color of Statistics Students |
| 11 | Harman23.cor | Harman Example 2.3 |
| 12 | Harman74.cor | Harman Example 7.4 |
| 13 | Indometh | Pharmacokinetics of Indomethacin |
| 14 | InsectSprays | Effectiveness of Insect Sprays |
| 15 | JohnsonJohnson | Quarterly Earnings per Johnson & Johnson Share |
| 16 | LakeHuron | Level of Lake Huron 1875-1972 |
| 17 | LifeCycleSavings | Intercountry Life-Cycle Savings Data |
| 18 | Loblolly | Growth of Loblolly pine trees |
| 19 | Nile | Flow of the River Nile |
| 20 | Orange | Growth of Orange Trees |
| 21 | OrchardSprays | Potency of Orchard Sprays |
| 22 | PlantGrowth | Results from an Experiment on Plant Growth |
| 23 | Puromycin | Reaction Velocity of an Enzymatic Reaction |
| 24 | Seatbelts | Road Casualties in Great Britain 1969-84 |
| 25 | Theoph | Pharmacokinetics of Theophylline |
| 26 | Titanic | Survival of passengers on the Titanic |
| 27 | ToothGrowth | The Effect of Vitamin C on Tooth Growth in Guinea Pigs |
| 28 | UCBAdmissions | Student Admissions at UC Berkeley |
| 29 | UKDriverDeaths | Road Casualties in Great Britain 1969-84 |
| 30 | UKgas | UK Quarterly Gas Consumption |
| 31 | USAccDeaths | Accidental Deaths in the US 1973-1978 |
| 32 | USArrests | Violent Crime Rates by US State |
| 33 | USJudgeRatings | Lawyers’ Ratings of State Judges in the US Superior Court |
| 34 | USPersonalExpenditure | Personal Expenditure Data |
| 35 | UScitiesD | Distances Between European Cities and Between US Cities |
| 36 | VADeaths | Death Rates in Virginia (1940) |
| 37 | WWWusage | Internet Usage per Minute |
| 38 | WorldPhones | The World’s Telephones |
| 39 | ability.cov | Ability and Intelligence Tests |
| 40 | airmiles | Passenger Miles on Commercial US Airlines, 1937-1960 |
| 41 | airquality | New York Air Quality Measurements |
| 42 | anscombe | Anscombe’s Quartet of ‘Identical’ Simple Linear Regressions |
| 43 | attenu | The Joyner-Boore Attenuation Data |
| 44 | attitude | The Chatterjee-Price Attitude Data |
| 45 | austres | Quarterly Time Series of the Number of Australian Residents |
| 46 | beaver1 (beavers) | Body Temperature Series of Two Beavers |
| 47 | beaver2 (beavers) | Body Temperature Series of Two Beavers |
| 48 | cars | Speed and Stopping Distances of Cars |
| 49 | chickwts | Chicken Weights by Feed Type |
| 50 | co2 | Mauna Loa Atmospheric CO2 Concentration |
| 51 | crimtab | Student’s 3000 Criminals Data |
| 52 | discoveries | Yearly Numbers of Important Discoveries |
| 53 | esoph | Smoking, Alcohol and (O)esophageal Cancer |
| 54 | euro | Conversion Rates of Euro Currencies |
| 55 | euro.cross (euro) | Conversion Rates of Euro Currencies |
| 56 | eurodist | Distances Between European Cities and Between US Cities |
| 57 | faithful | Old Faithful Geyser Data |
| 58 | fdeaths (UKLungDeaths) | Monthly Deaths from Lung Diseases in the UK |
| 59 | freeny | Freeny’s Revenue Data |
| 60 | freeny.x (freeny) | Freeny’s Revenue Data |
| 61 | freeny.y (freeny) | Freeny’s Revenue Data |
| 62 | infert | Infertility after Spontaneous and Induced Abortion |
| 63 | iris | Edgar Anderson’s Iris Data |
| 64 | iris3 | Edgar Anderson’s Iris Data |
| 65 | islands | Areas of the World’s Major Landmasses |
| 66 | ldeaths (UKLungDeaths) | Monthly Deaths from Lung Diseases in the UK |
| 67 | lh | Luteinizing Hormone in Blood Samples |
| 68 | longley | Longley’s Economic Regression Data |
| 69 | lynx | Annual Canadian Lynx trappings 1821-1934 |
| 70 | mdeaths (UKLungDeaths) | Monthly Deaths from Lung Diseases in the UK |
| 71 | morley | Michelson Speed of Light Data |
| 72 | mtcars | Motor Trend Car Road Tests |
| 73 | nhtemp | Average Yearly Temperatures in New Haven |
| 74 | nottem | Average Monthly Temperatures at Nottingham, 1920-1939 |
| 75 | npk | Classical N, P, K Factorial Experiment |
| 76 | occupationalStatus | Occupational Status of Fathers and their Sons |
| 77 | precip | Annual Precipitation in US Cities |
| 78 | presidents | Quarterly Approval Ratings of US Presidents |
| 79 | pressure | Vapor Pressure of Mercury as a Function of Temperature |
| 80 | quakes | Locations of Earthquakes off Fiji |
| 81 | randu | Random Numbers from Congruential Generator RANDU |
| 82 | rivers | Lengths of Major North American Rivers |
| 83 | rock | Measurements on Petroleum Rock Samples |
| 84 | sleep | Student’s Sleep Data |
| 85 | stack.loss (stackloss) | Brownlee’s Stack Loss Plant Data |
| 86 | stack.x (stackloss) | Brownlee’s Stack Loss Plant Data |
| 87 | stackloss | Brownlee’s Stack Loss Plant Data |
| 88 | state.abb (state) | US State Facts and Figures |
| 89 | state.area (state) | US State Facts and Figures |
| 90 | state.center (state) | US State Facts and Figures |
| 91 | state.division (state) | US State Facts and Figures |
| 92 | state.name (state) | US State Facts and Figures |
| 93 | state.region (state) | US State Facts and Figures |
| 94 | state.x77 (state) | US State Facts and Figures |
| 95 | sunspot.month | Monthly Sunspot Data, from 1749 to “Present” |
| 96 | sunspot.year | Yearly Sunspot Data, 1700-1988 |
| 97 | sunspots | Monthly Sunspot Numbers, 1749-1983 |
| 98 | swiss | Swiss Fertility and Socioeconomic Indicators (1888) Data |
| 99 | treering | Yearly Treering Data, -6000-1979 |
| 100 | trees | Girth, Height and Volume for Black Cherry Trees |
| 101 | uspop | Populations Recorded by the US Census |
| 102 | volcano | Topographic Information on Auckland’s Maunga Whau Volcano |
| 103 | warpbreaks | The Number of Breaks in Yarn during Weaving |
| 104 | women | Average Heights and Weights for American Women |
AirPassengers
時系列モデル.
Box & Jenkins のデータ. 1949〜1960における, 航空会社の国際線の顧客の月別総乗客数.
AirPassengers## Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
## 1949 112 118 132 129 121 135 148 148 136 119 104 118
## 1950 115 126 141 135 125 149 170 170 158 133 114 140
## 1951 145 150 178 163 172 178 199 199 184 162 146 166
## 1952 171 180 193 181 183 218 230 242 209 191 172 194
## 1953 196 196 236 235 229 243 264 272 237 211 180 201
## 1954 204 188 235 227 234 264 302 293 259 229 203 229
## 1955 242 233 267 269 270 315 364 347 312 274 237 278
## 1956 284 277 317 313 318 374 413 405 355 306 271 306
## 1957 315 301 356 348 355 422 465 467 404 347 305 336
## 1958 340 318 362 348 363 435 491 505 404 359 310 337
## 1959 360 342 406 396 420 472 548 559 463 407 362 405
## 1960 417 391 419 461 472 535 622 606 508 461 390 432plot(AirPassengers,type="l")
BJsales
時系列モデル. Box & Jenkins のセールスのデータ.
BJsales## Time Series:
## Start = 1
## End = 150
## Frequency = 1
## [1] 200.1 199.5 199.4 198.9 199.0 200.2 198.6 200.0 200.3 201.2 201.6
## [12] 201.5 201.5 203.5 204.9 207.1 210.5 210.5 209.8 208.8 209.5 213.2
## [23] 213.7 215.1 218.7 219.8 220.5 223.8 222.8 223.8 221.7 222.3 220.8
## [34] 219.4 220.1 220.6 218.9 217.8 217.7 215.0 215.3 215.9 216.7 216.7
## [45] 217.7 218.7 222.9 224.9 222.2 220.7 220.0 218.7 217.0 215.9 215.8
## [56] 214.1 212.3 213.9 214.6 213.6 212.1 211.4 213.1 212.9 213.3 211.5
## [67] 212.3 213.0 211.0 210.7 210.1 211.4 210.0 209.7 208.8 208.8 208.8
## [78] 210.6 211.9 212.8 212.5 214.8 215.3 217.5 218.8 220.7 222.2 226.7
## [89] 228.4 233.2 235.7 237.1 240.6 243.8 245.3 246.0 246.3 247.7 247.6
## [100] 247.8 249.4 249.0 249.9 250.5 251.5 249.0 247.6 248.8 250.4 250.7
## [111] 253.0 253.7 255.0 256.2 256.0 257.4 260.4 260.0 261.3 260.4 261.6
## [122] 260.8 259.8 259.0 258.9 257.4 257.7 257.9 257.4 257.3 257.6 258.9
## [133] 257.8 257.7 257.2 257.5 256.8 257.5 257.0 257.6 257.3 257.5 259.6
## [144] 261.1 262.9 263.3 262.8 261.8 262.2 262.7plot(BJsales,type="l")
BJsales.lead
時系列モデル. Box & Jenkins のセールスの主要指標のデータ.
Leading Indicator。
BJsales.lead## Time Series:
## Start = 1
## End = 150
## Frequency = 1
## [1] 10.01 10.07 10.32 9.75 10.33 10.13 10.36 10.32 10.13 10.16 10.58
## [12] 10.62 10.86 11.20 10.74 10.56 10.48 10.77 11.33 10.96 11.16 11.70
## [23] 11.39 11.42 11.94 11.24 11.59 10.96 11.40 11.02 11.01 11.23 11.33
## [34] 10.83 10.84 11.14 10.38 10.90 11.05 11.11 11.01 11.22 11.21 11.91
## [45] 11.69 10.93 10.99 11.01 10.84 10.76 10.77 10.88 10.49 10.50 11.00
## [56] 10.98 10.61 10.48 10.53 11.07 10.61 10.86 10.34 10.78 10.80 10.33
## [67] 10.44 10.50 10.75 10.40 10.40 10.34 10.55 10.46 10.82 10.91 10.87
## [78] 10.67 11.11 10.88 11.28 11.27 11.44 11.52 12.10 11.83 12.62 12.41
## [89] 12.43 12.73 13.01 12.74 12.73 12.76 12.92 12.64 12.79 13.05 12.69
## [100] 13.01 12.90 13.12 12.47 12.47 12.94 13.10 12.91 13.39 13.13 13.34
## [111] 13.34 13.14 13.49 13.87 13.39 13.59 13.27 13.70 13.20 13.32 13.15
## [122] 13.30 12.94 13.29 13.26 13.08 13.24 13.31 13.52 13.02 13.25 13.12
## [133] 13.26 13.11 13.30 13.06 13.32 13.10 13.27 13.64 13.58 13.87 13.53
## [144] 13.41 13.25 13.50 13.58 13.51 13.77 13.40plot(BJsales.lead,type="l")
BOD
6行 x 2列. 生物化学的酸素要求量（水質の悪さ）と水質を評価した日数.
BOD## Time demand
## 1 1 8.3
## 2 2 10.3
## 3 3 19.0
## 4 4 16.0
## 5 5 15.6
## 6 7 19.8plot(BOD)
CO2
イヌビエの耐寒性の実験データ. 84行 x 5列.
head(CO2)## Plant Type Treatment conc uptake
## 1 Qn1 Quebec nonchilled 95 16.0
## 2 Qn1 Quebec nonchilled 175 30.4
## 3 Qn1 Quebec nonchilled 250 34.8
## 4 Qn1 Quebec nonchilled 350 37.2
## 5 Qn1 Quebec nonchilled 500 35.3
## 6 Qn1 Quebec nonchilled 675 39.2coplot(uptake ~ conc | Plant, data = CO2, type = "b", show.given = FALSE)
ChickWeight
578 x 4. ヒヨコにダイエット（4種類）させたときの経過日数と体重変化.
head(ChickWeight)## weight Time Chick Diet
## 1 42 0 1 1
## 2 51 2 1 1
## 3 59 4 1 1
## 4 64 6 1 1
## 5 76 8 1 1
## 6 93 10 1 1require(graphics)
coplot(weight ~ Time | Chick, data = ChickWeight, type = "b", show.given = FALSE)
DNase
176 x 3. ラットの血漿中の組換タンパク質に関するエライサ（抗体の濃度の検査）
head(DNase)## Run conc density
## 1 1 0.04882812 0.017
## 2 1 0.04882812 0.018
## 3 1 0.19531250 0.121
## 4 1 0.19531250 0.124
## 5 1 0.39062500 0.206
## 6 1 0.39062500 0.215require(graphics)
coplot(density ~ conc | Run, data = DNase, show.given = FALSE, type = "b")
EuStockMarkets
多次元の時系列（パネル）データ. 1860 x 4.
Contains the daily closing prices of major European stock indices: Germany DAX (Ibis), Switzerland SMI, France CAC, and UK FTSE. The data are sampled in business time, i.e., weekends and holidays are omitted.
head(EuStockMarkets)## DAX SMI CAC FTSE
## [1,] 1628.75 1678.1 1772.8 2443.6
## [2,] 1613.63 1688.5 1750.5 2460.2
## [3,] 1606.51 1678.6 1718.0 2448.2
## [4,] 1621.04 1684.1 1708.1 2470.4
## [5,] 1618.16 1686.6 1723.1 2484.7
## [6,] 1610.61 1671.6 1714.3 2466.8plot(EuStockMarkets)
Formaldehyde
6 x 2. 単回帰モデル. These data are from a chemical experiment to prepare a standard curve for the determination of formaldehyde by the addition of chromatropic acid and concentrated sulphuric acid and the reading of the resulting purple color on a spectrophotometer.
Formaldehyde## carb optden
## 1 0.1 0.086
## 2 0.3 0.269
## 3 0.5 0.446
## 4 0.6 0.538
## 5 0.7 0.626
## 6 0.9 0.782plot(Formaldehyde)
HairEyeColor
Distribution of hair and eye color and sex in 592 statistics students. クロス集計表.
HairEyeColor## , , Sex = Male
##
## Eye
## Hair Brown Blue Hazel Green
## Black 32 11 10 3
## Brown 53 50 25 15
## Red 10 10 7 7
## Blond 3 30 5 8
##
## , , Sex = Female
##
## Eye
## Hair Brown Blue Hazel Green
## Black 36 9 5 2
## Brown 66 34 29 14
## Red 16 7 7 7
## Blond 4 64 5 8mosaicplot(HairEyeColor)
Harman23.cor
相関行列. 因子分析. A correlation matrix of eight physical measurements on 305 girls between ages seven and seventeen.
Harman23.cor## $cov
## height arm.span forearm lower.leg weight bitro.diameter
## height 1.000 0.846 0.805 0.859 0.473 0.398
## arm.span 0.846 1.000 0.881 0.826 0.376 0.326
## forearm 0.805 0.881 1.000 0.801 0.380 0.319
## lower.leg 0.859 0.826 0.801 1.000 0.436 0.329
## weight 0.473 0.376 0.380 0.436 1.000 0.762
## bitro.diameter 0.398 0.326 0.319 0.329 0.762 1.000
## chest.girth 0.301 0.277 0.237 0.327 0.730 0.583
## chest.width 0.382 0.415 0.345 0.365 0.629 0.577
## chest.girth chest.width
## height 0.301 0.382
## arm.span 0.277 0.415
## forearm 0.237 0.345
## lower.leg 0.327 0.365
## weight 0.730 0.629
## bitro.diameter 0.583 0.577
## chest.girth 1.000 0.539
## chest.width 0.539 1.000
##
## $center
## [1] 0 0 0 0 0 0 0 0
##
## $n.obs
## [1] 305factanal(factors=2, covmat=Harman23.cor)##
## Call:
## factanal(factors = 2, covmat = Harman23.cor)
##
## Uniquenesses:
## height arm.span forearm lower.leg weight
## 0.170 0.107 0.166 0.199 0.089
## bitro.diameter chest.girth chest.width
## 0.364 0.416 0.537
##
## Loadings:
## Factor1 Factor2
## height 0.865 0.287
## arm.span 0.927 0.181
## forearm 0.895 0.179
## lower.leg 0.859 0.252
## weight 0.233 0.925
## bitro.diameter 0.194 0.774
## chest.girth 0.134 0.752
## chest.width 0.278 0.621
##
## Factor1 Factor2
## SS loadings 3.335 2.617
## Proportion Var 0.417 0.327
## Cumulative Var 0.417 0.744
##
## Test of the hypothesis that 2 factors are sufficient.
## The chi square statistic is 75.74 on 13 degrees of freedom.
## The p-value is 6.94e-11Harman74.cor
相関行列. 因子分析. A correlation matrix of 24 psychological tests given to 145 seventh and eight-grade children in a Chicago suburb by Holzinger and Swineford.
#Harman74.cor
factanal(factors=2, covmat=Harman74.cor)##
## Call:
## factanal(factors = 2, covmat = Harman74.cor)
##
## Uniquenesses:
## VisualPerception Cubes PaperFormBoard
## 0.650 0.864 0.844
## Flags GeneralInformation PargraphComprehension
## 0.778 0.375 0.316
## SentenceCompletion WordClassification WordMeaning
## 0.319 0.503 0.258
## Addition Code CountingDots
## 0.670 0.608 0.581
## StraightCurvedCapitals WordRecognition NumberRecognition
## 0.567 0.832 0.850
## FigureRecognition ObjectNumber NumberFigure
## 0.743 0.770 0.625
## FigureWord Deduction NumericalPuzzles
## 0.792 0.629 0.579
## ProblemReasoning SeriesCompletion ArithmeticProblems
## 0.634 0.539 0.553
##
## Loadings:
## Factor1 Factor2
## VisualPerception 0.506 0.306
## Cubes 0.304 0.209
## PaperFormBoard 0.297 0.260
## Flags 0.327 0.339
## GeneralInformation 0.240 0.753
## PargraphComprehension 0.171 0.809
## SentenceCompletion 0.163 0.809
## WordClassification 0.344 0.615
## WordMeaning 0.148 0.849
## Addition 0.563 0.115
## Code 0.591 0.207
## CountingDots 0.647
## StraightCurvedCapitals 0.612 0.241
## WordRecognition 0.315 0.263
## NumberRecognition 0.328 0.205
## FigureRecognition 0.457 0.218
## ObjectNumber 0.431 0.209
## NumberFigure 0.601 0.116
## FigureWord 0.399 0.222
## Deduction 0.379 0.477
## NumericalPuzzles 0.604 0.237
## ProblemReasoning 0.390 0.462
## SeriesCompletion 0.486 0.474
## ArithmeticProblems 0.544 0.389
##
## Factor1 Factor2
## SS loadings 4.573 4.548
## Proportion Var 0.191 0.190
## Cumulative Var 0.191 0.380
##
## Test of the hypothesis that 2 factors are sufficient.
## The chi square statistic is 420.24 on 229 degrees of freedom.
## The p-value is 2.01e-13Indometh
66 x 3. インドメタシンの薬物動態データ.
head(Indometh)## Subject time conc
## 1 1 0.25 1.50
## 2 1 0.50 0.94
## 3 1 0.75 0.78
## 4 1 1.00 0.48
## 5 1 1.25 0.37
## 6 1 2.00 0.19coplot(conc~time|Subject,data=Indometh,show.given=FALSE)
InsectSprays
複数の殺虫剤を用いた農場試験での虫の数. 72 x 2.
head(InsectSprays)## count spray
## 1 10 A
## 2 7 A
## 3 20 A
## 4 14 A
## 5 14 A
## 6 12 Aboxplot(count~spray,data=InsectSprays,horizontal=T)
JohnsonJohnson
1960〜80年の4半期ごとの Johnson & Johnson の一株あたり利益（ドル）
JohnsonJohnson## Qtr1 Qtr2 Qtr3 Qtr4
## 1960 0.71 0.63 0.85 0.44
## 1961 0.61 0.69 0.92 0.55
## 1962 0.72 0.77 0.92 0.60
## 1963 0.83 0.80 1.00 0.77
## 1964 0.92 1.00 1.24 1.00
## 1965 1.16 1.30 1.45 1.25
## 1966 1.26 1.38 1.86 1.56
## 1967 1.53 1.59 1.83 1.86
## 1968 1.53 2.07 2.34 2.25
## 1969 2.16 2.43 2.70 2.25
## 1970 2.79 3.42 3.69 3.60
## 1971 3.60 4.32 4.32 4.05
## 1972 4.86 5.04 5.04 4.41
## 1973 5.58 5.85 6.57 5.31
## 1974 6.03 6.39 6.93 5.85
## 1975 6.93 7.74 7.83 6.12
## 1976 7.74 8.91 8.28 6.84
## 1977 9.54 10.26 9.54 8.73
## 1978 11.88 12.06 12.15 8.91
## 1979 14.04 12.96 14.85 9.99
## 1980 16.20 14.67 16.02 11.61plot(JohnsonJohnson, type="l")
LakeHuron
1875〜1972年のヒューロン湖（Lake Huron）における水位（フィート）.
LakeHuron## Time Series:
## Start = 1875
## End = 1972
## Frequency = 1
## [1] 580.38 581.86 580.97 580.80 579.79 580.39 580.42 580.82 581.40 581.32
## [11] 581.44 581.68 581.17 580.53 580.01 579.91 579.14 579.16 579.55 579.67
## [21] 578.44 578.24 579.10 579.09 579.35 578.82 579.32 579.01 579.00 579.80
## [31] 579.83 579.72 579.89 580.01 579.37 578.69 578.19 578.67 579.55 578.92
## [41] 578.09 579.37 580.13 580.14 579.51 579.24 578.66 578.86 578.05 577.79
## [51] 576.75 576.75 577.82 578.64 580.58 579.48 577.38 576.90 576.94 576.24
## [61] 576.84 576.85 576.90 577.79 578.18 577.51 577.23 578.42 579.61 579.05
## [71] 579.26 579.22 579.38 579.10 577.95 578.12 579.75 580.85 580.41 579.96
## [81] 579.61 578.76 578.18 577.21 577.13 579.10 578.25 577.91 576.89 575.96
## [91] 576.80 577.68 578.38 578.52 579.74 579.31 579.89 579.96plot(LakeHuron, type="l")
LifeCycleSavings
1960〜1970年の貯蓄率.
head(LifeCycleSavings)## sr pop15 pop75 dpi ddpi
## Australia 11.43 29.35 2.87 2329.68 2.87
## Austria 12.07 23.32 4.41 1507.99 3.93
## Belgium 13.17 23.80 4.43 2108.47 3.82
## Bolivia 5.75 41.89 1.67 189.13 0.22
## Brazil 12.88 42.19 0.83 728.47 4.56
## Canada 8.79 31.72 2.85 2982.88 2.43plot(LifeCycleSavings)
Loblolly
84 x 3. テーダマツ（Loblolly）の生長データ.
head(Loblolly)## height age Seed
## 1 4.51 3 301
## 15 10.89 5 301
## 29 28.72 10 301
## 43 41.74 15 301
## 57 52.70 20 301
## 71 60.92 25 301coplot(height~age|Seed, data=Loblolly,show.given=FALSE)
Nile
1871〜1970年におけるAshwanでのナイル川の年間流量.
Nile## Time Series:
## Start = 1871
## End = 1970
## Frequency = 1
## [1] 1120 1160 963 1210 1160 1160 813 1230 1370 1140 995 935 1110 994
## [15] 1020 960 1180 799 958 1140 1100 1210 1150 1250 1260 1220 1030 1100
## [29] 774 840 874 694 940 833 701 916 692 1020 1050 969 831 726
## [43] 456 824 702 1120 1100 832 764 821 768 845 864 862 698 845
## [57] 744 796 1040 759 781 865 845 944 984 897 822 1010 771 676
## [71] 649 846 812 742 801 1040 860 874 848 890 744 749 838 1050
## [85] 918 986 797 923 975 815 1020 906 901 1170 912 746 919 718
## [99] 714 740plot(Nile)
Orange
35 x 3. オレンジの木の生長の記録.
head(Orange)## Tree age circumference
## 1 1 118 30
## 2 1 484 58
## 3 1 664 87
## 4 1 1004 115
## 5 1 1231 120
## 6 1 1372 142coplot(circumference~age|Tree, data=Orange, show.given=FALSE)
OrchardSprays
64 x 4. 分散分析. An experiment was conducted to assess the potency of various constituents of orchard sprays in repelling honeybees, using a Latin square design.
head(OrchardSprays)## decrease rowpos colpos treatment
## 1 57 1 1 D
## 2 95 2 1 E
## 3 8 3 1 B
## 4 69 4 1 H
## 5 92 5 1 G
## 6 90 6 1 Faov(decrease~factor(rowpos)+factor(colpos)+treatment,data=OrchardSprays)## Call:
## aov(formula = decrease ~ factor(rowpos) + factor(colpos) + treatment,
## data = OrchardSprays)
##
## Terms:
## factor(rowpos) factor(colpos) treatment Residuals
## Sum of Squares 4767.48 2807.23 56159.98 15994.91
## Deg. of Freedom 7 7 7 42
##
## Residual standard error: 19.51489
## Estimated effects may be unbalancedPlantGrowth
Results from an experiment to compare yields (as measured by dried weight of plants) obtained under a control and two different treatment conditions.
head(PlantGrowth)## weight group
## 1 4.17 ctrl
## 2 5.58 ctrl
## 3 5.18 ctrl
## 4 6.11 ctrl
## 5 4.50 ctrl
## 6 4.61 ctrlboxplot(weight~group, data=PlantGrowth, horizontal=TRUE)
Puromycin
23 x 3. ピューロマイシン（抗生物質）による細胞の酵素反応に関する反応速度（rate＝counts/min/min）と基質濃度（ppm）
head(Puromycin)## conc rate state
## 1 0.02 76 treated
## 2 0.02 47 treated
## 3 0.06 97 treated
## 4 0.06 107 treated
## 5 0.11 123 treated
## 6 0.11 139 treatedcoplot(rate~conc|state, data=Puromycin, show.given=FALSE)
Seatbelts
UKDriverDeaths の詳細版. 1969年1月〜1984年12月のイギリスにおけるドライバーの死傷者数. 1983年1月31日にシートベルトが義務化された.
head(Seatbelts)## [1] 107 97 102 87 119 106plot(Seatbelts)
Theoph
132 x 5. テオフィリンの薬物動態実験のデータ.
head(Theoph)## Subject Wt Dose Time conc
## 1 1 79.6 4.02 0.00 0.74
## 2 1 79.6 4.02 0.25 2.84
## 3 1 79.6 4.02 0.57 6.57
## 4 1 79.6 4.02 1.12 10.50
## 5 1 79.6 4.02 2.02 9.66
## 6 1 79.6 4.02 3.82 8.58coplot(conc~Time|Subject, data=Theoph, show.given=FALSE)
Titanic
タイタニック号のクロス集計表.
Titanic## , , Age = Child, Survived = No
##
## Sex
## Class Male Female
## 1st 0 0
## 2nd 0 0
## 3rd 35 17
## Crew 0 0
##
## , , Age = Adult, Survived = No
##
## Sex
## Class Male Female
## 1st 118 4
## 2nd 154 13
## 3rd 387 89
## Crew 670 3
##
## , , Age = Child, Survived = Yes
##
## Sex
## Class Male Female
## 1st 5 1
## 2nd 11 13
## 3rd 13 14
## Crew 0 0
##
## , , Age = Adult, Survived = Yes
##
## Sex
## Class Male Female
## 1st 57 140
## 2nd 14 80
## 3rd 75 76
## Crew 192 20mosaicplot(Titanic)
ToothGrowth
The response is the length of odontoblasts (teeth) in each of 10 guinea pigs at each of three dose levels of Vitamin C (0.5, 1, and 2 mg) with each of two delivery methods (orange juice or ascorbic acid).
head(ToothGrowth)## len supp dose
## 1 4.2 VC 0.5
## 2 11.5 VC 0.5
## 3 7.3 VC 0.5
## 4 5.8 VC 0.5
## 5 6.4 VC 0.5
## 6 10.0 VC 0.5coplot(len~dose|supp, data=ToothGrowth,show.given=FALSE)
UCBAdmissions
1973年のUC Berkeley 大学院（6学科）の出願者のクロス集計表.
（下のグラフはあまり良いグラフでないかも）
UCBAdmissions## , , Dept = A
##
## Gender
## Admit Male Female
## Admitted 512 89
## Rejected 313 19
##
## , , Dept = B
##
## Gender
## Admit Male Female
## Admitted 353 17
## Rejected 207 8
##
## , , Dept = C
##
## Gender
## Admit Male Female
## Admitted 120 202
## Rejected 205 391
##
## , , Dept = D
##
## Gender
## Admit Male Female
## Admitted 138 131
## Rejected 279 244
##
## , , Dept = E
##
## Gender
## Admit Male Female
## Admitted 53 94
## Rejected 138 299
##
## , , Dept = F
##
## Gender
## Admit Male Female
## Admitted 22 24
## Rejected 351 317mosaicplot(UCBAdmissions)
UKDriverDeaths
1969年1月〜1984年12月のイギリスにおけるドライバーの死傷者数. 1983年1月31日にシートベルトが義務化された.
UKDriverDeaths## Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
## 1969 1687 1508 1507 1385 1632 1511 1559 1630 1579 1653 2152 2148
## 1970 1752 1765 1717 1558 1575 1520 1805 1800 1719 2008 2242 2478
## 1971 2030 1655 1693 1623 1805 1746 1795 1926 1619 1992 2233 2192
## 1972 2080 1768 1835 1569 1976 1853 1965 1689 1778 1976 2397 2654
## 1973 2097 1963 1677 1941 2003 1813 2012 1912 2084 2080 2118 2150
## 1974 1608 1503 1548 1382 1731 1798 1779 1887 2004 2077 2092 2051
## 1975 1577 1356 1652 1382 1519 1421 1442 1543 1656 1561 1905 2199
## 1976 1473 1655 1407 1395 1530 1309 1526 1327 1627 1748 1958 2274
## 1977 1648 1401 1411 1403 1394 1520 1528 1643 1515 1685 2000 2215
## 1978 1956 1462 1563 1459 1446 1622 1657 1638 1643 1683 2050 2262
## 1979 1813 1445 1762 1461 1556 1431 1427 1554 1645 1653 2016 2207
## 1980 1665 1361 1506 1360 1453 1522 1460 1552 1548 1827 1737 1941
## 1981 1474 1458 1542 1404 1522 1385 1641 1510 1681 1938 1868 1726
## 1982 1456 1445 1456 1365 1487 1558 1488 1684 1594 1850 1998 2079
## 1983 1494 1057 1218 1168 1236 1076 1174 1139 1427 1487 1483 1513
## 1984 1357 1165 1282 1110 1297 1185 1222 1284 1444 1575 1737 1763plot(UKDriverDeaths)
UKgas
1960年〜1986年の四半期ごとのイギリスのガス消費量（単位：100万サーム）.
UKgas## Qtr1 Qtr2 Qtr3 Qtr4
## 1960 160.1 129.7 84.8 120.1
## 1961 160.1 124.9 84.8 116.9
## 1962 169.7 140.9 89.7 123.3
## 1963 187.3 144.1 92.9 120.1
## 1964 176.1 147.3 89.7 123.3
## 1965 185.7 155.3 99.3 131.3
## 1966 200.1 161.7 102.5 136.1
## 1967 204.9 176.1 112.1 140.9
## 1968 227.3 195.3 115.3 142.5
## 1969 244.9 214.5 118.5 153.7
## 1970 244.9 216.1 188.9 142.5
## 1971 301.0 196.9 136.1 267.3
## 1972 317.0 230.5 152.1 336.2
## 1973 371.4 240.1 158.5 355.4
## 1974 449.9 286.6 179.3 403.4
## 1975 491.5 321.8 177.7 409.8
## 1976 593.9 329.8 176.1 483.5
## 1977 584.3 395.4 187.3 485.1
## 1978 669.2 421.0 216.1 509.1
## 1979 827.7 467.5 209.7 542.7
## 1980 840.5 414.6 217.7 670.8
## 1981 848.5 437.0 209.7 701.2
## 1982 925.3 443.4 214.5 683.6
## 1983 917.3 515.5 224.1 694.8
## 1984 989.4 477.1 233.7 730.0
## 1985 1087.0 534.7 281.8 787.6
## 1986 1163.9 613.1 347.4 782.8plot(UKgas)
USAccDeaths
1973年〜1978年のアメリカにおける月別の交通事故死者数.
USAccDeaths## Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov
## 1973 9007 8106 8928 9137 10017 10826 11317 10744 9713 9938 9161
## 1974 7750 6981 8038 8422 8714 9512 10120 9823 8743 9129 8710
## 1975 8162 7306 8124 7870 9387 9556 10093 9620 8285 8466 8160
## 1976 7717 7461 7767 7925 8623 8945 10078 9179 8037 8488 7874
## 1977 7792 6957 7726 8106 8890 9299 10625 9302 8314 8850 8265
## 1978 7836 6892 7791 8192 9115 9434 10484 9827 9110 9070 8633
## Dec
## 1973 8927
## 1974 8680
## 1975 8034
## 1976 8647
## 1977 8796
## 1978 9240plot(USAccDeaths)
USArrests
This data set contains statistics, in arrests per 100,000 residents for assault, murder, and rape in each of the 50 US states in 1973. Also given is the percent of the population living in urban areas.
head(USArrests)## Murder Assault UrbanPop Rape
## Alabama 13.2 236 58 21.2
## Alaska 10.0 263 48 44.5
## Arizona 8.1 294 80 31.0
## Arkansas 8.8 190 50 19.5
## California 9.0 276 91 40.6
## Colorado 7.9 204 78 38.7plot(USArrests)
USJudgeRatings
43 x 12. アメリカの上級裁判所の州裁判官についての弁護士の評価.
head(USJudgeRatings)## CONT INTG DMNR DILG CFMG DECI PREP FAMI ORAL WRIT PHYS RTEN
## AARONSON,L.H. 5.7 7.9 7.7 7.3 7.1 7.4 7.1 7.1 7.1 7.0 8.3 7.8
## ALEXANDER,J.M. 6.8 8.9 8.8 8.5 7.8 8.1 8.0 8.0 7.8 7.9 8.5 8.7
## ARMENTANO,A.J. 7.2 8.1 7.8 7.8 7.5 7.6 7.5 7.5 7.3 7.4 7.9 7.8
## BERDON,R.I. 6.8 8.8 8.5 8.8 8.3 8.5 8.7 8.7 8.4 8.5 8.8 8.7
## BRACKEN,J.J. 7.3 6.4 4.3 6.5 6.0 6.2 5.7 5.7 5.1 5.3 5.5 4.8
## BURNS,E.B. 6.2 8.8 8.7 8.5 7.9 8.0 8.1 8.0 8.0 8.0 8.6 8.6plot(USJudgeRatings)
USPersonalExpenditure
アメリカにおける個人支出額（億ドル）の推移（1940, 1945, 1950, 1955, 1960）.
USPersonalExpenditure## 1940 1945 1950 1955 1960
## Food and Tobacco 22.200 44.500 59.60 73.2 86.80
## Household Operation 10.500 15.500 29.00 36.5 46.20
## Medical and Health 3.530 5.760 9.71 14.0 21.10
## Personal Care 1.040 1.980 2.45 3.4 5.40
## Private Education 0.341 0.974 1.80 2.6 3.64matplot(t(USPersonalExpenditure),type = "l")
UScitiesD
クラスター分析. アメリカの10都市の間の直線距離（km）.
UScitiesD## Atlanta Chicago Denver Houston LosAngeles Miami NewYork
## Chicago 587
## Denver 1212 920
## Houston 701 940 879
## LosAngeles 1936 1745 831 1374
## Miami 604 1188 1726 968 2339
## NewYork 748 713 1631 1420 2451 1092
## SanFrancisco 2139 1858 949 1645 347 2594 2571
## Seattle 2182 1737 1021 1891 959 2734 2408
## Washington.DC 543 597 1494 1220 2300 923 205
## SanFrancisco Seattle
## Chicago
## Denver
## Houston
## LosAngeles
## Miami
## NewYork
## SanFrancisco
## Seattle 678
## Washington.DC 2442 2329plot(hclust(UScitiesD))
VADeaths
バージニア州における1940年の1000人あたり死亡率.
VADeaths## Rural Male Rural Female Urban Male Urban Female
## 50-54 11.7 8.7 15.4 8.4
## 55-59 18.1 11.7 24.3 13.6
## 60-64 26.9 20.3 37.0 19.3
## 65-69 41.0 30.9 54.6 35.1
## 70-74 66.0 54.3 71.1 50.0WWWusage
あるサーバを通じてインターネットに接続していた人の人数（毎分）.
WWWusage## Time Series:
## Start = 1
## End = 100
## Frequency = 1
## [1] 88 84 85 85 84 85 83 85 88 89 91 99 104 112 126 138 146
## [18] 151 150 148 147 149 143 132 131 139 147 150 148 145 140 134 131 131
## [35] 129 126 126 132 137 140 142 150 159 167 170 171 172 172 174 175 172
## [52] 172 174 174 169 165 156 142 131 121 112 104 102 99 99 95 88 84
## [69] 84 87 89 88 85 86 89 91 91 94 101 110 121 135 145 149 156
## [86] 165 171 175 177 182 193 204 208 210 215 222 228 226 222 220plot(WWWusage)
WorldPhones
各地域での電話機の数（単位：千台）.
WorldPhones## N.Amer Europe Asia S.Amer Oceania Africa Mid.Amer
## 1951 45939 21574 2876 1815 1646 89 555
## 1956 60423 29990 4708 2568 2366 1411 733
## 1957 64721 32510 5230 2695 2526 1546 773
## 1958 68484 35218 6662 2845 2691 1663 836
## 1959 71799 37598 6856 3000 2868 1769 911
## 1960 76036 40341 8220 3145 3054 1905 1008
## 1961 79831 43173 9053 3338 3224 2005 1076matplot(WorldPhones,type="l")
ability.cov
112名に対する6つのテストの結果の共分散行列.
ability.cov## $cov
## general picture blocks maze reading vocab
## general 24.641 5.991 33.520 6.023 20.755 29.701
## picture 5.991 6.700 18.137 1.782 4.936 7.204
## blocks 33.520 18.137 149.831 19.424 31.430 50.753
## maze 6.023 1.782 19.424 12.711 4.757 9.075
## reading 20.755 4.936 31.430 4.757 52.604 66.762
## vocab 29.701 7.204 50.753 9.075 66.762 135.292
##
## $center
## [1] 0 0 0 0 0 0
##
## $n.obs
## [1] 112factanal(factors=2, covmat=ability.cov)##
## Call:
## factanal(factors = 2, covmat = ability.cov)
##
## Uniquenesses:
## general picture blocks maze reading vocab
## 0.455 0.589 0.218 0.769 0.052 0.334
##
## Loadings:
## Factor1 Factor2
## general 0.499 0.543
## picture 0.156 0.622
## blocks 0.206 0.860
## maze 0.109 0.468
## reading 0.956 0.182
## vocab 0.785 0.225
##
## Factor1 Factor2
## SS loadings 1.858 1.724
## Proportion Var 0.310 0.287
## Cumulative Var 0.310 0.597
##
## Test of the hypothesis that 2 factors are sufficient.
## The chi square statistic is 6.11 on 4 degrees of freedom.
## The p-value is 0.191airmiles
The revenue passenger miles flown by commercial airlines in the United States for each year from 1937 to 1960.
airmiles## Time Series:
## Start = 1937
## End = 1960
## Frequency = 1
## [1] 412 480 683 1052 1385 1418 1634 2178 3362 5948 6109
## [12] 5981 6753 8003 10566 12528 14760 16769 19819 22362 25340 25343
## [23] 29269 30514plot(airmiles)
airquality
154 x 6. ニューヨークにおける 1973年5月〜9月の大気質の日別観測値.
head(airquality)## Ozone Solar.R Wind Temp Month Day
## 1 41 190 7.4 67 5 1
## 2 36 118 8.0 72 5 2
## 3 12 149 12.6 74 5 3
## 4 18 313 11.5 62 5 4
## 5 NA NA 14.3 56 5 5
## 6 28 NA 14.9 66 5 6plot(airquality[,1:4])
anscombe
アンスコムの数値例. 4つのセットは全く異なる散布図だが, 得られる回帰直線はほぼ同一.
anscombe## x1 x2 x3 x4 y1 y2 y3 y4
## 1 10 10 10 8 8.04 9.14 7.46 6.58
## 2 8 8 8 8 6.95 8.14 6.77 5.76
## 3 13 13 13 8 7.58 8.74 12.74 7.71
## 4 9 9 9 8 8.81 8.77 7.11 8.84
## 5 11 11 11 8 8.33 9.26 7.81 8.47
## 6 14 14 14 8 9.96 8.10 8.84 7.04
## 7 6 6 6 8 7.24 6.13 6.08 5.25
## 8 4 4 4 19 4.26 3.10 5.39 12.50
## 9 12 12 12 8 10.84 9.13 8.15 5.56
## 10 7 7 7 8 4.82 7.26 6.42 7.91
## 11 5 5 5 8 5.68 4.74 5.73 6.89par(mfrow=c(2,2))
plot(anscombe$x1,anscombe$y1)
plot(anscombe$x2,anscombe$y2)
plot(anscombe$x3,anscombe$y3)
plot(anscombe$x4,anscombe$y4)
lm(y1~x1, data=anscombe)##
## Call:
## lm(formula = y1 ~ x1, data = anscombe)
##
## Coefficients:
## (Intercept) x1
## 3.0001 0.5001lm(y2~x2, data=anscombe)##
## Call:
## lm(formula = y2 ~ x2, data = anscombe)
##
## Coefficients:
## (Intercept) x2
## 3.001 0.500lm(y3~x3, data=anscombe)##
## Call:
## lm(formula = y3 ~ x3, data = anscombe)
##
## Coefficients:
## (Intercept) x3
## 3.0025 0.4997lm(y4~x4, data=anscombe)##
## Call:
## lm(formula = y4 ~ x4, data = anscombe)
##
## Coefficients:
## (Intercept) x4
## 3.0017 0.4999attenu
182 x 5. カリフォルニアで起きた23回の地震について, いくつかの測定局で測定したピーク時の加速度.
head(attenu)## event mag station dist accel
## 1 1 7.0 117 12 0.359
## 2 2 7.4 1083 148 0.014
## 3 2 7.4 1095 42 0.196
## 4 2 7.4 283 85 0.135
## 5 2 7.4 135 107 0.062
## 6 2 7.4 475 109 0.054plot(attenu[,c(-1,-3)])
attitude
大きな金融機関の事務員の調査. 30 部局から約35人ずつを抽出し, 部局ごとの割合を求めたもの.
attitude## rating complaints privileges learning raises critical advance
## 1 43 51 30 39 61 92 45
## 2 63 64 51 54 63 73 47
## 3 71 70 68 69 76 86 48
## 4 61 63 45 47 54 84 35
## 5 81 78 56 66 71 83 47
## 6 43 55 49 44 54 49 34
## 7 58 67 42 56 66 68 35
## 8 71 75 50 55 70 66 41
## 9 72 82 72 67 71 83 31
## 10 67 61 45 47 62 80 41
## 11 64 53 53 58 58 67 34
## 12 67 60 47 39 59 74 41
## 13 69 62 57 42 55 63 25
## 14 68 83 83 45 59 77 35
## 15 77 77 54 72 79 77 46
## 16 81 90 50 72 60 54 36
## 17 74 85 64 69 79 79 63
## 18 65 60 65 75 55 80 60
## 19 65 70 46 57 75 85 46
## 20 50 58 68 54 64 78 52
## 21 50 40 33 34 43 64 33
## 22 64 61 52 62 66 80 41
## 23 53 66 52 50 63 80 37
## 24 40 37 42 58 50 57 49
## 25 63 54 42 48 66 75 33
## 26 66 77 66 63 88 76 72
## 27 78 75 58 74 80 78 49
## 28 48 57 44 45 51 83 38
## 29 85 85 71 71 77 74 55
## 30 82 82 39 59 64 78 39plot(attitude)
austres
1971年3月から1994年3月までの, 四半期ごとのオーストラリアの住民数（千人）.
austres## Qtr1 Qtr2 Qtr3 Qtr4
## 1971 13067.3 13130.5 13198.4
## 1972 13254.2 13303.7 13353.9 13409.3
## 1973 13459.2 13504.5 13552.6 13614.3
## 1974 13669.5 13722.6 13772.1 13832.0
## 1975 13862.6 13893.0 13926.8 13968.9
## 1976 14004.7 14033.1 14066.0 14110.1
## 1977 14155.6 14192.2 14231.7 14281.5
## 1978 14330.3 14359.3 14396.6 14430.8
## 1979 14478.4 14515.7 14554.9 14602.5
## 1980 14646.4 14695.4 14746.6 14807.4
## 1981 14874.4 14923.3 14988.7 15054.1
## 1982 15121.7 15184.2 15239.3 15288.9
## 1983 15346.2 15393.5 15439.0 15483.5
## 1984 15531.5 15579.4 15628.5 15677.3
## 1985 15736.7 15788.3 15839.7 15900.6
## 1986 15961.5 16018.3 16076.9 16139.0
## 1987 16203.0 16263.3 16327.9 16398.9
## 1988 16478.3 16538.2 16621.6 16697.0
## 1989 16777.2 16833.1 16891.6 16956.8
## 1990 17026.3 17085.4 17106.9 17169.4
## 1991 17239.4 17292.0 17354.2 17414.2
## 1992 17447.3 17482.6 17526.0 17568.7
## 1993 17627.1 17661.5plot(austres)
beaver1
beaver2とセットのデータ. 114 x 4. 10分ごとのビーバーの体温.
head(beaver1)## day time temp activ
## 1 346 840 36.33 0
## 2 346 850 36.34 0
## 3 346 900 36.35 0
## 4 346 910 36.42 0
## 5 346 920 36.55 0
## 6 346 930 36.69 0hist(beaver1$temp)
beaver2
beaver1とセットのデータ. 100 x 4. 10分ごとのビーバーの体温.
head(beaver2)## day time temp activ
## 1 307 930 36.58 0
## 2 307 940 36.73 0
## 3 307 950 36.93 0
## 4 307 1000 37.15 0
## 5 307 1010 37.23 0
## 6 307 1020 37.24 0hist(beaver2$temp)
cars
50 x 2. 1920年代の車のスピードと停止距離.
head(cars)## speed dist
## 1 4 2
## 2 4 10
## 3 7 4
## 4 7 22
## 5 8 16
## 6 9 10plot(cars)
chickwts
71 x 2. ニワトリの成長率について, 5種類のエサで比較した結果.
head(chickwts)## weight feed
## 1 179 horsebean
## 2 160 horsebean
## 3 136 horsebean
## 4 227 horsebean
## 5 217 horsebean
## 6 168 horsebeanboxplot(weight~feed,data=chickwts)
co2
Atmospheric concentrations of CO2 are expressed in parts per million (ppm) and reported in the preliminary 1997 SIO manometric mole fraction scale.
co2## Jan Feb Mar Apr May Jun Jul Aug Sep Oct
## 1959 315.42 316.31 316.50 317.56 318.13 318.00 316.39 314.65 313.68 313.18
## 1960 316.27 316.81 317.42 318.87 319.87 319.43 318.01 315.74 314.00 313.68
## 1961 316.73 317.54 318.38 319.31 320.42 319.61 318.42 316.63 314.83 315.16
## 1962 317.78 318.40 319.53 320.42 320.85 320.45 319.45 317.25 316.11 315.27
## 1963 318.58 318.92 319.70 321.22 322.08 321.31 319.58 317.61 316.05 315.83
## 1964 319.41 320.07 320.74 321.40 322.06 321.73 320.27 318.54 316.54 316.71
## 1965 319.27 320.28 320.73 321.97 322.00 321.71 321.05 318.71 317.66 317.14
## 1966 320.46 321.43 322.23 323.54 323.91 323.59 322.24 320.20 318.48 317.94
## 1967 322.17 322.34 322.88 324.25 324.83 323.93 322.38 320.76 319.10 319.24
## 1968 322.40 322.99 323.73 324.86 325.40 325.20 323.98 321.95 320.18 320.09
## 1969 323.83 324.26 325.47 326.50 327.21 326.54 325.72 323.50 322.22 321.62
## 1970 324.89 325.82 326.77 327.97 327.91 327.50 326.18 324.53 322.93 322.90
## 1971 326.01 326.51 327.01 327.62 328.76 328.40 327.20 325.27 323.20 323.40
## 1972 326.60 327.47 327.58 329.56 329.90 328.92 327.88 326.16 324.68 325.04
## 1973 328.37 329.40 330.14 331.33 332.31 331.90 330.70 329.15 327.35 327.02
## 1974 329.18 330.55 331.32 332.48 332.92 332.08 331.01 329.23 327.27 327.21
## 1975 330.23 331.25 331.87 333.14 333.80 333.43 331.73 329.90 328.40 328.17
## 1976 331.58 332.39 333.33 334.41 334.71 334.17 332.89 330.77 329.14 328.78
## 1977 332.75 333.24 334.53 335.90 336.57 336.10 334.76 332.59 331.42 330.98
## 1978 334.80 335.22 336.47 337.59 337.84 337.72 336.37 334.51 332.60 332.38
## 1979 336.05 336.59 337.79 338.71 339.30 339.12 337.56 335.92 333.75 333.70
## 1980 337.84 338.19 339.91 340.60 341.29 341.00 339.39 337.43 335.72 335.84
## 1981 339.06 340.30 341.21 342.33 342.74 342.08 340.32 338.26 336.52 336.68
## 1982 340.57 341.44 342.53 343.39 343.96 343.18 341.88 339.65 337.81 337.69
## 1983 341.20 342.35 342.93 344.77 345.58 345.14 343.81 342.21 339.69 339.82
## 1984 343.52 344.33 345.11 346.88 347.25 346.62 345.22 343.11 340.90 341.18
## 1985 344.79 345.82 347.25 348.17 348.74 348.07 346.38 344.51 342.92 342.62
## 1986 346.11 346.78 347.68 349.37 350.03 349.37 347.76 345.73 344.68 343.99
## 1987 347.84 348.29 349.23 350.80 351.66 351.07 349.33 347.92 346.27 346.18
## 1988 350.25 351.54 352.05 353.41 354.04 353.62 352.22 350.27 348.55 348.72
## 1989 352.60 352.92 353.53 355.26 355.52 354.97 353.75 351.52 349.64 349.83
## 1990 353.50 354.55 355.23 356.04 357.00 356.07 354.67 352.76 350.82 351.04
## 1991 354.59 355.63 357.03 358.48 359.22 358.12 356.06 353.92 352.05 352.11
## 1992 355.88 356.63 357.72 359.07 359.58 359.17 356.94 354.92 352.94 353.23
## 1993 356.63 357.10 358.32 359.41 360.23 359.55 357.53 355.48 353.67 353.95
## 1994 358.34 358.89 359.95 361.25 361.67 360.94 359.55 357.49 355.84 356.00
## 1995 359.98 361.03 361.66 363.48 363.82 363.30 361.94 359.50 358.11 357.80
## 1996 362.09 363.29 364.06 364.76 365.45 365.01 363.70 361.54 359.51 359.65
## 1997 363.23 364.06 364.61 366.40 366.84 365.68 364.52 362.57 360.24 360.83
## Nov Dec
## 1959 314.66 315.43
## 1960 314.84 316.03
## 1961 315.94 316.85
## 1962 316.53 317.53
## 1963 316.91 318.20
## 1964 317.53 318.55
## 1965 318.70 319.25
## 1966 319.63 320.87
## 1967 320.56 321.80
## 1968 321.16 322.74
## 1969 322.69 323.95
## 1970 323.85 324.96
## 1971 324.63 325.85
## 1972 326.34 327.39
## 1973 327.99 328.48
## 1974 328.29 329.41
## 1975 329.32 330.59
## 1976 330.14 331.52
## 1977 332.24 333.68
## 1978 333.75 334.78
## 1979 335.12 336.56
## 1980 336.93 338.04
## 1981 338.19 339.44
## 1982 339.09 340.32
## 1983 340.98 342.82
## 1984 342.80 344.04
## 1985 344.06 345.38
## 1986 345.48 346.72
## 1987 347.64 348.78
## 1988 349.91 351.18
## 1989 351.14 352.37
## 1990 352.69 354.07
## 1991 353.64 354.89
## 1992 354.09 355.33
## 1993 355.30 356.78
## 1994 357.59 359.05
## 1995 359.61 360.74
## 1996 360.80 362.38
## 1997 362.49 364.34plot(co2)
crimtab
イギリスとウェールズの主要な刑務所における, 服役中の20歳以上の男性犯罪者3000名のデータ. 中指の長さ（cm）と身長（cm）.
crimtab## 142.24 144.78 147.32 149.86 152.4 154.94 157.48 160.02 162.56 165.1
## 9.4 0 0 0 0 0 0 0 0 0 0
## 9.5 0 0 0 0 0 1 0 0 0 0
## 9.6 0 0 0 0 0 0 0 0 0 0
## 9.7 0 0 0 0 0 0 0 0 0 0
## 9.8 0 0 0 0 0 0 1 0 0 0
## 9.9 0 0 1 0 1 0 1 0 0 0
## 10 1 0 0 1 2 0 2 0 0 1
## 10.1 0 0 0 1 3 1 0 1 1 0
## 10.2 0 0 2 2 2 1 0 2 0 1
## 10.3 0 1 1 3 2 2 3 5 0 0
## 10.4 0 0 1 1 2 3 3 4 3 3
## 10.5 0 0 0 1 3 7 6 4 3 1
## 10.6 0 0 0 1 4 5 9 14 6 3
## 10.7 0 0 1 2 4 9 14 16 15 7
## 10.8 0 0 0 2 5 6 14 27 10 7
## 10.9 0 0 0 0 2 6 14 24 27 14
## 11 0 0 0 2 6 12 15 31 37 27
## 11.1 0 0 0 3 3 12 22 26 24 26
## 11.2 0 0 0 3 2 7 21 30 38 29
## 11.3 0 0 0 1 0 5 10 24 26 39
## 11.4 0 0 0 0 3 4 9 29 56 58
## 11.5 0 0 0 0 0 5 11 17 33 57
## 11.6 0 0 0 0 2 1 4 13 37 39
## 11.7 0 0 0 0 0 2 9 17 30 37
## 11.8 0 0 0 0 1 0 2 11 15 35
## 11.9 0 0 0 0 1 1 2 12 10 27
## 12 0 0 0 0 0 0 1 4 8 19
## 12.1 0 0 0 0 0 0 0 2 4 13
## 12.2 0 0 0 0 0 0 1 2 5 6
## 12.3 0 0 0 0 0 0 0 0 4 8
## 12.4 0 0 0 0 0 0 1 1 1 2
## 12.5 0 0 0 0 0 0 0 1 0 1
## 12.6 0 0 0 0 0 0 0 0 0 1
## 12.7 0 0 0 0 0 0 0 0 0 1
## 12.8 0 0 0 0 0 0 0 0 0 0
## 12.9 0 0 0 0 0 0 0 0 0 0
## 13 0 0 0 0 0 0 0 0 0 0
## 13.1 0 0 0 0 0 0 0 0 0 0
## 13.2 0 0 0 0 0 0 0 0 0 0
## 13.3 0 0 0 0 0 0 0 0 0 0
## 13.4 0 0 0 0 0 0 0 0 0 0
## 13.5 0 0 0 0 0 0 0 0 0 0
## 167.64 170.18 172.72 175.26 177.8 180.34 182.88 185.42 187.96 190.5
## 9.4 0 0 0 0 0 0 0 0 0 0
## 9.5 0 0 0 0 0 0 0 0 0 0
## 9.6 0 0 0 0 0 0 0 0 0 0
## 9.7 0 0 0 0 0 0 0 0 0 0
## 9.8 0 0 0 0 0 0 0 0 0 0
## 9.9 0 0 0 0 0 0 0 0 0 0
## 10 0 0 0 0 0 0 0 0 0 0
## 10.1 0 0 0 0 0 0 0 0 0 0
## 10.2 0 0 0 0 0 0 0 0 0 0
## 10.3 0 0 0 0 0 0 0 0 0 0
## 10.4 0 0 0 0 0 0 0 0 0 0
## 10.5 3 1 0 1 0 0 0 0 0 0
## 10.6 1 0 0 1 0 0 0 0 0 0
## 10.7 3 1 2 0 0 0 0 0 0 0
## 10.8 1 2 1 0 0 0 0 0 0 0
## 10.9 10 4 1 0 0 0 0 0 0 0
## 11 17 10 6 0 0 0 0 0 0 0
## 11.1 24 7 4 1 0 0 0 0 0 0
## 11.2 27 20 4 1 0 0 0 0 0 0
## 11.3 26 24 7 2 0 0 0 0 0 0
## 11.4 26 22 10 11 0 0 0 0 0 0
## 11.5 38 34 25 11 2 0 0 0 0 0
## 11.6 48 38 27 12 2 2 0 1 0 0
## 11.7 48 45 24 9 9 2 0 0 0 0
## 11.8 41 34 29 10 5 1 0 0 0 0
## 11.9 32 35 19 10 9 3 1 0 0 0
## 12 42 39 22 16 8 2 2 0 0 0
## 12.1 22 28 15 27 10 4 1 0 0 0
## 12.2 23 17 16 11 8 1 1 0 0 0
## 12.3 10 13 20 23 6 5 0 0 0 0
## 12.4 7 12 4 7 7 1 0 0 1 0
## 12.5 3 12 11 8 6 8 0 2 0 0
## 12.6 0 3 5 7 8 6 3 1 1 0
## 12.7 1 7 5 5 8 2 2 0 0 0
## 12.8 1 2 3 1 8 5 3 1 1 0
## 12.9 0 1 2 2 0 1 1 0 0 0
## 13 3 0 1 0 1 0 2 1 0 0
## 13.1 0 1 1 0 0 0 0 0 0 0
## 13.2 1 1 0 1 0 3 0 0 0 0
## 13.3 0 0 0 0 0 0 1 0 1 0
## 13.4 0 0 0 0 0 0 0 0 0 0
## 13.5 0 0 0 0 0 0 0 1 0 0
## 193.04 195.58
## 9.4 0 0
## 9.5 0 0
## 9.6 0 0
## 9.7 0 0
## 9.8 0 0
## 9.9 0 0
## 10 0 0
## 10.1 0 0
## 10.2 0 0
## 10.3 0 0
## 10.4 0 0
## 10.5 0 0
## 10.6 0 0
## 10.7 0 0
## 10.8 0 0
## 10.9 0 0
## 11 0 0
## 11.1 0 0
## 11.2 0 1
## 11.3 0 0
## 11.4 0 0
## 11.5 0 0
## 11.6 0 0
## 11.7 0 0
## 11.8 0 0
## 11.9 0 0
## 12 0 0
## 12.1 0 0
## 12.2 0 0
## 12.3 0 0
## 12.4 0 0
## 12.5 0 0
## 12.6 0 0
## 12.7 0 0
## 12.8 0 0
## 12.9 0 0
## 13 0 0
## 13.1 0 0
## 13.2 0 0
## 13.3 0 0
## 13.4 0 0
## 13.5 0 0discoveries
1860〜1959年の各年における, 偉大な発明や科学上の発見の数.
discoveries## Time Series:
## Start = 1860
## End = 1959
## Frequency = 1
## [1] 5 3 0 2 0 3 2 3 6 1 2 1 2 1 3 3 3 5 2 4 4 0 2
## [24] 3 7 12 3 10 9 2 3 7 7 2 3 3 6 2 4 3 5 2 2 4 0 4
## [47] 2 5 2 3 3 6 5 8 3 6 6 0 5 2 2 2 6 3 4 4 2 2 4
## [70] 7 5 3 3 0 2 2 2 1 3 4 2 2 1 1 1 2 1 4 4 3 2 1
## [93] 4 1 1 1 0 0 2 0plot(discoveries)
esoph
フランスのイル＝エ＝ヴィレーヌにおける, 食道癌についてのケースコントロール研究.
head(esoph)## agegp alcgp tobgp ncases ncontrols
## 1 25-34 0-39g/day 0-9g/day 0 40
## 2 25-34 0-39g/day 10-19 0 10
## 3 25-34 0-39g/day 20-29 0 6
## 4 25-34 0-39g/day 30+ 0 5
## 5 25-34 40-79 0-9g/day 0 27
## 6 25-34 40-79 10-19 0 7glm(cbind(ncases,ncontrols)~agegp+tobgp*alcgp,data=esoph,family=binomial())##
## Call: glm(formula = cbind(ncases, ncontrols) ~ agegp + tobgp * alcgp,
## family = binomial(), data = esoph)
##
## Coefficients:
## (Intercept) agegp.L agegp.Q agegp.C
## -1.75985 2.99646 -1.35008 0.13436
## agegp^4 agegp^5 tobgp.L tobgp.Q
## 0.07098 -0.21347 0.63846 0.02922
## tobgp.C alcgp.L alcgp.Q alcgp.C
## 0.15607 1.37077 -0.14913 0.22823
## tobgp.L:alcgp.L tobgp.Q:alcgp.L tobgp.C:alcgp.L tobgp.L:alcgp.Q
## -0.70426 0.12225 -0.29187 0.12948
## tobgp.Q:alcgp.Q tobgp.C:alcgp.Q tobgp.L:alcgp.C tobgp.Q:alcgp.C
## -0.44527 -0.05205 -0.16118 0.04843
## tobgp.C:alcgp.C
## -0.13905
##
## Degrees of Freedom: 87 Total (i.e. Null); 67 Residual
## Null Deviance: 227.2
## Residual Deviance: 47.48 AIC: 237euro
ユーロに参加した国々のユーロへの交換率.
euro## ATS BEF DEM ESP FIM FRF
## 13.760300 40.339900 1.955830 166.386000 5.945730 6.559570
## IEP ITL LUF NLG PTE
## 0.787564 1936.270000 40.339900 2.203710 200.482000glm(cbind(ncases,ncontrols)~agegp+tobgp*alcgp,data=esoph,family=binomial())##
## Call: glm(formula = cbind(ncases, ncontrols) ~ agegp + tobgp * alcgp,
## family = binomial(), data = esoph)
##
## Coefficients:
## (Intercept) agegp.L agegp.Q agegp.C
## -1.75985 2.99646 -1.35008 0.13436
## agegp^4 agegp^5 tobgp.L tobgp.Q
## 0.07098 -0.21347 0.63846 0.02922
## tobgp.C alcgp.L alcgp.Q alcgp.C
## 0.15607 1.37077 -0.14913 0.22823
## tobgp.L:alcgp.L tobgp.Q:alcgp.L tobgp.C:alcgp.L tobgp.L:alcgp.Q
## -0.70426 0.12225 -0.29187 0.12948
## tobgp.Q:alcgp.Q tobgp.C:alcgp.Q tobgp.L:alcgp.C tobgp.Q:alcgp.C
## -0.44527 -0.05205 -0.16118 0.04843
## tobgp.C:alcgp.C
## -0.13905
##
## Degrees of Freedom: 87 Total (i.e. Null); 67 Residual
## Null Deviance: 227.2
## Residual Deviance: 47.48 AIC: 237euro.cross (euro)
ユーロ参加時の各通貨の交換率.
euro.cross## ATS BEF DEM ESP FIM
## ATS 1.000000000 2.93161486 0.142135709 12.0917422 0.432093050
## BEF 0.341108927 1.00000000 0.048483759 4.1246012 0.147390797
## DEM 7.035529673 20.62546336 1.000000000 85.0718109 3.040003477
## ESP 0.082701069 0.24244768 0.011754775 1.0000000 0.035734557
## FIM 2.314316324 6.78468413 0.328946992 27.9841163 1.000000000
## FRF 2.097744212 6.14977811 0.298164361 25.3653822 0.906420695
## IEP 17.471976881 51.22110711 2.483391826 211.2666399 7.549519785
## ITL 0.007106602 0.02083382 0.001010102 0.0859312 0.003070713
## LUF 0.341108927 1.00000000 0.048483759 4.1246012 0.147390797
## NLG 6.244151907 18.30544854 0.887516960 75.5026750 2.698054644
## PTE 0.068636087 0.20121457 0.009755639 0.8299299 0.029657176
## FRF IEP ITL LUF NLG
## ATS 0.476702543 0.0572345080 140.714229 2.93161486 0.160149851
## BEF 0.162607493 0.0195232016 47.998880 1.00000000 0.054628544
## DEM 3.353854885 0.4026750791 989.999131 20.62546336 1.126739032
## ESP 0.039423810 0.0047333550 11.637217 0.24244768 0.013244564
## FIM 1.103240477 0.1324587561 325.657236 6.78468413 0.370637415
## FRF 1.000000000 0.1200633578 295.182459 6.14977811 0.335953424
## IEP 8.328935807 1.0000000000 2458.555749 51.22110711 2.798134501
## ITL 0.003387735 0.0004067429 1.000000 0.02083382 0.001138121
## LUF 0.162607493 0.0195232016 47.998880 1.00000000 0.054628544
## NLG 2.976603092 0.3573809621 878.641019 18.30544854 1.000000000
## PTE 0.032718997 0.0039283527 9.658074 0.20121457 0.010992059
## PTE
## ATS 14.5695951
## BEF 4.9698190
## DEM 102.5048189
## ESP 1.2049211
## FIM 33.7186519
## FRF 30.5632839
## IEP 254.5596294
## ITL 0.1035403
## LUF 4.9698190
## NLG 90.9747653
## PTE 1.0000000eurodist
ヨーロッパの21都市の間の直線距離（km）.
eurodist## Athens Barcelona Brussels Calais Cherbourg Cologne
## Barcelona 3313
## Brussels 2963 1318
## Calais 3175 1326 204
## Cherbourg 3339 1294 583 460
## Cologne 2762 1498 206 409 785
## Copenhagen 3276 2218 966 1136 1545 760
## Geneva 2610 803 677 747 853 1662
## Gibraltar 4485 1172 2256 2224 2047 2436
## Hamburg 2977 2018 597 714 1115 460
## Hook of Holland 3030 1490 172 330 731 269
## Lisbon 4532 1305 2084 2052 1827 2290
## Lyons 2753 645 690 739 789 714
## Madrid 3949 636 1558 1550 1347 1764
## Marseilles 2865 521 1011 1059 1101 1035
## Milan 2282 1014 925 1077 1209 911
## Munich 2179 1365 747 977 1160 583
## Paris 3000 1033 285 280 340 465
## Rome 817 1460 1511 1662 1794 1497
## Stockholm 3927 2868 1616 1786 2196 1403
## Vienna 1991 1802 1175 1381 1588 937
## Copenhagen Geneva Gibraltar Hamburg Hook of Holland Lisbon
## Barcelona
## Brussels
## Calais
## Cherbourg
## Cologne
## Copenhagen
## Geneva 1418
## Gibraltar 3196 1975
## Hamburg 460 1118 2897
## Hook of Holland 269 895 2428 550
## Lisbon 2971 1936 676 2671 2280
## Lyons 1458 158 1817 1159 863 1178
## Madrid 2498 1439 698 2198 1730 668
## Marseilles 1778 425 1693 1479 1183 1762
## Milan 1537 328 2185 1238 1098 2250
## Munich 1104 591 2565 805 851 2507
## Paris 1176 513 1971 877 457 1799
## Rome 2050 995 2631 1751 1683 2700
## Stockholm 650 2068 3886 949 1500 3231
## Vienna 1455 1019 2974 1155 1205 2937
## Lyons Madrid Marseilles Milan Munich Paris Rome Stockholm
## Barcelona
## Brussels
## Calais
## Cherbourg
## Cologne
## Copenhagen
## Geneva
## Gibraltar
## Hamburg
## Hook of Holland
## Lisbon
## Lyons
## Madrid 1281
## Marseilles 320 1157
## Milan 328 1724 618
## Munich 724 2010 1109 331
## Paris 471 1273 792 856 821
## Rome 1048 2097 1011 586 946 1476
## Stockholm 2108 3188 2428 2187 1754 1827 2707
## Vienna 1157 2409 1363 898 428 1249 1209 2105plot(hclust(eurodist))
faithful
272 x 2. オールドフェイスフル（ワイオミング州の間欠泉）の噴出している時間および次に噴出するまでの時間（分）.
head(faithful)## eruptions waiting
## 1 3.600 79
## 2 1.800 54
## 3 3.333 74
## 4 2.283 62
## 5 4.533 85
## 6 2.883 55plot(faithful)
fdeaths (UKLungDeaths)
1974〜79年のイギリスでの気管支炎, 肺気腫, 喘息での死者数（女性）. ldeaths は男女合わせて, mdeaths は男性のみ.
fdeaths## Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
## 1974 901 689 827 677 522 406 441 393 387 582 578 666
## 1975 830 752 785 664 467 438 421 412 343 440 531 771
## 1976 767 1141 896 532 447 420 376 330 357 445 546 764
## 1977 862 660 663 643 502 392 411 348 387 385 411 638
## 1978 796 853 737 546 530 446 431 362 387 430 425 679
## 1979 821 785 727 612 478 429 405 379 393 411 487 574plot(fdeaths)
freeny
Freeny (1977) による四半期ごとの収入と説明変数のデータ.
freeny## y lag.quarterly.revenue price.index income.level
## 1962.25 8.79236 8.79636 4.70997 5.82110
## 1962.5 8.79137 8.79236 4.70217 5.82558
## 1962.75 8.81486 8.79137 4.68944 5.83112
## 1963 8.81301 8.81486 4.68558 5.84046
## 1963.25 8.90751 8.81301 4.64019 5.85036
## 1963.5 8.93673 8.90751 4.62553 5.86464
## 1963.75 8.96161 8.93673 4.61991 5.87769
## 1964 8.96044 8.96161 4.61654 5.89763
## 1964.25 9.00868 8.96044 4.61407 5.92574
## 1964.5 9.03049 9.00868 4.60766 5.94232
## 1964.75 9.06906 9.03049 4.60227 5.95365
## 1965 9.05871 9.06906 4.58960 5.96120
## 1965.25 9.10698 9.05871 4.57592 5.97805
## 1965.5 9.12685 9.10698 4.58661 6.00377
## 1965.75 9.17096 9.12685 4.57997 6.02829
## 1966 9.18665 9.17096 4.57176 6.03475
## 1966.25 9.23823 9.18665 4.56104 6.03906
## 1966.5 9.26487 9.23823 4.54906 6.05046
## 1966.75 9.28436 9.26487 4.53957 6.05563
## 1967 9.31378 9.28436 4.51018 6.06093
## 1967.25 9.35025 9.31378 4.50352 6.07103
## 1967.5 9.35835 9.35025 4.49360 6.08018
## 1967.75 9.39767 9.35835 4.46505 6.08858
## 1968 9.42150 9.39767 4.44924 6.10199
## 1968.25 9.44223 9.42150 4.43966 6.11207
## 1968.5 9.48721 9.44223 4.42025 6.11596
## 1968.75 9.52374 9.48721 4.41060 6.12129
## 1969 9.53980 9.52374 4.41151 6.12200
## 1969.25 9.58123 9.53980 4.39810 6.13119
## 1969.5 9.60048 9.58123 4.38513 6.14705
## 1969.75 9.64496 9.60048 4.37320 6.15336
## 1970 9.64390 9.64496 4.32770 6.15627
## 1970.25 9.69405 9.64390 4.32023 6.16274
## 1970.5 9.69958 9.69405 4.30909 6.17369
## 1970.75 9.68683 9.69958 4.30909 6.16135
## 1971 9.71774 9.68683 4.30552 6.18231
## 1971.25 9.74924 9.71774 4.29627 6.18768
## 1971.5 9.77536 9.74924 4.27839 6.19377
## 1971.75 9.79424 9.77536 4.27789 6.20030
## market.potential
## 1962.25 12.9699
## 1962.5 12.9733
## 1962.75 12.9774
## 1963 12.9806
## 1963.25 12.9831
## 1963.5 12.9854
## 1963.75 12.9900
## 1964 12.9943
## 1964.25 12.9992
## 1964.5 13.0033
## 1964.75 13.0099
## 1965 13.0159
## 1965.25 13.0212
## 1965.5 13.0265
## 1965.75 13.0351
## 1966 13.0429
## 1966.25 13.0497
## 1966.5 13.0551
## 1966.75 13.0634
## 1967 13.0693
## 1967.25 13.0737
## 1967.5 13.0770
## 1967.75 13.0849
## 1968 13.0918
## 1968.25 13.0950
## 1968.5 13.0984
## 1968.75 13.1089
## 1969 13.1169
## 1969.25 13.1222
## 1969.5 13.1266
## 1969.75 13.1356
## 1970 13.1415
## 1970.25 13.1444
## 1970.5 13.1459
## 1970.75 13.1520
## 1971 13.1593
## 1971.25 13.1579
## 1971.5 13.1625
## 1971.75 13.1664plot(freeny)
freeny.x
Freeny (1977) による四半期ごとの収入と説明変数のデータ. freeny.x は説明変数のみ.
freeny.x## lag quarterly revenue price index income level market potential
## [1,] 8.79636 4.70997 5.82110 12.9699
## [2,] 8.79236 4.70217 5.82558 12.9733
## [3,] 8.79137 4.68944 5.83112 12.9774
## [4,] 8.81486 4.68558 5.84046 12.9806
## [5,] 8.81301 4.64019 5.85036 12.9831
## [6,] 8.90751 4.62553 5.86464 12.9854
## [7,] 8.93673 4.61991 5.87769 12.9900
## [8,] 8.96161 4.61654 5.89763 12.9943
## [9,] 8.96044 4.61407 5.92574 12.9992
## [10,] 9.00868 4.60766 5.94232 13.0033
## [11,] 9.03049 4.60227 5.95365 13.0099
## [12,] 9.06906 4.58960 5.96120 13.0159
## [13,] 9.05871 4.57592 5.97805 13.0212
## [14,] 9.10698 4.58661 6.00377 13.0265
## [15,] 9.12685 4.57997 6.02829 13.0351
## [16,] 9.17096 4.57176 6.03475 13.0429
## [17,] 9.18665 4.56104 6.03906 13.0497
## [18,] 9.23823 4.54906 6.05046 13.0551
## [19,] 9.26487 4.53957 6.05563 13.0634
## [20,] 9.28436 4.51018 6.06093 13.0693
## [21,] 9.31378 4.50352 6.07103 13.0737
## [22,] 9.35025 4.49360 6.08018 13.0770
## [23,] 9.35835 4.46505 6.08858 13.0849
## [24,] 9.39767 4.44924 6.10199 13.0918
## [25,] 9.42150 4.43966 6.11207 13.0950
## [26,] 9.44223 4.42025 6.11596 13.0984
## [27,] 9.48721 4.41060 6.12129 13.1089
## [28,] 9.52374 4.41151 6.12200 13.1169
## [29,] 9.53980 4.39810 6.13119 13.1222
## [30,] 9.58123 4.38513 6.14705 13.1266
## [31,] 9.60048 4.37320 6.15336 13.1356
## [32,] 9.64496 4.32770 6.15627 13.1415
## [33,] 9.64390 4.32023 6.16274 13.1444
## [34,] 9.69405 4.30909 6.17369 13.1459
## [35,] 9.69958 4.30909 6.16135 13.1520
## [36,] 9.68683 4.30552 6.18231 13.1593
## [37,] 9.71774 4.29627 6.18768 13.1579
## [38,] 9.74924 4.27839 6.19377 13.1625
## [39,] 9.77536 4.27789 6.20030 13.1664plot(freeny.x[,2],type="l")
freeny.y
Freeny (1977) による四半期ごとの収入と説明変数のデータ. freeny.y は収入のみ.
freeny.y## Qtr1 Qtr2 Qtr3 Qtr4
## 1962 8.79236 8.79137 8.81486
## 1963 8.81301 8.90751 8.93673 8.96161
## 1964 8.96044 9.00868 9.03049 9.06906
## 1965 9.05871 9.10698 9.12685 9.17096
## 1966 9.18665 9.23823 9.26487 9.28436
## 1967 9.31378 9.35025 9.35835 9.39767
## 1968 9.42150 9.44223 9.48721 9.52374
## 1969 9.53980 9.58123 9.60048 9.64496
## 1970 9.64390 9.69405 9.69958 9.68683
## 1971 9.71774 9.74924 9.77536 9.79424plot(freeny.y)
infert
This is a matched case-control study dating from before the availability of conditional logistic regression.
head(infert)## education age parity induced case spontaneous stratum pooled.stratum
## 1 0-5yrs 26 6 1 1 2 1 3
## 2 0-5yrs 42 1 1 1 0 2 1
## 3 0-5yrs 39 6 2 1 0 3 4
## 4 0-5yrs 34 4 2 1 0 4 2
## 5 6-11yrs 35 3 1 1 1 5 32
## 6 6-11yrs 36 4 2 1 1 6 36plot(infert)
iris
150 x 5. Fisherのアイリスデータ.
head(iris)## Sepal.Length Sepal.Width Petal.Length Petal.Width Species
## 1 5.1 3.5 1.4 0.2 setosa
## 2 4.9 3.0 1.4 0.2 setosa
## 3 4.7 3.2 1.3 0.2 setosa
## 4 4.6 3.1 1.5 0.2 setosa
## 5 5.0 3.6 1.4 0.2 setosa
## 6 5.4 3.9 1.7 0.4 setosaplot(iris[,1:4],col=iris[,5])
iris3
上と同じデータ. ただし形式が違う.
iris3## , , Setosa
##
## Sepal L. Sepal W. Petal L. Petal W.
## [1,] 5.1 3.5 1.4 0.2
## [2,] 4.9 3.0 1.4 0.2
## [3,] 4.7 3.2 1.3 0.2
## [4,] 4.6 3.1 1.5 0.2
## [5,] 5.0 3.6 1.4 0.2
## [6,] 5.4 3.9 1.7 0.4
## [7,] 4.6 3.4 1.4 0.3
## [8,] 5.0 3.4 1.5 0.2
## [9,] 4.4 2.9 1.4 0.2
## [10,] 4.9 3.1 1.5 0.1
## [11,] 5.4 3.7 1.5 0.2
## [12,] 4.8 3.4 1.6 0.2
## [13,] 4.8 3.0 1.4 0.1
## [14,] 4.3 3.0 1.1 0.1
## [15,] 5.8 4.0 1.2 0.2
## [16,] 5.7 4.4 1.5 0.4
## [17,] 5.4 3.9 1.3 0.4
## [18,] 5.1 3.5 1.4 0.3
## [19,] 5.7 3.8 1.7 0.3
## [20,] 5.1 3.8 1.5 0.3
## [21,] 5.4 3.4 1.7 0.2
## [22,] 5.1 3.7 1.5 0.4
## [23,] 4.6 3.6 1.0 0.2
## [24,] 5.1 3.3 1.7 0.5
## [25,] 4.8 3.4 1.9 0.2
## [26,] 5.0 3.0 1.6 0.2
## [27,] 5.0 3.4 1.6 0.4
## [28,] 5.2 3.5 1.5 0.2
## [29,] 5.2 3.4 1.4 0.2
## [30,] 4.7 3.2 1.6 0.2
## [31,] 4.8 3.1 1.6 0.2
## [32,] 5.4 3.4 1.5 0.4
## [33,] 5.2 4.1 1.5 0.1
## [34,] 5.5 4.2 1.4 0.2
## [35,] 4.9 3.1 1.5 0.2
## [36,] 5.0 3.2 1.2 0.2
## [37,] 5.5 3.5 1.3 0.2
## [38,] 4.9 3.6 1.4 0.1
## [39,] 4.4 3.0 1.3 0.2
## [40,] 5.1 3.4 1.5 0.2
## [41,] 5.0 3.5 1.3 0.3
## [42,] 4.5 2.3 1.3 0.3
## [43,] 4.4 3.2 1.3 0.2
## [44,] 5.0 3.5 1.6 0.6
## [45,] 5.1 3.8 1.9 0.4
## [46,] 4.8 3.0 1.4 0.3
## [47,] 5.1 3.8 1.6 0.2
## [48,] 4.6 3.2 1.4 0.2
## [49,] 5.3 3.7 1.5 0.2
## [50,] 5.0 3.3 1.4 0.2
##
## , , Versicolor
##
## Sepal L. Sepal W. Petal L. Petal W.
## [1,] 7.0 3.2 4.7 1.4
## [2,] 6.4 3.2 4.5 1.5
## [3,] 6.9 3.1 4.9 1.5
## [4,] 5.5 2.3 4.0 1.3
## [5,] 6.5 2.8 4.6 1.5
## [6,] 5.7 2.8 4.5 1.3
## [7,] 6.3 3.3 4.7 1.6
## [8,] 4.9 2.4 3.3 1.0
## [9,] 6.6 2.9 4.6 1.3
## [10,] 5.2 2.7 3.9 1.4
## [11,] 5.0 2.0 3.5 1.0
## [12,] 5.9 3.0 4.2 1.5
## [13,] 6.0 2.2 4.0 1.0
## [14,] 6.1 2.9 4.7 1.4
## [15,] 5.6 2.9 3.6 1.3
## [16,] 6.7 3.1 4.4 1.4
## [17,] 5.6 3.0 4.5 1.5
## [18,] 5.8 2.7 4.1 1.0
## [19,] 6.2 2.2 4.5 1.5
## [20,] 5.6 2.5 3.9 1.1
## [21,] 5.9 3.2 4.8 1.8
## [22,] 6.1 2.8 4.0 1.3
## [23,] 6.3 2.5 4.9 1.5
## [24,] 6.1 2.8 4.7 1.2
## [25,] 6.4 2.9 4.3 1.3
## [26,] 6.6 3.0 4.4 1.4
## [27,] 6.8 2.8 4.8 1.4
## [28,] 6.7 3.0 5.0 1.7
## [29,] 6.0 2.9 4.5 1.5
## [30,] 5.7 2.6 3.5 1.0
## [31,] 5.5 2.4 3.8 1.1
## [32,] 5.5 2.4 3.7 1.0
## [33,] 5.8 2.7 3.9 1.2
## [34,] 6.0 2.7 5.1 1.6
## [35,] 5.4 3.0 4.5 1.5
## [36,] 6.0 3.4 4.5 1.6
## [37,] 6.7 3.1 4.7 1.5
## [38,] 6.3 2.3 4.4 1.3
## [39,] 5.6 3.0 4.1 1.3
## [40,] 5.5 2.5 4.0 1.3
## [41,] 5.5 2.6 4.4 1.2
## [42,] 6.1 3.0 4.6 1.4
## [43,] 5.8 2.6 4.0 1.2
## [44,] 5.0 2.3 3.3 1.0
## [45,] 5.6 2.7 4.2 1.3
## [46,] 5.7 3.0 4.2 1.2
## [47,] 5.7 2.9 4.2 1.3
## [48,] 6.2 2.9 4.3 1.3
## [49,] 5.1 2.5 3.0 1.1
## [50,] 5.7 2.8 4.1 1.3
##
## , , Virginica
##
## Sepal L. Sepal W. Petal L. Petal W.
## [1,] 6.3 3.3 6.0 2.5
## [2,] 5.8 2.7 5.1 1.9
## [3,] 7.1 3.0 5.9 2.1
## [4,] 6.3 2.9 5.6 1.8
## [5,] 6.5 3.0 5.8 2.2
## [6,] 7.6 3.0 6.6 2.1
## [7,] 4.9 2.5 4.5 1.7
## [8,] 7.3 2.9 6.3 1.8
## [9,] 6.7 2.5 5.8 1.8
## [10,] 7.2 3.6 6.1 2.5
## [11,] 6.5 3.2 5.1 2.0
## [12,] 6.4 2.7 5.3 1.9
## [13,] 6.8 3.0 5.5 2.1
## [14,] 5.7 2.5 5.0 2.0
## [15,] 5.8 2.8 5.1 2.4
## [16,] 6.4 3.2 5.3 2.3
## [17,] 6.5 3.0 5.5 1.8
## [18,] 7.7 3.8 6.7 2.2
## [19,] 7.7 2.6 6.9 2.3
## [20,] 6.0 2.2 5.0 1.5
## [21,] 6.9 3.2 5.7 2.3
## [22,] 5.6 2.8 4.9 2.0
## [23,] 7.7 2.8 6.7 2.0
## [24,] 6.3 2.7 4.9 1.8
## [25,] 6.7 3.3 5.7 2.1
## [26,] 7.2 3.2 6.0 1.8
## [27,] 6.2 2.8 4.8 1.8
## [28,] 6.1 3.0 4.9 1.8
## [29,] 6.4 2.8 5.6 2.1
## [30,] 7.2 3.0 5.8 1.6
## [31,] 7.4 2.8 6.1 1.9
## [32,] 7.9 3.8 6.4 2.0
## [33,] 6.4 2.8 5.6 2.2
## [34,] 6.3 2.8 5.1 1.5
## [35,] 6.1 2.6 5.6 1.4
## [36,] 7.7 3.0 6.1 2.3
## [37,] 6.3 3.4 5.6 2.4
## [38,] 6.4 3.1 5.5 1.8
## [39,] 6.0 3.0 4.8 1.8
## [40,] 6.9 3.1 5.4 2.1
## [41,] 6.7 3.1 5.6 2.4
## [42,] 6.9 3.1 5.1 2.3
## [43,] 5.8 2.7 5.1 1.9
## [44,] 6.8 3.2 5.9 2.3
## [45,] 6.7 3.3 5.7 2.5
## [46,] 6.7 3.0 5.2 2.3
## [47,] 6.3 2.5 5.0 1.9
## [48,] 6.5 3.0 5.2 2.0
## [49,] 6.2 3.4 5.4 2.3
## [50,] 5.9 3.0 5.1 1.8islands
大陸・島ごとの面積（単位1000マイル^2, 10,000マイル^2を超えるもののみ）.
islands## Africa Antarctica Asia Australia
## 11506 5500 16988 2968
## Axel Heiberg Baffin Banks Borneo
## 16 184 23 280
## Britain Celebes Celon Cuba
## 84 73 25 43
## Devon Ellesmere Europe Greenland
## 21 82 3745 840
## Hainan Hispaniola Hokkaido Honshu
## 13 30 30 89
## Iceland Ireland Java Kyushu
## 40 33 49 14
## Luzon Madagascar Melville Mindanao
## 42 227 16 36
## Moluccas New Britain New Guinea New Zealand (N)
## 29 15 306 44
## New Zealand (S) Newfoundland North America Novaya Zemlya
## 58 43 9390 32
## Prince of Wales Sakhalin South America Southampton
## 13 29 6795 16
## Spitsbergen Sumatra Taiwan Tasmania
## 15 183 14 26
## Tierra del Fuego Timor Vancouver Victoria
## 19 13 12 82hist(islands)
ldeaths
1974〜79年のイギリスでの気管支炎, 肺気腫, 喘息での死者数（男女合わせて）. mdeaths は男性のみ, fdeaths は女性のみ.
ldeaths## Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
## 1974 3035 2552 2704 2554 2014 1655 1721 1524 1596 2074 2199 2512
## 1975 2933 2889 2938 2497 1870 1726 1607 1545 1396 1787 2076 2837
## 1976 2787 3891 3179 2011 1636 1580 1489 1300 1356 1653 2013 2823
## 1977 3102 2294 2385 2444 1748 1554 1498 1361 1346 1564 1640 2293
## 1978 2815 3137 2679 1969 1870 1633 1529 1366 1357 1570 1535 2491
## 1979 3084 2605 2573 2143 1693 1504 1461 1354 1333 1492 1781 1915plot(ldeaths)
lh
48時点. ある女性の10分ごとの黄体形成ホルモンの時系列データ.
lh## Time Series:
## Start = 1
## End = 48
## Frequency = 1
## [1] 2.4 2.4 2.4 2.2 2.1 1.5 2.3 2.3 2.5 2.0 1.9 1.7 2.2 1.8 3.2 3.2 2.7
## [18] 2.2 2.2 1.9 1.9 1.8 2.7 3.0 2.3 2.0 2.0 2.9 2.9 2.7 2.7 2.3 2.6 2.4
## [35] 1.8 1.7 1.5 1.4 2.1 3.3 3.5 3.5 3.1 2.6 2.1 3.4 3.0 2.9plot(lh)
longley
マクロ経済学のデータセット. 多重共線性がかなり起きている有名なデータ.
longley## GNP.deflator GNP Unemployed Armed.Forces Population Year Employed
## 1947 83.0 234.289 235.6 159.0 107.608 1947 60.323
## 1948 88.5 259.426 232.5 145.6 108.632 1948 61.122
## 1949 88.2 258.054 368.2 161.6 109.773 1949 60.171
## 1950 89.5 284.599 335.1 165.0 110.929 1950 61.187
## 1951 96.2 328.975 209.9 309.9 112.075 1951 63.221
## 1952 98.1 346.999 193.2 359.4 113.270 1952 63.639
## 1953 99.0 365.385 187.0 354.7 115.094 1953 64.989
## 1954 100.0 363.112 357.8 335.0 116.219 1954 63.761
## 1955 101.2 397.469 290.4 304.8 117.388 1955 66.019
## 1956 104.6 419.180 282.2 285.7 118.734 1956 67.857
## 1957 108.4 442.769 293.6 279.8 120.445 1957 68.169
## 1958 110.8 444.546 468.1 263.7 121.950 1958 66.513
## 1959 112.6 482.704 381.3 255.2 123.366 1959 68.655
## 1960 114.2 502.601 393.1 251.4 125.368 1960 69.564
## 1961 115.7 518.173 480.6 257.2 127.852 1961 69.331
## 1962 116.9 554.894 400.7 282.7 130.081 1962 70.551plot(longley)
lynx
1821〜1934年にカナダで罠にかかったオオヤマネコの年間数.
lynx## Time Series:
## Start = 1821
## End = 1934
## Frequency = 1
## [1] 269 321 585 871 1475 2821 3928 5943 4950 2577 523 98 184 279
## [15] 409 2285 2685 3409 1824 409 151 45 68 213 546 1033 2129 2536
## [29] 957 361 377 225 360 731 1638 2725 2871 2119 684 299 236 245
## [43] 552 1623 3311 6721 4254 687 255 473 358 784 1594 1676 2251 1426
## [57] 756 299 201 229 469 736 2042 2811 4431 2511 389 73 39 49
## [71] 59 188 377 1292 4031 3495 587 105 153 387 758 1307 3465 6991
## [85] 6313 3794 1836 345 382 808 1388 2713 3800 3091 2985 3790 674 81
## [99] 80 108 229 399 1132 2432 3574 2935 1537 529 485 662 1000 1590
## [113] 2657 3396plot(lynx)
mdeaths
1974〜79年のイギリスでの気管支炎, 肺気腫, 喘息での死者数（男性）. ldeaths は男女合わせて, fdeaths は女性のみ.
mdeaths## Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
## 1974 2134 1863 1877 1877 1492 1249 1280 1131 1209 1492 1621 1846
## 1975 2103 2137 2153 1833 1403 1288 1186 1133 1053 1347 1545 2066
## 1976 2020 2750 2283 1479 1189 1160 1113 970 999 1208 1467 2059
## 1977 2240 1634 1722 1801 1246 1162 1087 1013 959 1179 1229 1655
## 1978 2019 2284 1942 1423 1340 1187 1098 1004 970 1140 1110 1812
## 1979 2263 1820 1846 1531 1215 1075 1056 975 940 1081 1294 1341plot(mdeaths)
morley
1879年に行われた光の速度（km/sec, 299,000 を減じた値）の測定. なお, 光速は 299,792.458 km/sec である.
head(morley)## Expt Run Speed
## 001 1 1 850
## 002 1 2 740
## 003 1 3 900
## 004 1 4 1070
## 005 1 5 930
## 006 1 6 850plot(Speed~Expt,data=morley)
mtcars
32 x 11. 1974年の Motor Trend US 誌による, 32 の乗用車（1973〜74年モデル）のスペックのデータ.
mtcars## mpg cyl disp hp drat wt qsec vs am gear carb
## Mazda RX4 21.0 6 160.0 110 3.90 2.620 16.46 0 1 4 4
## Mazda RX4 Wag 21.0 6 160.0 110 3.90 2.875 17.02 0 1 4 4
## Datsun 710 22.8 4 108.0 93 3.85 2.320 18.61 1 1 4 1
## Hornet 4 Drive 21.4 6 258.0 110 3.08 3.215 19.44 1 0 3 1
## Hornet Sportabout 18.7 8 360.0 175 3.15 3.440 17.02 0 0 3 2
## Valiant 18.1 6 225.0 105 2.76 3.460 20.22 1 0 3 1
## Duster 360 14.3 8 360.0 245 3.21 3.570 15.84 0 0 3 4
## Merc 240D 24.4 4 146.7 62 3.69 3.190 20.00 1 0 4 2
## Merc 230 22.8 4 140.8 95 3.92 3.150 22.90 1 0 4 2
## Merc 280 19.2 6 167.6 123 3.92 3.440 18.30 1 0 4 4
## Merc 280C 17.8 6 167.6 123 3.92 3.440 18.90 1 0 4 4
## Merc 450SE 16.4 8 275.8 180 3.07 4.070 17.40 0 0 3 3
## Merc 450SL 17.3 8 275.8 180 3.07 3.730 17.60 0 0 3 3
## Merc 450SLC 15.2 8 275.8 180 3.07 3.780 18.00 0 0 3 3
## Cadillac Fleetwood 10.4 8 472.0 205 2.93 5.250 17.98 0 0 3 4
## Lincoln Continental 10.4 8 460.0 215 3.00 5.424 17.82 0 0 3 4
## Chrysler Imperial 14.7 8 440.0 230 3.23 5.345 17.42 0 0 3 4
## Fiat 128 32.4 4 78.7 66 4.08 2.200 19.47 1 1 4 1
## Honda Civic 30.4 4 75.7 52 4.93 1.615 18.52 1 1 4 2
## Toyota Corolla 33.9 4 71.1 65 4.22 1.835 19.90 1 1 4 1
## Toyota Corona 21.5 4 120.1 97 3.70 2.465 20.01 1 0 3 1
## Dodge Challenger 15.5 8 318.0 150 2.76 3.520 16.87 0 0 3 2
## AMC Javelin 15.2 8 304.0 150 3.15 3.435 17.30 0 0 3 2
## Camaro Z28 13.3 8 350.0 245 3.73 3.840 15.41 0 0 3 4
## Pontiac Firebird 19.2 8 400.0 175 3.08 3.845 17.05 0 0 3 2
## Fiat X1-9 27.3 4 79.0 66 4.08 1.935 18.90 1 1 4 1
## Porsche 914-2 26.0 4 120.3 91 4.43 2.140 16.70 0 1 5 2
## Lotus Europa 30.4 4 95.1 113 3.77 1.513 16.90 1 1 5 2
## Ford Pantera L 15.8 8 351.0 264 4.22 3.170 14.50 0 1 5 4
## Ferrari Dino 19.7 6 145.0 175 3.62 2.770 15.50 0 1 5 6
## Maserati Bora 15.0 8 301.0 335 3.54 3.570 14.60 0 1 5 8
## Volvo 142E 21.4 4 121.0 109 4.11 2.780 18.60 1 1 4 2plot(mtcars)
nhtemp
1912〜1971年のコネチカット州ニューヘブンでの年間平均気温（華氏）.
nhtemp## Time Series:
## Start = 1912
## End = 1971
## Frequency = 1
## [1] 49.9 52.3 49.4 51.1 49.4 47.9 49.8 50.9 49.3 51.9 50.8 49.6 49.3 50.6
## [15] 48.4 50.7 50.9 50.6 51.5 52.8 51.8 51.1 49.8 50.2 50.4 51.6 51.8 50.9
## [29] 48.8 51.7 51.0 50.6 51.7 51.5 52.1 51.3 51.0 54.0 51.4 52.7 53.1 54.6
## [43] 52.0 52.0 50.9 52.6 50.2 52.6 51.6 51.9 50.5 50.9 51.7 51.4 51.7 50.8
## [57] 51.9 51.8 51.9 53.0plot(nhtemp)
nottem
A time series object containing average air temperatures at Nottingham Castle in degrees Fahrenheit for 20 years.
nottem## Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
## 1920 40.6 40.8 44.4 46.7 54.1 58.5 57.7 56.4 54.3 50.5 42.9 39.8
## 1921 44.2 39.8 45.1 47.0 54.1 58.7 66.3 59.9 57.0 54.2 39.7 42.8
## 1922 37.5 38.7 39.5 42.1 55.7 57.8 56.8 54.3 54.3 47.1 41.8 41.7
## 1923 41.8 40.1 42.9 45.8 49.2 52.7 64.2 59.6 54.4 49.2 36.3 37.6
## 1924 39.3 37.5 38.3 45.5 53.2 57.7 60.8 58.2 56.4 49.8 44.4 43.6
## 1925 40.0 40.5 40.8 45.1 53.8 59.4 63.5 61.0 53.0 50.0 38.1 36.3
## 1926 39.2 43.4 43.4 48.9 50.6 56.8 62.5 62.0 57.5 46.7 41.6 39.8
## 1927 39.4 38.5 45.3 47.1 51.7 55.0 60.4 60.5 54.7 50.3 42.3 35.2
## 1928 40.8 41.1 42.8 47.3 50.9 56.4 62.2 60.5 55.4 50.2 43.0 37.3
## 1929 34.8 31.3 41.0 43.9 53.1 56.9 62.5 60.3 59.8 49.2 42.9 41.9
## 1930 41.6 37.1 41.2 46.9 51.2 60.4 60.1 61.6 57.0 50.9 43.0 38.8
## 1931 37.1 38.4 38.4 46.5 53.5 58.4 60.6 58.2 53.8 46.6 45.5 40.6
## 1932 42.4 38.4 40.3 44.6 50.9 57.0 62.1 63.5 56.3 47.3 43.6 41.8
## 1933 36.2 39.3 44.5 48.7 54.2 60.8 65.5 64.9 60.1 50.2 42.1 35.8
## 1934 39.4 38.2 40.4 46.9 53.4 59.6 66.5 60.4 59.2 51.2 42.8 45.8
## 1935 40.0 42.6 43.5 47.1 50.0 60.5 64.6 64.0 56.8 48.6 44.2 36.4
## 1936 37.3 35.0 44.0 43.9 52.7 58.6 60.0 61.1 58.1 49.6 41.6 41.3
## 1937 40.8 41.0 38.4 47.4 54.1 58.6 61.4 61.8 56.3 50.9 41.4 37.1
## 1938 42.1 41.2 47.3 46.6 52.4 59.0 59.6 60.4 57.0 50.7 47.8 39.2
## 1939 39.4 40.9 42.4 47.8 52.4 58.0 60.7 61.8 58.2 46.7 46.6 37.8plot(nottem)
npk
A classical N, P, K (nitrogen, phosphate, potassium) factorial experiment on the growth of peas conducted on 6 blocks. Each half of a fractional factorial design confounding the NPK interaction was used on 3 of the plots.
npk## block N P K yield
## 1 1 0 1 1 49.5
## 2 1 1 1 0 62.8
## 3 1 0 0 0 46.8
## 4 1 1 0 1 57.0
## 5 2 1 0 0 59.8
## 6 2 1 1 1 58.5
## 7 2 0 0 1 55.5
## 8 2 0 1 0 56.0
## 9 3 0 1 0 62.8
## 10 3 1 1 1 55.8
## 11 3 1 0 0 69.5
## 12 3 0 0 1 55.0
## 13 4 1 0 0 62.0
## 14 4 1 1 1 48.8
## 15 4 0 0 1 45.5
## 16 4 0 1 0 44.2
## 17 5 1 1 0 52.0
## 18 5 0 0 0 51.5
## 19 5 1 0 1 49.8
## 20 5 0 1 1 48.8
## 21 6 1 0 1 57.2
## 22 6 1 1 0 59.0
## 23 6 0 1 1 53.2
## 24 6 0 0 0 56.0aov(yield ~ block + N*P*K, npk)## Call:
## aov(formula = yield ~ block + N * P * K, data = npk)
##
## Terms:
## block N P K N:P N:K
## Sum of Squares 343.2950 189.2817 8.4017 95.2017 21.2817 33.1350
## Deg. of Freedom 5 1 1 1 1 1
## P:K Residuals
## Sum of Squares 0.4817 185.2867
## Deg. of Freedom 1 12
##
## Residual standard error: 3.929447
## 1 out of 13 effects not estimable
## Estimated effects may be unbalancedoccupationalStatus
Cross-classification of a sample of British males according to each subject’s occupational status and his father’s occupational status.
occupationalStatus## destination
## origin 1 2 3 4 5 6 7 8
## 1 50 19 26 8 7 11 6 2
## 2 16 40 34 18 11 20 8 3
## 3 12 35 65 66 35 88 23 21
## 4 11 20 58 110 40 183 64 32
## 5 2 8 12 23 25 46 28 12
## 6 12 28 102 162 90 554 230 177
## 7 0 6 19 40 21 158 143 71
## 8 0 3 14 32 15 126 91 106plot(occupationalStatus)
precip
アメリカ（とプエルトリコの）70年における平均降雨量（インチ）.
precip## Mobile Juneau Phoenix
## 67.0 54.7 7.0
## Little Rock Los Angeles Sacramento
## 48.5 14.0 17.2
## San Francisco Denver Hartford
## 20.7 13.0 43.4
## Wilmington Washington Jacksonville
## 40.2 38.9 54.5
## Miami Atlanta Honolulu
## 59.8 48.3 22.9
## Boise Chicago Peoria
## 11.5 34.4 35.1
## Indianapolis Des Moines Wichita
## 38.7 30.8 30.6
## Louisville New Orleans Portland
## 43.1 56.8 40.8
## Baltimore Boston Detroit
## 41.8 42.5 31.0
## Sault Ste. Marie Duluth Minneapolis/St Paul
## 31.7 30.2 25.9
## Jackson Kansas City St Louis
## 49.2 37.0 35.9
## Great Falls Omaha Reno
## 15.0 30.2 7.2
## Concord Atlantic City Albuquerque
## 36.2 45.5 7.8
## Albany Buffalo New York
## 33.4 36.1 40.2
## Charlotte Raleigh Bismark
## 42.7 42.5 16.2
## Cincinati Cleveland Columbus
## 39.0 35.0 37.0
## Oklahoma City Portland Philadelphia
## 31.4 37.6 39.9
## Pittsburg Providence Columbia
## 36.2 42.8 46.4
## Sioux Falls Memphis Nashville
## 24.7 49.1 46.0
## Dallas El Paso Houston
## 35.9 7.8 48.2
## Salt Lake City Burlington Norfolk
## 15.2 32.5 44.7
## Richmond Seattle Tacoma Spokane
## 42.6 38.8 17.4
## Charleston Milwaukee Cheyenne
## 40.8 29.1 14.6
## San Juan
## 59.2hist(precip)
presidents
1945年〜1974年の四半期ごとのアメリカ大統領の支持率の推移.
presidents## Qtr1 Qtr2 Qtr3 Qtr4
## 1945 NA 87 82 75
## 1946 63 50 43 32
## 1947 35 60 54 55
## 1948 36 39 NA NA
## 1949 69 57 57 51
## 1950 45 37 46 39
## 1951 36 24 32 23
## 1952 25 32 NA 32
## 1953 59 74 75 60
## 1954 71 61 71 57
## 1955 71 68 79 73
## 1956 76 71 67 75
## 1957 79 62 63 57
## 1958 60 49 48 52
## 1959 57 62 61 66
## 1960 71 62 61 57
## 1961 72 83 71 78
## 1962 79 71 62 74
## 1963 76 64 62 57
## 1964 80 73 69 69
## 1965 71 64 69 62
## 1966 63 46 56 44
## 1967 44 52 38 46
## 1968 36 49 35 44
## 1969 59 65 65 56
## 1970 66 53 61 52
## 1971 51 48 54 49
## 1972 49 61 NA NA
## 1973 68 44 40 27
## 1974 28 25 24 24plot(presidents)
pressure
Data on the relation between temperature in degrees Celsius and vapor pressure of mercury in millimeters (of mercury).
pressure## temperature pressure
## 1 0 0.0002
## 2 20 0.0012
## 3 40 0.0060
## 4 60 0.0300
## 5 80 0.0900
## 6 100 0.2700
## 7 120 0.7500
## 8 140 1.8500
## 9 160 4.2000
## 10 180 8.8000
## 11 200 17.3000
## 12 220 32.1000
## 13 240 57.0000
## 14 260 96.0000
## 15 280 157.0000
## 16 300 247.0000
## 17 320 376.0000
## 18 340 558.0000
## 19 360 806.0000plot(pressure)
quakes
1964年以降のフィジーの近くでのマグニチュード4.0を超える地震1000個の発生位置.
head(quakes)## lat long depth mag stations
## 1 -20.42 181.62 562 4.8 41
## 2 -20.62 181.03 650 4.2 15
## 3 -26.00 184.10 42 5.4 43
## 4 -17.97 181.66 626 4.1 19
## 5 -20.42 181.96 649 4.0 11
## 6 -19.68 184.31 195 4.0 12plot(quakes)
randu
400 x 3. VMS1.5 で VAX FORTRAN の関数 RANDU を実行したときの乱数.
head(randu)## x y z
## 1 0.000031 0.000183 0.000824
## 2 0.044495 0.155732 0.533939
## 3 0.822440 0.873416 0.838542
## 4 0.322291 0.648545 0.990648
## 5 0.393595 0.826873 0.418881
## 6 0.309097 0.926590 0.777664plot(randu)
rivers
北アメリカにおける 141 の有名な川の長さ（マイル）. US Geological Survey による.
rivers## [1] 735 320 325 392 524 450 1459 135 465 600 330 336 280 315
## [15] 870 906 202 329 290 1000 600 505 1450 840 1243 890 350 407
## [29] 286 280 525 720 390 250 327 230 265 850 210 630 260 230
## [43] 360 730 600 306 390 420 291 710 340 217 281 352 259 250
## [57] 470 680 570 350 300 560 900 625 332 2348 1171 3710 2315 2533
## [71] 780 280 410 460 260 255 431 350 760 618 338 981 1306 500
## [85] 696 605 250 411 1054 735 233 435 490 310 460 383 375 1270
## [99] 545 445 1885 380 300 380 377 425 276 210 800 420 350 360
## [113] 538 1100 1205 314 237 610 360 540 1038 424 310 300 444 301
## [127] 268 620 215 652 900 525 246 360 529 500 720 270 430 671
## [141] 1770hist(rivers)
rock
あるLPガスの貯水池からの48個の岩石のサンプル.
rock## area peri shape perm
## 1 4990 2791.900 0.0903296 6.3
## 2 7002 3892.600 0.1486220 6.3
## 3 7558 3930.660 0.1833120 6.3
## 4 7352 3869.320 0.1170630 6.3
## 5 7943 3948.540 0.1224170 17.1
## 6 7979 4010.150 0.1670450 17.1
## 7 9333 4345.750 0.1896510 17.1
## 8 8209 4344.750 0.1641270 17.1
## 9 8393 3682.040 0.2036540 119.0
## 10 6425 3098.650 0.1623940 119.0
## 11 9364 4480.050 0.1509440 119.0
## 12 8624 3986.240 0.1481410 119.0
## 13 10651 4036.540 0.2285950 82.4
## 14 8868 3518.040 0.2316230 82.4
## 15 9417 3999.370 0.1725670 82.4
## 16 8874 3629.070 0.1534810 82.4
## 17 10962 4608.660 0.2043140 58.6
## 18 10743 4787.620 0.2627270 58.6
## 19 11878 4864.220 0.2000710 58.6
## 20 9867 4479.410 0.1448100 58.6
## 21 7838 3428.740 0.1138520 142.0
## 22 11876 4353.140 0.2910290 142.0
## 23 12212 4697.650 0.2400770 142.0
## 24 8233 3518.440 0.1618650 142.0
## 25 6360 1977.390 0.2808870 740.0
## 26 4193 1379.350 0.1794550 740.0
## 27 7416 1916.240 0.1918020 740.0
## 28 5246 1585.420 0.1330830 740.0
## 29 6509 1851.210 0.2252140 890.0
## 30 4895 1239.660 0.3412730 890.0
## 31 6775 1728.140 0.3116460 890.0
## 32 7894 1461.060 0.2760160 890.0
## 33 5980 1426.760 0.1976530 950.0
## 34 5318 990.388 0.3266350 950.0
## 35 7392 1350.760 0.1541920 950.0
## 36 7894 1461.060 0.2760160 950.0
## 37 3469 1376.700 0.1769690 100.0
## 38 1468 476.322 0.4387120 100.0
## 39 3524 1189.460 0.1635860 100.0
## 40 5267 1644.960 0.2538320 100.0
## 41 5048 941.543 0.3286410 1300.0
## 42 1016 308.642 0.2300810 1300.0
## 43 5605 1145.690 0.4641250 1300.0
## 44 8793 2280.490 0.4204770 1300.0
## 45 3475 1174.110 0.2007440 580.0
## 46 1651 597.808 0.2626510 580.0
## 47 5514 1455.880 0.1824530 580.0
## 48 9718 1485.580 0.2004470 580.0plot(rock)
sleep
20 x 3. 10人の被験者に対する, 2種類の睡眠剤の効果の差（コントロール群との睡眠時間（h）の差）.
sleep## extra group ID
## 1 0.7 1 1
## 2 -1.6 1 2
## 3 -0.2 1 3
## 4 -1.2 1 4
## 5 -0.1 1 5
## 6 3.4 1 6
## 7 3.7 1 7
## 8 0.8 1 8
## 9 0.0 1 9
## 10 2.0 1 10
## 11 1.9 2 1
## 12 0.8 2 2
## 13 1.1 2 3
## 14 0.1 2 4
## 15 -0.1 2 5
## 16 4.4 2 6
## 17 5.5 2 7
## 18 1.6 2 8
## 19 4.6 2 9
## 20 3.4 2 10stack.loss
アンモニアを硝酸に酸化したときの装置のデータ. stackloss のデータのうち一部（stack.lossという変数のみ）.
stack.loss## [1] 42 37 37 28 18 18 19 20 15 14 14 13 11 12 8 7 8 8 9 15 15hist(stack.loss)
stack.x
アンモニアを硝酸に酸化したときの装置のデータ. stackloss のデータのうち一部（Air.Flow, Water.Temp, Acid.Conc.の3変数）.
stack.x## Air.Flow Water.Temp Acid.Conc.
## [1,] 80 27 89
## [2,] 80 27 88
## [3,] 75 25 90
## [4,] 62 24 87
## [5,] 62 22 87
## [6,] 62 23 87
## [7,] 62 24 93
## [8,] 62 24 93
## [9,] 58 23 87
## [10,] 58 18 80
## [11,] 58 18 89
## [12,] 58 17 88
## [13,] 58 18 82
## [14,] 58 19 93
## [15,] 50 18 89
## [16,] 50 18 86
## [17,] 50 19 72
## [18,] 50 19 79
## [19,] 50 20 80
## [20,] 56 20 82
## [21,] 70 20 91plot(as.data.frame(stack.x))
stackloss
アンモニアを硝酸に酸化したときの装置のデータ.
stackloss## Air.Flow Water.Temp Acid.Conc. stack.loss
## 1 80 27 89 42
## 2 80 27 88 37
## 3 75 25 90 37
## 4 62 24 87 28
## 5 62 22 87 18
## 6 62 23 87 18
## 7 62 24 93 19
## 8 62 24 93 20
## 9 58 23 87 15
## 10 58 18 80 14
## 11 58 18 89 14
## 12 58 17 88 13
## 13 58 18 82 11
## 14 58 19 93 12
## 15 50 18 89 8
## 16 50 18 86 7
## 17 50 19 72 8
## 18 50 19 79 8
## 19 50 20 80 9
## 20 56 20 82 15
## 21 70 20 91 15plot(stackloss)
state.abb
アメリカの州の名前の省略名.
state.abb## [1] "AL" "AK" "AZ" "AR" "CA" "CO" "CT" "DE" "FL" "GA" "HI" "ID" "IL" "IN"
## [15] "IA" "KS" "KY" "LA" "ME" "MD" "MA" "MI" "MN" "MS" "MO" "MT" "NE" "NV"
## [29] "NH" "NJ" "NM" "NY" "NC" "ND" "OH" "OK" "OR" "PA" "RI" "SC" "SD" "TN"
## [43] "TX" "UT" "VT" "VA" "WA" "WV" "WI" "WY"state.area
アメリカの各州の面積（平米）.
state.area## [1] 51609 589757 113909 53104 158693 104247 5009 2057 58560 58876
## [11] 6450 83557 56400 36291 56290 82264 40395 48523 33215 10577
## [21] 8257 58216 84068 47716 69686 147138 77227 110540 9304 7836
## [31] 121666 49576 52586 70665 41222 69919 96981 45333 1214 31055
## [41] 77047 42244 267339 84916 9609 40815 68192 24181 56154 97914hist(state.area)
state.center
アメリカの州の中心の座標（緯度, 経度）.
state.center## $x
## [1] -86.7509 -127.2500 -111.6250 -92.2992 -119.7730 -105.5130 -72.3573
## [8] -74.9841 -81.6850 -83.3736 -126.2500 -113.9300 -89.3776 -86.0808
## [15] -93.3714 -98.1156 -84.7674 -92.2724 -68.9801 -76.6459 -71.5800
## [22] -84.6870 -94.6043 -89.8065 -92.5137 -109.3200 -99.5898 -116.8510
## [29] -71.3924 -74.2336 -105.9420 -75.1449 -78.4686 -100.0990 -82.5963
## [36] -97.1239 -120.0680 -77.4500 -71.1244 -80.5056 -99.7238 -86.4560
## [43] -98.7857 -111.3300 -72.5450 -78.2005 -119.7460 -80.6665 -89.9941
## [50] -107.2560
##
## $y
## [1] 32.5901 49.2500 34.2192 34.7336 36.5341 38.6777 41.5928 38.6777
## [9] 27.8744 32.3329 31.7500 43.5648 40.0495 40.0495 41.9358 38.4204
## [17] 37.3915 30.6181 45.6226 39.2778 42.3645 43.1361 46.3943 32.6758
## [25] 38.3347 46.8230 41.3356 39.1063 43.3934 39.9637 34.4764 43.1361
## [33] 35.4195 47.2517 40.2210 35.5053 43.9078 40.9069 41.5928 33.6190
## [41] 44.3365 35.6767 31.3897 39.1063 44.2508 37.5630 47.4231 38.4204
## [49] 44.5937 43.0504plot(state.center)
state.division
アメリカの州の地区（division）.
state.division## [1] East South Central Pacific Mountain
## [4] West South Central Pacific Mountain
## [7] New England South Atlantic South Atlantic
## [10] South Atlantic Pacific Mountain
## [13] East North Central East North Central West North Central
## [16] West North Central East South Central West South Central
## [19] New England South Atlantic New England
## [22] East North Central West North Central East South Central
## [25] West North Central Mountain West North Central
## [28] Mountain New England Middle Atlantic
## [31] Mountain Middle Atlantic South Atlantic
## [34] West North Central East North Central West South Central
## [37] Pacific Middle Atlantic New England
## [40] South Atlantic West North Central East South Central
## [43] West South Central Mountain New England
## [46] South Atlantic Pacific South Atlantic
## [49] East North Central Mountain
## 9 Levels: New England Middle Atlantic ... Pacifictable(state.division)## state.division
## New England Middle Atlantic South Atlantic
## 6 3 8
## East South Central West South Central East North Central
## 4 4 5
## West North Central Mountain Pacific
## 7 8 5state.name
アメリカの州の名前.
state.name## [1] "Alabama" "Alaska" "Arizona" "Arkansas"
## [5] "California" "Colorado" "Connecticut" "Delaware"
## [9] "Florida" "Georgia" "Hawaii" "Idaho"
## [13] "Illinois" "Indiana" "Iowa" "Kansas"
## [17] "Kentucky" "Louisiana" "Maine" "Maryland"
## [21] "Massachusetts" "Michigan" "Minnesota" "Mississippi"
## [25] "Missouri" "Montana" "Nebraska" "Nevada"
## [29] "New Hampshire" "New Jersey" "New Mexico" "New York"
## [33] "North Carolina" "North Dakota" "Ohio" "Oklahoma"
## [37] "Oregon" "Pennsylvania" "Rhode Island" "South Carolina"
## [41] "South Dakota" "Tennessee" "Texas" "Utah"
## [45] "Vermont" "Virginia" "Washington" "West Virginia"
## [49] "Wisconsin" "Wyoming"state.region
アメリカの州の地域（region）.
state.region## [1] South West West South West
## [6] West Northeast South South South
## [11] West West North Central North Central North Central
## [16] North Central South South Northeast South
## [21] Northeast North Central North Central South North Central
## [26] West North Central West Northeast Northeast
## [31] West Northeast South North Central North Central
## [36] South West Northeast Northeast South
## [41] North Central South South West Northeast
## [46] South West South North Central West
## Levels: Northeast South North Central Westtable(state.region)## state.region
## Northeast South North Central West
## 9 16 12 13state.x77
50 x 8. アメリカの州の統計.
state.x77## Population Income Illiteracy Life Exp Murder HS Grad Frost
## Alabama 3615 3624 2.1 69.05 15.1 41.3 20
## Alaska 365 6315 1.5 69.31 11.3 66.7 152
## Arizona 2212 4530 1.8 70.55 7.8 58.1 15
## Arkansas 2110 3378 1.9 70.66 10.1 39.9 65
## California 21198 5114 1.1 71.71 10.3 62.6 20
## Colorado 2541 4884 0.7 72.06 6.8 63.9 166
## Connecticut 3100 5348 1.1 72.48 3.1 56.0 139
## Delaware 579 4809 0.9 70.06 6.2 54.6 103
## Florida 8277 4815 1.3 70.66 10.7 52.6 11
## Georgia 4931 4091 2.0 68.54 13.9 40.6 60
## Hawaii 868 4963 1.9 73.60 6.2 61.9 0
## Idaho 813 4119 0.6 71.87 5.3 59.5 126
## Illinois 11197 5107 0.9 70.14 10.3 52.6 127
## Indiana 5313 4458 0.7 70.88 7.1 52.9 122
## Iowa 2861 4628 0.5 72.56 2.3 59.0 140
## Kansas 2280 4669 0.6 72.58 4.5 59.9 114
## Kentucky 3387 3712 1.6 70.10 10.6 38.5 95
## Louisiana 3806 3545 2.8 68.76 13.2 42.2 12
## Maine 1058 3694 0.7 70.39 2.7 54.7 161
## Maryland 4122 5299 0.9 70.22 8.5 52.3 101
## Massachusetts 5814 4755 1.1 71.83 3.3 58.5 103
## Michigan 9111 4751 0.9 70.63 11.1 52.8 125
## Minnesota 3921 4675 0.6 72.96 2.3 57.6 160
## Mississippi 2341 3098 2.4 68.09 12.5 41.0 50
## Missouri 4767 4254 0.8 70.69 9.3 48.8 108
## Montana 746 4347 0.6 70.56 5.0 59.2 155
## Nebraska 1544 4508 0.6 72.60 2.9 59.3 139
## Nevada 590 5149 0.5 69.03 11.5 65.2 188
## New Hampshire 812 4281 0.7 71.23 3.3 57.6 174
## New Jersey 7333 5237 1.1 70.93 5.2 52.5 115
## New Mexico 1144 3601 2.2 70.32 9.7 55.2 120
## New York 18076 4903 1.4 70.55 10.9 52.7 82
## North Carolina 5441 3875 1.8 69.21 11.1 38.5 80
## North Dakota 637 5087 0.8 72.78 1.4 50.3 186
## Ohio 10735 4561 0.8 70.82 7.4 53.2 124
## Oklahoma 2715 3983 1.1 71.42 6.4 51.6 82
## Oregon 2284 4660 0.6 72.13 4.2 60.0 44
## Pennsylvania 11860 4449 1.0 70.43 6.1 50.2 126
## Rhode Island 931 4558 1.3 71.90 2.4 46.4 127
## South Carolina 2816 3635 2.3 67.96 11.6 37.8 65
## South Dakota 681 4167 0.5 72.08 1.7 53.3 172
## Tennessee 4173 3821 1.7 70.11 11.0 41.8 70
## Texas 12237 4188 2.2 70.90 12.2 47.4 35
## Utah 1203 4022 0.6 72.90 4.5 67.3 137
## Vermont 472 3907 0.6 71.64 5.5 57.1 168
## Virginia 4981 4701 1.4 70.08 9.5 47.8 85
## Washington 3559 4864 0.6 71.72 4.3 63.5 32
## West Virginia 1799 3617 1.4 69.48 6.7 41.6 100
## Wisconsin 4589 4468 0.7 72.48 3.0 54.5 149
## Wyoming 376 4566 0.6 70.29 6.9 62.9 173
## Area
## Alabama 50708
## Alaska 566432
## Arizona 113417
## Arkansas 51945
## California 156361
## Colorado 103766
## Connecticut 4862
## Delaware 1982
## Florida 54090
## Georgia 58073
## Hawaii 6425
## Idaho 82677
## Illinois 55748
## Indiana 36097
## Iowa 55941
## Kansas 81787
## Kentucky 39650
## Louisiana 44930
## Maine 30920
## Maryland 9891
## Massachusetts 7826
## Michigan 56817
## Minnesota 79289
## Mississippi 47296
## Missouri 68995
## Montana 145587
## Nebraska 76483
## Nevada 109889
## New Hampshire 9027
## New Jersey 7521
## New Mexico 121412
## New York 47831
## North Carolina 48798
## North Dakota 69273
## Ohio 40975
## Oklahoma 68782
## Oregon 96184
## Pennsylvania 44966
## Rhode Island 1049
## South Carolina 30225
## South Dakota 75955
## Tennessee 41328
## Texas 262134
## Utah 82096
## Vermont 9267
## Virginia 39780
## Washington 66570
## West Virginia 24070
## Wisconsin 54464
## Wyoming 97203plot(as.data.frame(state.x77))
sunspot.month
sunspot.year
sunspots
swiss
47 x 6. Standardized fertility measure and socio-economic indicators for each of 47 French-speaking provinces of Switzerland at about 1888.
head(swiss)## Fertility Agriculture Examination Education Catholic
## Courtelary 80.2 17.0 15 12 9.96
## Delemont 83.1 45.1 6 9 84.84
## Franches-Mnt 92.5 39.7 5 5 93.40
## Moutier 85.8 36.5 12 7 33.77
## Neuveville 76.9 43.5 17 15 5.16
## Porrentruy 76.1 35.3 9 7 90.57
## Infant.Mortality
## Courtelary 22.2
## Delemont 22.2
## Franches-Mnt 20.2
## Moutier 20.3
## Neuveville 20.6
## Porrentruy 26.6plot(swiss)
treering
- 紀元前6000年〜1979年までの木の年輪の幅（標準化したもの）の時系列データ.
head(treering)## [1] 1.345 1.077 1.545 1.319 1.413 1.069plot(treering)
trees
31の伐採された Black Cherry の木の胴周り（直径, インチ）, 高さ, 体積のデータ.
trees## Girth Height Volume
## 1 8.3 70 10.3
## 2 8.6 65 10.3
## 3 8.8 63 10.2
## 4 10.5 72 16.4
## 5 10.7 81 18.8
## 6 10.8 83 19.7
## 7 11.0 66 15.6
## 8 11.0 75 18.2
## 9 11.1 80 22.6
## 10 11.2 75 19.9
## 11 11.3 79 24.2
## 12 11.4 76 21.0
## 13 11.4 76 21.4
## 14 11.7 69 21.3
## 15 12.0 75 19.1
## 16 12.9 74 22.2
## 17 12.9 85 33.8
## 18 13.3 86 27.4
## 19 13.7 71 25.7
## 20 13.8 64 24.9
## 21 14.0 78 34.5
## 22 14.2 80 31.7
## 23 14.5 74 36.3
## 24 16.0 72 38.3
## 25 16.3 77 42.6
## 26 17.3 81 55.4
## 27 17.5 82 55.7
## 28 17.9 80 58.3
## 29 18.0 80 51.5
## 30 18.0 80 51.0
## 31 20.6 87 77.0plot(trees)
uspop
1790〜1970年のアメリカの人口（百万人）の推移.
uspop## Time Series:
## Start = 1790
## End = 1970
## Frequency = 0.1
## [1] 3.93 5.31 7.24 9.64 12.90 17.10 23.20 31.40 39.80 50.20
## [11] 62.90 76.00 92.00 105.70 122.80 131.70 151.30 179.30 203.20plot(uspop)
volcano
Maunga Whau (Mt Eden) is one of about 50 volcanos in the Auckland volcanic field. This data set gives topographic information for Maunga Whau on a 10m by 10m grid.
volcano## [,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10] [,11] [,12] [,13]
## [1,] 100 100 101 101 101 101 101 100 100 100 101 101 102
## [2,] 101 101 102 102 102 102 102 101 101 101 102 102 103
## [3,] 102 102 103 103 103 103 103 102 102 102 103 103 104
## [4,] 103 103 104 104 104 104 104 103 103 103 103 104 104
## [5,] 104 104 105 105 105 105 105 104 104 103 104 104 105
## [6,] 105 105 105 106 106 106 106 105 105 104 104 105 105
## [7,] 105 106 106 107 107 107 107 106 106 105 105 106 106
## [8,] 106 107 107 108 108 108 108 107 107 106 106 107 108
## [9,] 107 108 108 109 109 109 109 108 108 107 108 108 110
## [10,] 108 109 109 110 110 110 110 109 109 108 110 110 113
## [11,] 109 110 110 111 111 111 111 110 110 110 112 114 118
## [12,] 110 110 111 113 112 111 113 112 112 114 116 119 121
## [13,] 110 111 113 115 114 113 114 114 115 117 119 121 124
## [14,] 111 113 115 117 116 115 116 117 117 119 121 124 126
## [15,] 114 115 117 117 117 118 119 119 120 121 124 126 128
## [16,] 116 118 118 118 120 121 121 122 122 123 125 128 130
## [17,] 118 120 120 121 122 123 124 124 125 126 127 129 132
## [18,] 120 121 122 123 124 125 126 127 127 128 130 132 134
## [19,] 120 122 125 126 126 127 128 129 130 130 132 134 136
## [20,] 121 124 126 128 129 129 130 131 132 133 135 137 139
## [21,] 122 125 127 130 130 131 133 134 135 136 137 140 143
## [22,] 122 125 128 130 132 133 135 136 137 139 140 143 147
## [23,] 123 126 129 131 133 135 137 138 139 141 143 147 150
## [24,] 124 127 130 132 135 137 138 140 142 144 147 149 154
## [25,] 123 128 131 133 136 138 140 142 144 146 149 151 154
## [26,] 123 127 131 134 136 138 140 142 144 147 149 151 154
## [27,] 120 124 128 131 134 137 139 142 144 146 149 151 153
## [28,] 118 121 125 129 132 134 137 140 142 145 147 149 151
## [29,] 117 120 121 125 129 132 135 138 140 143 145 147 149
## [30,] 115 118 120 122 126 130 133 136 138 141 143 145 148
## [31,] 114 116 118 120 122 127 131 133 136 138 141 143 146
## [32,] 115 114 116 118 120 122 127 129 132 136 139 141 143
## [33,] 113 113 114 116 118 120 122 125 129 133 136 138 141
## [34,] 111 112 113 114 116 118 120 122 126 130 133 136 139
## [35,] 110 112 113 113 114 116 118 120 123 127 131 134 137
## [36,] 109 110 111 112 114 116 118 119 120 124 128 131 136
## [37,] 108 109 111 112 114 116 117 118 120 121 125 128 132
## [38,] 108 109 111 113 114 116 117 118 119 120 122 126 130
## [39,] 107 108 111 112 114 115 116 117 119 120 121 124 128
## [40,] 107 108 110 112 113 113 115 116 118 120 122 125 128
## [41,] 107 108 109 111 113 114 116 117 119 120 122 125 128
## [42,] 108 109 110 112 114 115 116 117 119 120 122 126 129
## [43,] 109 110 111 113 115 116 117 118 120 121 123 126 129
## [44,] 110 111 112 113 116 117 118 119 120 122 125 127 130
## [45,] 111 112 113 114 116 117 118 119 120 123 125 128 130
## [46,] 111 112 113 115 117 118 118 120 121 124 126 128 131
## [47,] 112 113 114 116 117 118 119 120 122 124 127 129 132
## [48,] 113 114 115 116 117 119 119 120 122 125 127 129 132
## [49,] 113 114 115 117 118 119 120 121 123 125 127 130 132
## [50,] 114 115 116 117 118 119 120 121 123 126 128 130 133
## [51,] 115 116 117 118 119 120 121 121 123 126 128 131 134
## [52,] 115 116 117 118 119 120 121 122 123 125 128 131 134
## [53,] 114 115 116 116 118 119 120 121 122 126 129 132 135
## [54,] 113 114 115 116 117 118 119 120 123 126 129 132 135
## [55,] 112 113 114 115 116 117 119 120 122 126 130 133 136
## [56,] 111 112 114 115 116 117 118 120 122 125 131 134 137
## [57,] 111 112 113 115 115 116 117 119 121 126 131 135 138
## [58,] 112 113 113 114 115 116 117 119 122 127 132 135 139
## [59,] 112 113 114 114 116 117 118 120 122 128 132 136 139
## [60,] 112 114 114 115 116 117 119 120 122 128 133 136 140
## [61,] 113 114 115 116 116 117 118 120 123 129 133 137 140
## [62,] 114 115 115 116 117 118 118 120 123 129 133 137 140
## [63,] 114 115 116 117 117 119 118 120 123 128 132 136 139
## [64,] 115 116 116 117 118 119 119 120 124 128 132 136 139
## [65,] 115 116 117 118 118 119 120 123 125 128 131 135 138
## [66,] 116 117 118 118 119 120 122 123 125 128 131 134 137
## [67,] 116 117 118 119 120 121 123 124 126 128 130 133 137
## [68,] 117 118 119 119 120 121 123 124 126 128 129 131 135
## [69,] 117 118 119 120 120 121 123 124 125 126 128 129 132
## [70,] 116 117 118 120 120 121 122 123 124 125 126 128 130
## [71,] 114 115 116 117 119 119 120 121 122 123 125 127 129
## [72,] 112 113 114 115 116 116 117 119 120 122 124 126 127
## [73,] 109 111 112 112 113 113 113 114 116 119 121 123 124
## [74,] 106 107 108 108 109 110 110 112 113 114 117 119 120
## [75,] 104 105 105 106 106 107 108 108 109 109 111 115 116
## [76,] 102 103 103 104 104 105 106 106 107 108 109 111 112
## [77,] 101 102 103 103 104 105 105 106 106 107 108 109 109
## [78,] 100 101 102 102 103 103 104 104 105 106 106 107 106
## [79,] 100 101 101 102 102 103 103 104 104 105 105 105 105
## [80,] 99 100 101 102 102 103 103 103 104 104 104 104 103
## [81,] 99 100 100 101 101 102 102 102 103 103 103 103 102
## [82,] 99 100 100 100 101 101 101 102 102 103 102 102 101
## [83,] 99 99 99 99 100 100 101 101 102 102 101 101 101
## [84,] 98 99 99 99 99 100 100 101 101 102 101 100 100
## [85,] 98 98 98 99 99 99 100 100 101 101 100 100 99
## [86,] 97 98 98 98 99 99 99 100 100 100 100 100 99
## [87,] 97 97 97 98 98 99 99 99 100 100 100 99 99
## [,14] [,15] [,16] [,17] [,18] [,19] [,20] [,21] [,22] [,23] [,24]
## [1,] 102 102 102 103 104 103 102 101 101 102 103
## [2,] 103 103 103 104 105 104 103 102 102 103 105
## [3,] 104 104 104 105 106 105 104 104 105 106 107
## [4,] 104 105 105 106 107 106 106 106 107 108 110
## [5,] 105 105 106 107 108 108 108 109 110 112 114
## [6,] 106 106 107 109 110 110 112 113 115 116 118
## [7,] 107 108 109 111 113 114 116 118 120 121 122
## [8,] 108 110 113 115 117 118 120 122 124 125 127
## [9,] 111 113 116 118 120 123 125 127 129 130 132
## [10,] 116 118 120 122 125 127 129 133 136 138 140
## [11,] 121 123 125 127 129 133 137 141 143 145 146
## [12,] 124 127 129 133 138 143 146 149 149 151 153
## [13,] 126 129 133 140 145 150 154 155 155 157 159
## [14,] 128 132 137 143 151 156 161 161 162 163 165
## [15,] 131 137 143 150 156 160 163 165 168 170 171
## [16,] 134 141 147 152 156 160 165 168 170 174 176
## [17,] 135 142 149 153 157 161 166 170 174 178 180
## [18,] 137 142 151 155 158 162 169 172 176 181 183
## [19,] 139 145 152 157 160 167 172 175 178 181 185
## [20,] 143 150 154 159 164 170 173 176 179 184 186
## [21,] 147 154 158 162 166 171 174 177 181 186 189
## [22,] 152 157 161 164 168 172 175 179 182 186 190
## [23,] 156 161 164 167 170 173 177 181 184 187 188
## [24,] 157 161 165 168 171 175 178 181 184 186 187
## [25,] 157 160 164 168 172 175 178 181 183 184 184
## [26,] 157 160 164 168 171 174 178 180 181 181 182
## [27,] 156 160 163 167 171 174 178 180 180 180 180
## [28,] 155 159 163 166 169 173 177 179 180 180 180
## [29,] 153 157 160 163 166 171 174 177 179 180 180
## [30,] 151 154 157 160 163 168 171 174 177 179 179
## [31,] 148 151 154 157 160 164 168 171 174 178 178
## [32,] 146 148 151 153 156 160 164 167 172 174 176
## [33,] 143 146 149 150 153 156 160 165 170 173 176
## [34,] 142 145 147 148 151 155 158 163 168 173 176
## [35,] 141 143 145 148 150 154 157 161 166 171 176
## [36,] 140 142 145 147 150 153 157 160 165 170 174
## [37,] 138 142 144 147 149 153 156 160 164 170 174
## [38,] 135 139 143 147 149 152 156 160 164 169 173
## [39,] 133 137 141 145 149 152 156 160 164 168 172
## [40,] 132 136 140 145 148 150 155 160 164 167 170
## [41,] 132 137 141 144 146 149 152 157 162 166 168
## [42,] 133 137 141 143 146 148 151 155 160 164 167
## [43,] 133 138 141 143 146 148 150 155 159 163 165
## [44,] 133 138 141 143 146 148 150 154 159 162 163
## [45,] 134 139 141 144 146 148 151 154 158 161 164
## [46,] 135 139 142 144 146 148 151 155 160 164 165
## [47,] 135 139 142 144 146 149 152 157 162 167 169
## [48,] 135 139 142 144 147 149 154 159 164 169 170
## [49,] 135 139 142 145 148 150 156 161 166 170 170
## [50,] 136 139 142 145 148 152 157 161 166 168 170
## [51,] 136 139 142 145 149 152 157 161 163 164 166
## [52,] 137 139 142 145 149 152 156 159 159 160 162
## [53,] 137 140 143 146 149 152 155 156 157 158 159
## [54,] 138 140 143 146 148 151 153 154 156 157 157
## [55,] 138 141 143 146 148 150 152 154 155 155 155
## [56,] 139 142 144 146 148 150 152 153 153 153 153
## [57,] 140 142 144 146 148 150 151 151 151 151 151
## [58,] 141 143 145 147 149 150 150 150 150 150 150
## [59,] 141 144 146 147 149 150 150 150 150 150 150
## [60,] 142 144 146 148 150 150 150 150 150 150 150
## [61,] 142 144 146 149 150 150 150 150 150 150 150
## [62,] 143 145 147 150 150 150 150 150 150 150 150
## [63,] 142 145 148 150 150 150 150 150 150 150 150
## [64,] 142 145 148 150 150 150 150 150 150 150 150
## [65,] 141 145 148 150 150 150 150 150 150 150 150
## [66,] 141 145 148 149 150 150 150 150 150 150 150
## [67,] 140 144 145 147 148 149 150 149 149 147 146
## [68,] 139 142 143 145 146 147 147 147 146 144 142
## [69,] 137 140 142 143 143 144 144 144 143 141 139
## [70,] 134 139 140 141 141 141 141 141 140 138 136
## [71,] 133 136 134 134 136 138 138 137 137 135 133
## [72,] 129 129 128 127 129 132 133 133 133 133 131
## [73,] 125 124 123 123 123 125 127 129 129 128 128
## [74,] 121 119 117 117 117 118 120 123 124 125 125
## [75,] 114 113 112 111 110 111 113 116 119 122 122
## [76,] 110 109 108 108 108 108 109 110 112 116 117
## [77,] 107 106 106 105 105 105 106 107 108 109 110
## [78,] 106 106 105 105 104 103 103 104 105 107 108
## [79,] 106 105 105 104 103 102 101 102 103 104 106
## [80,] 104 104 104 104 102 101 101 102 103 104 105
## [81,] 103 103 104 103 102 101 101 101 102 103 104
## [82,] 102 102 103 103 101 101 100 101 101 102 103
## [83,] 101 101 102 102 101 100 100 101 101 101 103
## [84,] 100 101 101 101 100 100 100 100 101 101 101
## [85,] 99 100 100 100 100 100 100 100 101 101 101
## [86,] 99 99 100 100 100 100 100 100 100 101 101
## [87,] 99 99 99 100 100 100 100 100 100 101 101
## [,25] [,26] [,27] [,28] [,29] [,30] [,31] [,32] [,33] [,34] [,35]
## [1,] 104 104 105 107 107 107 108 108 110 110 110
## [2,] 106 106 107 109 110 110 110 110 111 112 113
## [3,] 108 110 111 113 114 115 114 115 116 118 119
## [4,] 111 114 117 118 117 119 120 121 122 124 125
## [5,] 115 118 121 122 121 123 128 131 129 130 131
## [6,] 119 121 124 126 126 129 134 137 137 136 136
## [7,] 123 125 127 129 130 135 140 142 142 142 141
## [8,] 128 129 131 134 135 141 146 147 146 146 145
## [9,] 134 135 137 139 142 146 152 152 151 151 150
## [10,] 141 142 148 150 151 156 158 159 158 157 158
## [11,] 148 150 154 156 159 161 162 163 164 163 164
## [12,] 154 157 159 160 163 165 166 167 168 168 168
## [13,] 161 162 164 165 167 168 169 170 172 174 172
## [14,] 166 167 168 170 171 173 175 177 179 178 177
## [15,] 172 173 174 175 177 179 180 182 183 183 183
## [16,] 179 180 181 181 182 182 183 184 186 187 187
## [17,] 182 183 184 184 185 186 186 187 189 189 189
## [18,] 184 186 187 188 189 189 189 189 190 190 191
## [19,] 186 188 190 191 192 193 193 192 192 191 192
## [20,] 189 190 191 192 193 194 195 194 193 192 191
## [21,] 190 190 191 192 191 191 190 189 188 189 190
## [22,] 190 190 190 189 187 184 184 183 182 182 183
## [23,] 190 189 187 185 183 179 176 174 174 174 174
## [24,] 187 184 184 181 179 175 171 169 168 168 168
## [25,] 185 183 180 177 174 170 167 165 164 164 164
## [26,] 183 181 178 173 169 166 163 161 161 160 160
## [27,] 180 180 175 171 167 162 160 158 157 157 157
## [28,] 180 179 174 169 166 161 158 156 154 153 153
## [29,] 180 179 172 168 164 160 157 154 151 149 150
## [30,] 179 176 171 167 164 160 156 153 149 148 149
## [31,] 179 177 173 169 165 161 157 154 151 149 150
## [32,] 177 176 173 170 166 162 159 157 154 153 154
## [33,] 176 176 173 172 169 165 163 160 158 157 158
## [34,] 177 177 176 174 171 169 166 164 161 161 162
## [35,] 178 178 178 176 174 172 170 167 167 167 166
## [36,] 178 179 179 178 178 176 174 171 170 170 170
## [37,] 178 180 180 179 179 178 176 172 170 170 170
## [38,] 177 180 180 180 180 179 178 174 170 170 168
## [39,] 176 179 180 180 180 179 178 174 170 168 166
## [40,] 174 177 179 179 178 176 176 173 169 166 164
## [41,] 171 173 175 175 173 172 172 171 168 165 162
## [42,] 168 169 170 170 169 168 167 168 166 163 160
## [43,] 166 167 168 168 166 165 164 161 160 159 158
## [44,] 164 166 166 166 165 163 161 159 157 156 155
## [45,] 166 167 168 166 165 163 161 158 156 154 152
## [46,] 168 169 169 168 166 163 160 158 156 153 151
## [47,] 170 170 170 168 165 163 161 159 157 155 151
## [48,] 170 170 170 170 168 165 163 161 158 155 151
## [49,] 170 170 170 170 169 166 163 161 159 155 151
## [50,] 170 170 170 168 166 164 163 160 159 155 151
## [51,] 168 167 166 164 163 161 160 158 156 152 149
## [52,] 162 161 161 160 159 158 157 155 153 150 148
## [53,] 159 159 158 158 157 155 153 151 150 149 147
## [54,] 157 157 156 155 154 152 150 149 148 147 146
## [55,] 155 155 154 152 152 150 148 147 146 145 145
## [56,] 153 153 153 151 149 147 146 144 144 143 143
## [57,] 151 151 151 150 148 146 144 142 141 141 142
## [58,] 150 150 150 149 147 144 142 141 140 140 140
## [59,] 150 150 150 149 146 143 141 140 140 139 139
## [60,] 150 150 150 148 145 142 140 138 138 138 137
## [61,] 150 150 150 147 143 141 139 137 136 136 135
## [62,] 150 150 148 145 142 139 138 136 135 134 134
## [63,] 150 150 147 144 141 139 136 135 134 133 132
## [64,] 150 149 146 143 140 138 135 134 133 131 131
## [65,] 150 147 145 142 139 137 134 132 131 130 129
## [66,] 148 145 143 141 138 135 133 130 129 128 127
## [67,] 144 141 139 136 133 131 129 128 127 126 125
## [68,] 140 138 135 133 130 128 127 126 125 124 123
## [69,] 137 135 133 130 128 127 126 125 123 122 121
## [70,] 134 133 131 129 127 125 124 123 122 120 119
## [71,] 132 130 129 127 125 124 122 121 120 119 117
## [72,] 129 127 126 125 124 122 121 119 118 117 116
## [73,] 127 125 124 123 122 121 119 118 117 116 114
## [74,] 125 123 121 120 120 119 118 117 116 115 114
## [75,] 122 121 120 119 118 118 117 116 115 114 113
## [76,] 117 118 118 118 117 116 116 115 114 113 112
## [77,] 111 113 114 115 115 115 114 113 112 111 110
## [78,] 110 111 111 112 112 113 113 112 111 110 108
## [79,] 107 110 111 111 111 112 112 112 110 107 107
## [80,] 107 110 111 111 111 111 111 111 108 106 105
## [81,] 106 109 110 111 111 111 110 110 107 105 103
## [82,] 105 109 110 110 111 110 110 109 106 105 100
## [83,] 104 107 109 109 110 110 109 108 105 102 100
## [84,] 103 106 107 109 109 109 109 107 104 101 100
## [85,] 102 105 106 109 108 109 107 105 102 100 100
## [86,] 101 103 104 105 106 105 104 101 100 100 99
## [87,] 100 100 100 100 100 100 100 100 100 100 99
## [,36] [,37] [,38] [,39] [,40] [,41] [,42] [,43] [,44] [,45] [,46]
## [1,] 110 110 110 110 110 108 108 108 107 107 108
## [2,] 114 116 115 114 112 110 110 110 109 108 109
## [3,] 119 121 121 120 118 116 114 112 111 110 110
## [4,] 126 127 127 126 124 122 120 117 116 113 111
## [5,] 131 132 132 131 130 128 126 122 119 115 114
## [6,] 135 136 136 136 135 133 129 126 122 118 116
## [7,] 140 140 140 140 139 137 134 129 125 121 118
## [8,] 144 144 144 143 142 141 139 135 130 126 122
## [9,] 149 148 148 146 145 143 142 139 135 131 127
## [10,] 158 154 151 149 148 146 144 141 137 134 130
## [11,] 164 160 157 154 151 149 146 144 140 137 133
## [12,] 168 166 162 159 157 154 152 149 144 140 136
## [13,] 172 171 169 166 163 161 158 153 148 143 140
## [14,] 176 176 174 171 169 165 161 156 152 148 144
## [15,] 183 180 178 177 172 168 164 160 156 152 148
## [16,] 184 184 181 180 176 172 168 165 161 157 153
## [17,] 189 189 186 182 179 175 171 168 165 162 157
## [18,] 190 190 188 186 183 180 175 171 168 165 161
## [19,] 191 191 190 190 187 184 181 177 172 169 165
## [20,] 191 191 191 190 190 188 184 181 177 173 169
## [21,] 190 191 190 190 190 189 186 184 181 177 173
## [22,] 183 183 184 185 186 187 186 185 184 181 177
## [23,] 174 176 177 179 180 182 183 182 181 181 180
## [24,] 169 170 172 174 177 178 179 180 181 181 180
## [25,] 165 166 168 171 175 176 178 180 181 180 180
## [26,] 161 163 165 168 173 176 178 179 180 181 180
## [27,] 158 159 162 166 170 175 177 178 180 181 181
## [28,] 154 156 159 163 169 173 175 178 180 181 180
## [29,] 150 154 158 164 169 174 178 180 180 180 180
## [30,] 151 155 158 163 170 173 177 179 180 180 180
## [31,] 152 155 159 166 171 175 177 179 180 180 179
## [32,] 155 158 161 169 172 174 176 178 178 178 178
## [33,] 159 161 166 170 170 173 175 176 178 176 173
## [34,] 164 165 167 170 170 171 173 173 173 170 168
## [35,] 168 170 169 168 167 168 168 168 168 167 165
## [36,] 168 167 166 164 163 161 162 163 163 163 161
## [37,] 168 166 164 162 160 157 156 157 158 158 156
## [38,] 167 165 163 161 157 154 153 152 152 152 149
## [39,] 165 163 161 158 154 150 149 148 146 145 143
## [40,] 163 161 159 155 152 148 145 143 141 140 139
## [41,] 160 158 156 153 149 145 142 139 138 137 136
## [42,] 158 155 153 150 147 143 140 137 136 134 133
## [43,] 155 152 149 147 144 141 138 135 134 132 130
## [44,] 153 150 146 143 140 138 136 133 132 130 129
## [45,] 150 146 142 139 137 135 133 131 130 129 128
## [46,] 148 145 142 139 137 135 132 130 129 127 126
## [47,] 148 145 141 139 136 134 132 130 128 127 126
## [48,] 148 145 142 139 137 135 132 131 128 126 125
## [49,] 148 146 143 140 138 135 134 132 130 127 125
## [50,] 148 146 143 141 138 136 134 132 130 128 125
## [51,] 147 144 143 141 139 136 134 132 130 128 125
## [52,] 146 145 143 142 140 137 134 131 129 126 124
## [53,] 146 145 144 142 141 138 135 132 128 125 122
## [54,] 145 144 142 141 140 139 136 132 129 125 121
## [55,] 143 142 141 140 140 140 137 133 129 125 120
## [56,] 142 141 140 140 140 140 138 134 130 123 120
## [57,] 141 140 140 140 140 140 140 136 132 126 120
## [58,] 140 140 140 140 140 140 140 137 133 128 120
## [59,] 139 140 140 140 140 140 140 137 133 129 121
## [60,] 138 140 140 140 140 140 140 137 134 130 122
## [61,] 136 138 140 140 140 140 139 136 134 130 123
## [62,] 134 136 138 137 138 139 137 134 132 125 122
## [63,] 132 134 134 134 134 135 133 131 128 124 120
## [64,] 131 131 131 131 131 130 127 124 122 119 117
## [65,] 128 128 128 128 128 126 123 121 119 116 114
## [66,] 126 125 125 125 124 123 120 118 116 114 111
## [67,] 124 123 123 122 121 120 118 116 114 112 108
## [68,] 122 121 120 119 118 117 115 114 112 110 106
## [69,] 120 119 117 116 115 114 112 111 108 107 105
## [70,] 118 117 116 114 112 111 108 109 106 106 100
## [71,] 116 115 114 112 110 109 108 107 105 105 100
## [72,] 114 113 112 110 109 108 106 106 105 100 100
## [73,] 113 112 110 109 108 107 106 105 100 100 100
## [74,] 113 111 109 109 107 106 105 100 100 100 96
## [75,] 112 111 108 108 106 105 100 100 100 96 96
## [76,] 111 110 107 107 105 100 100 100 97 96 96
## [77,] 108 108 106 105 100 100 100 97 97 96 96
## [78,] 107 106 105 100 100 100 98 97 97 96 96
## [79,] 106 105 102 100 100 99 98 97 97 96 96
## [80,] 105 102 101 100 99 99 98 97 97 96 96
## [81,] 104 100 100 99 99 98 98 97 97 96 96
## [82,] 102 100 99 99 99 98 98 97 97 96 96
## [83,] 100 99 99 99 98 98 98 97 96 96 96
## [84,] 99 99 99 98 98 98 97 96 96 96 96
## [85,] 99 99 98 98 98 97 96 96 96 96 95
## [86,] 99 98 98 97 97 97 96 96 96 95 95
## [87,] 99 98 97 97 97 96 96 96 95 95 95
## [,47] [,48] [,49] [,50] [,51] [,52] [,53] [,54] [,55] [,56] [,57]
## [1,] 108 108 108 108 107 107 107 107 106 106 105
## [2,] 109 109 109 108 108 108 108 107 107 106 106
## [3,] 110 110 109 109 109 109 108 108 107 107 106
## [4,] 110 110 110 109 109 109 109 108 108 107 107
## [5,] 112 110 110 110 110 110 109 109 108 107 107
## [6,] 115 113 111 110 110 110 110 109 108 108 108
## [7,] 116 114 112 110 110 110 111 110 109 109 108
## [8,] 118 116 114 112 112 113 112 110 110 109 109
## [9,] 122 119 117 115 115 115 114 112 110 110 109
## [10,] 125 122 120 118 117 117 115 113 111 110 110
## [11,] 129 126 124 121 119 118 116 114 112 111 110
## [12,] 133 131 128 125 122 119 117 115 113 111 110
## [13,] 137 134 131 128 125 120 118 116 114 112 110
## [14,] 140 138 135 131 127 123 119 117 115 113 111
## [15,] 144 141 138 134 130 126 121 117 114 112 110
## [16,] 149 145 142 138 133 129 125 120 115 111 110
## [17,] 152 149 145 141 137 131 125 120 116 111 110
## [18,] 157 152 149 145 141 134 127 121 116 112 110
## [19,] 161 156 152 147 143 139 131 123 119 115 111
## [20,] 165 160 155 149 145 142 136 129 123 118 114
## [21,] 169 164 158 152 148 144 140 134 125 118 115
## [22,] 173 169 163 157 149 145 141 136 130 119 116
## [23,] 176 171 166 160 152 147 142 138 133 126 121
## [24,] 179 174 167 161 155 148 144 139 134 128 121
## [25,] 179 177 170 163 157 150 144 139 134 128 121
## [26,] 180 175 173 166 159 152 145 139 134 127 121
## [27,] 180 178 175 169 160 154 148 140 134 128 121
## [28,] 180 179 175 170 160 154 149 142 135 128 122
## [29,] 178 177 175 170 161 153 148 142 135 129 123
## [30,] 178 175 173 171 162 154 147 141 136 130 124
## [31,] 176 174 171 168 159 151 146 141 135 129 124
## [32,] 175 172 169 162 156 149 144 140 134 128 123
## [33,] 171 168 164 158 153 146 140 137 132 127 121
## [34,] 165 163 160 155 149 143 138 134 130 125 119
## [35,] 163 160 156 152 146 140 136 131 128 122 118
## [36,] 160 157 153 148 142 136 130 127 124 120 117
## [37,] 153 151 149 144 139 130 127 124 121 118 115
## [38,] 148 147 144 140 134 128 125 122 119 117 114
## [39,] 143 143 140 136 130 126 123 120 118 115 112
## [40,] 139 138 136 132 128 124 121 118 116 114 111
## [41,] 135 133 131 129 126 122 119 117 114 112 110
## [42,] 132 130 129 127 125 121 118 115 112 110 110
## [43,] 129 128 126 124 122 120 117 113 111 110 110
## [44,] 128 125 124 122 120 119 117 114 111 110 110
## [45,] 127 125 123 121 120 118 116 113 111 110 110
## [46,] 125 124 123 120 120 117 116 114 112 110 110
## [47,] 124 123 122 120 119 117 116 114 112 111 109
## [48,] 124 122 121 120 119 117 115 113 111 110 109
## [49,] 123 121 120 120 119 116 114 112 110 110 108
## [50,] 123 121 120 120 118 116 113 111 110 110 109
## [51,] 122 120 120 119 117 115 113 110 110 109 107
## [52,] 122 120 119 117 115 113 111 110 109 109 107
## [53,] 120 118 117 115 113 112 110 109 108 108 106
## [54,] 118 116 115 113 111 110 109 108 108 107 106
## [55,] 117 115 111 110 110 109 108 107 107 106 105
## [56,] 118 111 110 110 110 108 107 106 108 105 105
## [57,] 115 110 110 110 109 107 106 105 107 105 104
## [58,] 117 110 110 110 108 106 105 105 106 105 104
## [59,] 118 110 110 109 107 106 105 105 105 104 104
## [60,] 118 110 110 108 106 105 103 104 104 104 104
## [61,] 119 113 109 108 106 104 103 104 104 104 103
## [62,] 117 114 109 107 105 103 102 104 104 103 103
## [63,] 116 113 110 107 104 102 102 103 103 103 102
## [64,] 115 112 109 106 104 101 102 103 103 102 102
## [65,] 112 110 108 105 103 101 103 103 103 102 102
## [66,] 109 107 106 104 102 100 101 101 102 102 101
## [67,] 107 105 103 102 100 100 100 100 101 101 100
## [68,] 105 102 101 100 100 100 100 100 100 100 100
## [69,] 100 100 100 100 100 100 100 99 99 99 99
## [70,] 100 100 100 100 99 99 99 99 99 99 99
## [71,] 100 100 100 99 99 99 98 98 98 98 98
## [72,] 100 98 98 98 98 98 98 97 97 97 97
## [73,] 97 97 97 97 97 97 97 96 96 96 96
## [74,] 96 96 96 96 96 96 96 96 96 96 96
## [75,] 96 96 96 96 96 96 96 96 96 96 96
## [76,] 96 96 96 96 96 96 96 96 96 96 96
## [77,] 96 96 96 96 96 96 96 96 96 96 96
## [78,] 96 96 96 96 96 96 96 96 96 96 96
## [79,] 96 96 96 96 96 96 96 96 96 96 96
## [80,] 96 96 96 96 96 96 96 96 96 96 96
## [81,] 96 96 96 96 96 96 96 96 95 95 95
## [82,] 96 96 96 96 95 95 95 95 95 95 95
## [83,] 96 96 95 95 95 95 95 95 95 94 94
## [84,] 95 95 95 95 95 95 95 94 94 94 94
## [85,] 95 95 95 95 95 94 94 94 94 94 94
## [86,] 95 95 95 94 94 94 94 94 94 94 94
## [87,] 95 94 94 94 94 94 94 94 94 94 94
## [,58] [,59] [,60] [,61]
## [1,] 105 104 104 103
## [2,] 105 105 104 104
## [3,] 106 105 105 104
## [4,] 106 106 105 105
## [5,] 107 106 106 105
## [6,] 107 107 106 106
## [7,] 108 107 107 106
## [8,] 108 108 107 106
## [9,] 109 108 107 107
## [10,] 109 108 107 107
## [11,] 109 108 107 106
## [12,] 109 108 107 106
## [13,] 109 108 107 105
## [14,] 110 108 106 105
## [15,] 110 108 106 104
## [16,] 110 108 106 104
## [17,] 110 108 106 104
## [18,] 110 108 106 104
## [19,] 110 108 106 105
## [20,] 110 108 108 107
## [21,] 111 110 108 107
## [22,] 112 110 108 106
## [23,] 115 110 106 105
## [24,] 115 110 106 105
## [25,] 115 110 108 107
## [26,] 115 110 109 108
## [27,] 115 110 110 109
## [28,] 116 111 110 110
## [29,] 116 113 112 110
## [30,] 117 115 112 110
## [31,] 119 116 113 110
## [32,] 118 115 112 110
## [33,] 117 113 111 110
## [34,] 116 112 110 109
## [35,] 114 110 110 109
## [36,] 113 110 110 109
## [37,] 112 110 110 109
## [38,] 110 110 109 109
## [39,] 110 110 109 109
## [40,] 110 110 109 108
## [41,] 110 109 108 107
## [42,] 110 108 107 107
## [43,] 110 108 107 107
## [44,] 109 108 107 107
## [45,] 109 108 107 106
## [46,] 108 107 106 106
## [47,] 107 106 106 105
## [48,] 106 105 105 104
## [49,] 106 105 104 104
## [50,] 106 105 104 104
## [51,] 106 105 104 104
## [52,] 106 105 104 104
## [53,] 105 105 104 104
## [54,] 105 104 104 104
## [55,] 105 104 104 103
## [56,] 104 104 103 103
## [57,] 104 104 103 103
## [58,] 104 103 103 103
## [59,] 103 103 103 102
## [60,] 103 103 102 102
## [61,] 103 102 102 101
## [62,] 102 102 101 101
## [63,] 102 102 101 100
## [64,] 102 101 100 100
## [65,] 101 100 100 100
## [66,] 100 100 100 100
## [67,] 100 100 100 100
## [68,] 99 99 99 99
## [69,] 99 99 99 98
## [70,] 98 98 98 97
## [71,] 97 97 97 97
## [72,] 97 97 97 96
## [73,] 96 96 96 96
## [74,] 96 96 96 96
## [75,] 96 96 96 96
## [76,] 96 96 96 96
## [77,] 96 96 96 96
## [78,] 96 96 96 96
## [79,] 96 96 96 95
## [80,] 96 96 95 95
## [81,] 95 95 95 95
## [82,] 95 95 95 94
## [83,] 94 94 94 94
## [84,] 94 94 94 94
## [85,] 94 94 94 94
## [86,] 94 94 94 94
## [87,] 94 94 94 94filled.contour(volcano, color.palette = terrain.colors, asp = 1)
warpbreaks
This data set gives the number of warp breaks per loom, where a loom corresponds to a fixed length of yarn.
warpbreaks## breaks wool tension
## 1 26 A L
## 2 30 A L
## 3 54 A L
## 4 25 A L
## 5 70 A L
## 6 52 A L
## 7 51 A L
## 8 26 A L
## 9 67 A L
## 10 18 A M
## 11 21 A M
## 12 29 A M
## 13 17 A M
## 14 12 A M
## 15 18 A M
## 16 35 A M
## 17 30 A M
## 18 36 A M
## 19 36 A H
## 20 21 A H
## 21 24 A H
## 22 18 A H
## 23 10 A H
## 24 43 A H
## 25 28 A H
## 26 15 A H
## 27 26 A H
## 28 27 B L
## 29 14 B L
## 30 29 B L
## 31 19 B L
## 32 29 B L
## 33 31 B L
## 34 41 B L
## 35 20 B L
## 36 44 B L
## 37 42 B M
## 38 26 B M
## 39 19 B M
## 40 16 B M
## 41 39 B M
## 42 28 B M
## 43 21 B M
## 44 39 B M
## 45 29 B M
## 46 20 B H
## 47 21 B H
## 48 24 B H
## 49 17 B H
## 50 13 B H
## 51 15 B H
## 52 15 B H
## 53 16 B H
## 54 28 B Hwomen
15 x 2. 30歳から39歳のアメリカの女性の身長（インチ）と体重（ポンド）の平均.
women## height weight
## 1 58 115
## 2 59 117
## 3 60 120
## 4 61 123
## 5 62 126
## 6 63 129
## 7 64 132
## 8 65 135
## 9 66 139
## 10 67 142
## 11 68 146
## 12 69 150
## 13 70 154
## 14 71 159
## 15 72 164plot(women)