R Markdown
setwd("C:/Users/ARORA/Desktop/Gittie/CUNY/R_Course/Week2/vincentarelbundock-Rdatasets-028956a")
getwd()
## [1] "C:/Users/ARORA/Desktop/Gittie/CUNY/R_Course/Week2/vincentarelbundock-Rdatasets-028956a"
#list.dirs()
#reFi <- read.csv("vincentarelbundock-Rdatasets-028956a/datasets.csv", header = T)
reFi <- read.csv("datasets.csv", header = T)
# fix open the dataframe loaded from csv in a seperate window in visual tabular format.
#fix(reFi)
############ Question 1 ###############
summary(reFi)
## Package Item
## Ecdat :130 lung : 3
## DAAG :121 aids : 2
## Stat2Data:119 channing: 2
## MASS : 87 Cigar : 2
## datasets : 84 cities : 2
## carData : 59 Clothing: 2
## (Other) :562 (Other) :1149
## Title
## Labour Training Evaluation Data : 11
## Seven data sets showing a bifactor solution. : 9
## Individual Preferences Over Immigration Policy : 6
## John Snow's Map and Data on the 1854 London Cholera Outbreak : 5
## Rain, wavesurge, portpirie and nidd datasets. : 4
## Australian and Related Historical Annual Climate Data, by region: 3
## (Other) :1124
## Rows Cols has_logical has_binary
## Min. : 0.0 Min. : 1.00 Mode :logical Mode :logical
## 1st Qu.: 30.0 1st Qu.: 3.00 FALSE:1152 FALSE:647
## Median : 91.0 Median : 5.00 TRUE :10 TRUE :515
## Mean : 1630.3 Mean : 16.31 NA's :0 NA's :0
## 3rd Qu.: 468.8 3rd Qu.: 9.00
## Max. :372864.0 Max. :6831.00
##
## has_numeric has_character
## Mode :logical Mode :logical
## FALSE:297 FALSE:1109
## TRUE :865 TRUE :53
## NA's :0 NA's :0
##
##
##
## CSV
## https://raw.github.com/vincentarelbundock/Rdatasets/master/csv/boot/acme.csv : 1
## https://raw.github.com/vincentarelbundock/Rdatasets/master/csv/boot/aids.csv : 1
## https://raw.github.com/vincentarelbundock/Rdatasets/master/csv/boot/aircondit.csv : 1
## https://raw.github.com/vincentarelbundock/Rdatasets/master/csv/boot/aircondit7.csv: 1
## https://raw.github.com/vincentarelbundock/Rdatasets/master/csv/boot/amis.csv : 1
## https://raw.github.com/vincentarelbundock/Rdatasets/master/csv/boot/aml.csv : 1
## (Other) :1156
## Doc
## https://raw.github.com/vincentarelbundock/Rdatasets/master/doc/boot/acme.html : 1
## https://raw.github.com/vincentarelbundock/Rdatasets/master/doc/boot/aids.html : 1
## https://raw.github.com/vincentarelbundock/Rdatasets/master/doc/boot/aircondit.html : 1
## https://raw.github.com/vincentarelbundock/Rdatasets/master/doc/boot/aircondit7.html: 1
## https://raw.github.com/vincentarelbundock/Rdatasets/master/doc/boot/amis.html : 1
## https://raw.github.com/vincentarelbundock/Rdatasets/master/doc/boot/aml.html : 1
## (Other) :1156
#subsetting
subset_reFi <- reFi[,4:5]
#fix(subset_reFi)
calMean1 <- mean(subset_reFi[,1])
calMean1
## [1] 1630.251
#1630.251
calMedian1 <- median(subset_reFi[,2])
calMedian1
## [1] 5
#[1] 5
#### Question 2 ###################
subset1 <- reFi[,1:4]
#fix(subset1)
subset2 <- reFi[c(200:470),c(1:4)]
#fix(subset2)
#### Question 3 ########
names(subset2)[1] <- "Package/Company Name"
names(subset2)[2] <- "Item"
names(subset2)[3] <- "Item Description"
fix(subset2)
##### Question 4 ############
summary(subset2)
## Package/Company Name Item
## Ecdat :126 Orange : 2
## datasets: 84 ability.cov : 1
## DAAG : 61 Accident : 1
## boot : 0 Airline : 1
## carData : 0 airmiles : 1
## cluster : 0 AirPassengers: 1
## (Other) : 0 (Other) :264
## Item Description Rows
## Labour Training Evaluation Data : 8 Min. : 4.0
## Global Terrorism Database yearly summaries: 3 1st Qu.: 45.5
## Edgar Anderson's Iris Data : 2 Median : 153.0
## Road Casualties in Great Britain 1969-84 : 2 Mean : 1335.2
## The Boston HMDA Data Set : 2 3rd Qu.: 755.5
## Unemployment Duration : 2 Max. :27765.0
## (Other) :252
calMean <- mean(subset2[,4])
calMean
## [1] 1335.232
#1120.317
calMedian <- median(subset2[,4])
calMedian
## [1] 153
#62
############# Question 5 #############
#fix(subset2)
gsub("e","EEE", subset2$Item)
## [1] "lEEEafshapEEE" "lEEEafshapEEE17"
## [3] "lEEEaftEEEmp" "lEEEaftEEEmp.all"
## [5] "littEEErs" "Lottario"
## [7] "lung" "Manitoba.lakEEEs"
## [9] "mEEEaslEEEs" "mEEEdExpEEEnsEEEs"
## [11] "mifEEEm" "mignonEEEttEEE"
## [13] "milk" "modEEElcars"
## [15] "monica" "moths"
## [17] "nassCDS" "nasshEEEad"
## [19] "nihills" "nsw74dEEEmo"
## [21] "nsw74psid1" "nsw74psid3"
## [23] "nsw74psidA" "nswdEEEmo"
## [25] "nswpsid1" "oddbooks"
## [27] "orings" "ozonEEE"
## [29] "pair65" "possum"
## [31] "possumsitEEEs" "poxEEEtc"
## [33] "primatEEEs" "progrEEEssion"
## [35] "psid1" "psid2"
## [37] "psid3" "racEEEs2000"
## [39] "rainforEEEst" "rarEEEplants"
## [41] "ricEEE" "rockArt"
## [43] "rollEEEr" "sciEEEncEEE"
## [45] "sEEEEEEdratEEEs" "socsupport"
## [47] "softbacks" "sorption"
## [49] "SP500closEEE" "SP500W90"
## [51] "spam7" "stVincEEEnt"
## [53] "sugar" "tinting"
## [55] "tomato" "toycars"
## [57] "vincEEE111b" "vlt"
## [59] "wagEEEs1833" "whoops"
## [61] "worldREEEcords" "ability.cov"
## [63] "airmilEEEs" "AirPassEEEngEEErs"
## [65] "airquality" "anscombEEE"
## [67] "attEEEnu" "attitudEEE"
## [69] "austrEEEs" "BJsalEEEs"
## [71] "BOD" "cars"
## [73] "ChickWEEEight" "chickwts"
## [75] "co2" "CO2"
## [77] "crimtab" "discovEEEriEEEs"
## [79] "DNasEEE" "EEEsoph"
## [81] "EEEuro" "EuStockMarkEEEts"
## [83] "faithful" "FormaldEEEhydEEE"
## [85] "frEEEEEEny" "HairEyEEEColor"
## [87] "Harman23.cor" "Harman74.cor"
## [89] "IndomEEEth" "infEEErt"
## [91] "InsEEEctSprays" "iris"
## [93] "iris3" "islands"
## [95] "JohnsonJohnson" "LakEEEHuron"
## [97] "lh" "LifEEECyclEEESavings"
## [99] "Loblolly" "longlEEEy"
## [101] "lynx" "morlEEEy"
## [103] "mtcars" "nhtEEEmp"
## [105] "NilEEE" "nottEEEm"
## [107] "npk" "occupationalStatus"
## [109] "OrangEEE" "OrchardSprays"
## [111] "PlantGrowth" "prEEEcip"
## [113] "prEEEsidEEEnts" "prEEEssurEEE"
## [115] "Puromycin" "quakEEEs"
## [117] "randu" "rivEEErs"
## [119] "rock" "SEEEatbEEElts"
## [121] "slEEEEEEp" "stackloss"
## [123] "sunspot.month" "sunspot.yEEEar"
## [125] "sunspots" "swiss"
## [127] "ThEEEoph" "Titanic"
## [129] "ToothGrowth" "trEEEEEEring"
## [131] "trEEEEEEs" "UCBAdmissions"
## [133] "UKDrivEEErDEEEaths" "UKgas"
## [135] "USAccDEEEaths" "USArrEEEsts"
## [137] "USJudgEEERatings" "USPEEErsonalExpEEEnditurEEE"
## [139] "uspop" "VADEEEaths"
## [141] "volcano" "warpbrEEEaks"
## [143] "womEEEn" "WorldPhonEEEs"
## [145] "WWWusagEEE" "AccidEEEnt"
## [147] "AirlinEEE" "Airq"
## [149] "bankingCrisEEEs" "BEEEnEEEfits"
## [151] "Bids" "brEEEachEEEs"
## [153] "BudgEEEtFood" "BudgEEEtItaly"
## [155] "BudgEEEtUK" "BwagEEEs"
## [157] "Capm" "Car"
## [159] "Caschool" "Catsup"
## [161] "Cigar" "CigarEEEttEEE"
## [163] "Clothing" "ComputEEErs"
## [165] "Consumption" "CPSch3"
## [167] "CrackEEEr" "CRANpackagEEEs"
## [169] "CrimEEE" "CRSPday"
## [171] "CRSPmon" "Diamond"
## [173] "DM" "Doctor"
## [175] "DoctorAUS" "DoctorContacts"
## [177] "Earnings" "ElEEEctricity"
## [179] "Fair" "Fatality"
## [181] "Fishing" "Forward"
## [183] "FriEEEndFoEEE" "Garch"
## [185] "GasolinEEE" "GrilichEEEs"
## [187] "GrunfEEEld" "HC"
## [189] "Hdma" "HEEEating"
## [191] "HEEEdonic" "HHSCybEEErSEEEcurityBrEEEachEEEs"
## [193] "HI" "Hmda"
## [195] "Housing" "Hstarts"
## [197] "IcEEEcrEEEam" "incidEEEnts.byCountryYr"
## [199] "incomEEEInEEEquality" "IncomEEEUK"
## [201] "IratEEEs" "Journals"
## [203] "Kakadu" "KEEEtchup"
## [205] "KlEEEin" "LaborSupply"
## [207] "Labour" "LonglEEEy"
## [209] "LT" "Macrodat"
## [211] "MalEEEs" "ManufCost"
## [213] "MathlEEEvEEEl" "MCAS"
## [215] "MEEEdExp" "MEEEtal"
## [217] "Mishkin" "ModEEE"
## [219] "ModEEEChoicEEE" "Mofa"
## [221] "MonEEEy" "MonEEEyUS"
## [223] "Mpyr" "Mroz"
## [225] "MunExp" "MW"
## [227] "NaturalPark" "NEEErlovEEE"
## [229] "nkill.byCountryYr" "nonEnglishNamEEEs"
## [231] "OFP" "Oil"
## [233] "OrangEEE" "Participation"
## [235] "PatEEEntsHGH" "PatEEEntsRD"
## [237] "PE" "politicalKnowlEEEdgEEE"
## [239] "Pound" "PPP"
## [241] "Pricing" "Produc"
## [243] "PSID" "REEEtSchool"
## [245] "Schooling" "Solow"
## [247] "SomEEErvillEEE" "SP500"
## [249] "Star" "StrikEEE"
## [251] "StrikEEEDur" "StrikEEENb"
## [253] "SumHEEEs" "TbratEEE"
## [255] "tEEErrorism" "Tobacco"
## [257] "Train" "TranspEq"
## [259] "TrEEEatmEEEnt" "Tuna"
## [261] "UnEEEmpDur" "UnEEEmploymEEEnt"
## [263] "UnivEEErsity" "USclassifiEEEdDocumEEEnts"
## [265] "USFinancEEEIndustry" "USGDPprEEEsidEEEnts"
## [267] "USstatEEEAbbrEEEviations" "UStaxWords"
## [269] "ViEEEtNamH" "ViEEEtNamI"
## [271] "WagEEEs"
gsub("a","AAA", subset2$Item)
## [1] "leAAAfshAAApe" "leAAAfshAAApe17"
## [3] "leAAAftemp" "leAAAftemp.AAAll"
## [5] "litters" "LottAAArio"
## [7] "lung" "MAAAnitobAAA.lAAAkes"
## [9] "meAAAsles" "medExpenses"
## [11] "mifem" "mignonette"
## [13] "milk" "modelcAAArs"
## [15] "monicAAA" "moths"
## [17] "nAAAssCDS" "nAAAssheAAAd"
## [19] "nihills" "nsw74demo"
## [21] "nsw74psid1" "nsw74psid3"
## [23] "nsw74psidA" "nswdemo"
## [25] "nswpsid1" "oddbooks"
## [27] "orings" "ozone"
## [29] "pAAAir65" "possum"
## [31] "possumsites" "poxetc"
## [33] "primAAAtes" "progression"
## [35] "psid1" "psid2"
## [37] "psid3" "rAAAces2000"
## [39] "rAAAinforest" "rAAAreplAAAnts"
## [41] "rice" "rockArt"
## [43] "roller" "science"
## [45] "seedrAAAtes" "socsupport"
## [47] "softbAAAcks" "sorption"
## [49] "SP500close" "SP500W90"
## [51] "spAAAm7" "stVincent"
## [53] "sugAAAr" "tinting"
## [55] "tomAAAto" "toycAAArs"
## [57] "vince111b" "vlt"
## [59] "wAAAges1833" "whoops"
## [61] "worldRecords" "AAAbility.cov"
## [63] "AAAirmiles" "AirPAAAssengers"
## [65] "AAAirquAAAlity" "AAAnscombe"
## [67] "AAAttenu" "AAAttitude"
## [69] "AAAustres" "BJsAAAles"
## [71] "BOD" "cAAArs"
## [73] "ChickWeight" "chickwts"
## [75] "co2" "CO2"
## [77] "crimtAAAb" "discoveries"
## [79] "DNAAAse" "esoph"
## [81] "euro" "EuStockMAAArkets"
## [83] "fAAAithful" "FormAAAldehyde"
## [85] "freeny" "HAAAirEyeColor"
## [87] "HAAArmAAAn23.cor" "HAAArmAAAn74.cor"
## [89] "Indometh" "infert"
## [91] "InsectSprAAAys" "iris"
## [93] "iris3" "islAAAnds"
## [95] "JohnsonJohnson" "LAAAkeHuron"
## [97] "lh" "LifeCycleSAAAvings"
## [99] "Loblolly" "longley"
## [101] "lynx" "morley"
## [103] "mtcAAArs" "nhtemp"
## [105] "Nile" "nottem"
## [107] "npk" "occupAAAtionAAAlStAAAtus"
## [109] "OrAAAnge" "OrchAAArdSprAAAys"
## [111] "PlAAAntGrowth" "precip"
## [113] "presidents" "pressure"
## [115] "Puromycin" "quAAAkes"
## [117] "rAAAndu" "rivers"
## [119] "rock" "SeAAAtbelts"
## [121] "sleep" "stAAAckloss"
## [123] "sunspot.month" "sunspot.yeAAAr"
## [125] "sunspots" "swiss"
## [127] "Theoph" "TitAAAnic"
## [129] "ToothGrowth" "treering"
## [131] "trees" "UCBAdmissions"
## [133] "UKDriverDeAAAths" "UKgAAAs"
## [135] "USAccDeAAAths" "USArrests"
## [137] "USJudgeRAAAtings" "USPersonAAAlExpenditure"
## [139] "uspop" "VADeAAAths"
## [141] "volcAAAno" "wAAArpbreAAAks"
## [143] "women" "WorldPhones"
## [145] "WWWusAAAge" "Accident"
## [147] "Airline" "Airq"
## [149] "bAAAnkingCrises" "Benefits"
## [151] "Bids" "breAAAches"
## [153] "BudgetFood" "BudgetItAAAly"
## [155] "BudgetUK" "BwAAAges"
## [157] "CAAApm" "CAAAr"
## [159] "CAAAschool" "CAAAtsup"
## [161] "CigAAAr" "CigAAArette"
## [163] "Clothing" "Computers"
## [165] "Consumption" "CPSch3"
## [167] "CrAAAcker" "CRANpAAAckAAAges"
## [169] "Crime" "CRSPdAAAy"
## [171] "CRSPmon" "DiAAAmond"
## [173] "DM" "Doctor"
## [175] "DoctorAUS" "DoctorContAAActs"
## [177] "EAAArnings" "Electricity"
## [179] "FAAAir" "FAAAtAAAlity"
## [181] "Fishing" "ForwAAArd"
## [183] "FriendFoe" "GAAArch"
## [185] "GAAAsoline" "Griliches"
## [187] "Grunfeld" "HC"
## [189] "HdmAAA" "HeAAAting"
## [191] "Hedonic" "HHSCyberSecurityBreAAAches"
## [193] "HI" "HmdAAA"
## [195] "Housing" "HstAAArts"
## [197] "IcecreAAAm" "incidents.byCountryYr"
## [199] "incomeInequAAAlity" "IncomeUK"
## [201] "IrAAAtes" "JournAAAls"
## [203] "KAAAkAAAdu" "Ketchup"
## [205] "Klein" "LAAAborSupply"
## [207] "LAAAbour" "Longley"
## [209] "LT" "MAAAcrodAAAt"
## [211] "MAAAles" "MAAAnufCost"
## [213] "MAAAthlevel" "MCAS"
## [215] "MedExp" "MetAAAl"
## [217] "Mishkin" "Mode"
## [219] "ModeChoice" "MofAAA"
## [221] "Money" "MoneyUS"
## [223] "Mpyr" "Mroz"
## [225] "MunExp" "MW"
## [227] "NAAAturAAAlPAAArk" "Nerlove"
## [229] "nkill.byCountryYr" "nonEnglishNAAAmes"
## [231] "OFP" "Oil"
## [233] "OrAAAnge" "PAAArticipAAAtion"
## [235] "PAAAtentsHGH" "PAAAtentsRD"
## [237] "PE" "politicAAAlKnowledge"
## [239] "Pound" "PPP"
## [241] "Pricing" "Produc"
## [243] "PSID" "RetSchool"
## [245] "Schooling" "Solow"
## [247] "Somerville" "SP500"
## [249] "StAAAr" "Strike"
## [251] "StrikeDur" "StrikeNb"
## [253] "SumHes" "TbrAAAte"
## [255] "terrorism" "TobAAAcco"
## [257] "TrAAAin" "TrAAAnspEq"
## [259] "TreAAAtment" "TunAAA"
## [261] "UnempDur" "Unemployment"
## [263] "University" "USclAAAssifiedDocuments"
## [265] "USFinAAAnceIndustry" "USGDPpresidents"
## [267] "USstAAAteAbbreviAAAtions" "UStAAAxWords"
## [269] "VietNAAAmH" "VietNAAAmI"
## [271] "WAAAges"
gsub("p","PPP",subset2$Item)
## [1] "leafshaPPPe" "leafshaPPPe17"
## [3] "leaftemPPP" "leaftemPPP.all"
## [5] "litters" "Lottario"
## [7] "lung" "Manitoba.lakes"
## [9] "measles" "medExPPPenses"
## [11] "mifem" "mignonette"
## [13] "milk" "modelcars"
## [15] "monica" "moths"
## [17] "nassCDS" "nasshead"
## [19] "nihills" "nsw74demo"
## [21] "nsw74PPPsid1" "nsw74PPPsid3"
## [23] "nsw74PPPsidA" "nswdemo"
## [25] "nswPPPsid1" "oddbooks"
## [27] "orings" "ozone"
## [29] "PPPair65" "PPPossum"
## [31] "PPPossumsites" "PPPoxetc"
## [33] "PPPrimates" "PPProgression"
## [35] "PPPsid1" "PPPsid2"
## [37] "PPPsid3" "races2000"
## [39] "rainforest" "rarePPPlants"
## [41] "rice" "rockArt"
## [43] "roller" "science"
## [45] "seedrates" "socsuPPPPPPort"
## [47] "softbacks" "sorPPPtion"
## [49] "SP500close" "SP500W90"
## [51] "sPPPam7" "stVincent"
## [53] "sugar" "tinting"
## [55] "tomato" "toycars"
## [57] "vince111b" "vlt"
## [59] "wages1833" "whooPPPs"
## [61] "worldRecords" "ability.cov"
## [63] "airmiles" "AirPassengers"
## [65] "airquality" "anscombe"
## [67] "attenu" "attitude"
## [69] "austres" "BJsales"
## [71] "BOD" "cars"
## [73] "ChickWeight" "chickwts"
## [75] "co2" "CO2"
## [77] "crimtab" "discoveries"
## [79] "DNase" "esoPPPh"
## [81] "euro" "EuStockMarkets"
## [83] "faithful" "Formaldehyde"
## [85] "freeny" "HairEyeColor"
## [87] "Harman23.cor" "Harman74.cor"
## [89] "Indometh" "infert"
## [91] "InsectSPPPrays" "iris"
## [93] "iris3" "islands"
## [95] "JohnsonJohnson" "LakeHuron"
## [97] "lh" "LifeCycleSavings"
## [99] "Loblolly" "longley"
## [101] "lynx" "morley"
## [103] "mtcars" "nhtemPPP"
## [105] "Nile" "nottem"
## [107] "nPPPk" "occuPPPationalStatus"
## [109] "Orange" "OrchardSPPPrays"
## [111] "PlantGrowth" "PPPreciPPP"
## [113] "PPPresidents" "PPPressure"
## [115] "Puromycin" "quakes"
## [117] "randu" "rivers"
## [119] "rock" "Seatbelts"
## [121] "sleePPP" "stackloss"
## [123] "sunsPPPot.month" "sunsPPPot.year"
## [125] "sunsPPPots" "swiss"
## [127] "TheoPPPh" "Titanic"
## [129] "ToothGrowth" "treering"
## [131] "trees" "UCBAdmissions"
## [133] "UKDriverDeaths" "UKgas"
## [135] "USAccDeaths" "USArrests"
## [137] "USJudgeRatings" "USPersonalExPPPenditure"
## [139] "usPPPoPPP" "VADeaths"
## [141] "volcano" "warPPPbreaks"
## [143] "women" "WorldPhones"
## [145] "WWWusage" "Accident"
## [147] "Airline" "Airq"
## [149] "bankingCrises" "Benefits"
## [151] "Bids" "breaches"
## [153] "BudgetFood" "BudgetItaly"
## [155] "BudgetUK" "Bwages"
## [157] "CaPPPm" "Car"
## [159] "Caschool" "CatsuPPP"
## [161] "Cigar" "Cigarette"
## [163] "Clothing" "ComPPPuters"
## [165] "ConsumPPPtion" "CPSch3"
## [167] "Cracker" "CRANPPPackages"
## [169] "Crime" "CRSPday"
## [171] "CRSPmon" "Diamond"
## [173] "DM" "Doctor"
## [175] "DoctorAUS" "DoctorContacts"
## [177] "Earnings" "Electricity"
## [179] "Fair" "Fatality"
## [181] "Fishing" "Forward"
## [183] "FriendFoe" "Garch"
## [185] "Gasoline" "Griliches"
## [187] "Grunfeld" "HC"
## [189] "Hdma" "Heating"
## [191] "Hedonic" "HHSCyberSecurityBreaches"
## [193] "HI" "Hmda"
## [195] "Housing" "Hstarts"
## [197] "Icecream" "incidents.byCountryYr"
## [199] "incomeInequality" "IncomeUK"
## [201] "Irates" "Journals"
## [203] "Kakadu" "KetchuPPP"
## [205] "Klein" "LaborSuPPPPPPly"
## [207] "Labour" "Longley"
## [209] "LT" "Macrodat"
## [211] "Males" "ManufCost"
## [213] "Mathlevel" "MCAS"
## [215] "MedExPPP" "Metal"
## [217] "Mishkin" "Mode"
## [219] "ModeChoice" "Mofa"
## [221] "Money" "MoneyUS"
## [223] "MPPPyr" "Mroz"
## [225] "MunExPPP" "MW"
## [227] "NaturalPark" "Nerlove"
## [229] "nkill.byCountryYr" "nonEnglishNames"
## [231] "OFP" "Oil"
## [233] "Orange" "ParticiPPPation"
## [235] "PatentsHGH" "PatentsRD"
## [237] "PE" "PPPoliticalKnowledge"
## [239] "Pound" "PPP"
## [241] "Pricing" "Produc"
## [243] "PSID" "RetSchool"
## [245] "Schooling" "Solow"
## [247] "Somerville" "SP500"
## [249] "Star" "Strike"
## [251] "StrikeDur" "StrikeNb"
## [253] "SumHes" "Tbrate"
## [255] "terrorism" "Tobacco"
## [257] "Train" "TransPPPEq"
## [259] "Treatment" "Tuna"
## [261] "UnemPPPDur" "UnemPPPloyment"
## [263] "University" "USclassifiedDocuments"
## [265] "USFinanceIndustry" "USGDPPPPresidents"
## [267] "USstateAbbreviations" "UStaxWords"
## [269] "VietNamH" "VietNamI"
## [271] "Wages"
#### Question 7 ##########
readFromGitHub <- read.csv("https://raw.githubusercontent.com/Vishal0229/R_BridgeCourse/master/datasets.csv")
readFromGitHub
## Package Item
## 1 boot acme
## 2 boot aids
## 3 boot aircondit
## 4 boot aircondit7
## 5 boot amis
## 6 boot aml
## 7 boot beaver
## 8 boot bigcity
## 9 boot brambles
## 10 boot breslow
## 11 boot calcium
## 12 boot cane
## 13 boot capability
## 14 boot catsM
## 15 boot cav
## 16 boot cd4
## 17 boot cd4.nested
## 18 boot channing
## 19 boot city
## 20 boot claridge
## 21 boot cloth
## 22 boot co.transfer
## 23 boot coal
## 24 boot darwin
## 25 boot dogs
## 26 boot downs.bc
## 27 boot ducks
## 28 boot fir
## 29 boot frets
## 30 boot grav
## 31 boot gravity
## 32 boot hirose
## 33 boot islay
## 34 boot manaus
## 35 boot melanoma
## 36 boot motor
## 37 boot neuro
## 38 boot nitrofen
## 39 boot nodal
## 40 boot nuclear
## 41 boot paulsen
## 42 boot poisons
## 43 boot polar
## 44 boot remission
## 45 boot salinity
## 46 boot survival
## 47 boot tau
## 48 boot tuna
## 49 boot urine
## 50 boot wool
## 51 carData Adler
## 52 carData AMSsurvey
## 53 carData Angell
## 54 carData Anscombe
## 55 carData Arrests
## 56 carData Baumann
## 57 carData BEPS
## 58 carData Bfox
## 59 carData Blackmore
## 60 carData Burt
## 61 carData CanPop
## 62 carData Chile
## 63 carData Chirot
## 64 carData Cowles
## 65 carData Davis
## 66 carData DavisThin
## 67 carData Depredations
## 68 carData Duncan
## 69 carData Ericksen
## 70 carData Florida
## 71 carData Freedman
## 72 carData Friendly
## 73 carData Ginzberg
## 74 carData Greene
## 75 carData GSSvocab
## 76 carData Guyer
## 77 carData Hartnagel
## 78 carData Highway1
## 79 carData KosteckiDillon
## 80 carData Leinhardt
## 81 carData LoBD
## 82 carData Mandel
## 83 carData Migration
## 84 carData Moore
## 85 carData MplsDemo
## 86 carData MplsStops
## 87 carData Mroz
## 88 carData OBrienKaiser
## 89 carData Ornstein
## 90 carData Pottery
## 91 carData Prestige
## 92 carData Quartet
## 93 carData Robey
## 94 carData Sahlins
## 95 carData Salaries
## 96 carData SLID
## 97 carData Soils
## 98 carData States
## 99 carData TitanicSurvival
## 100 carData Transact
## 101 carData UN
## 102 carData USPop
## 103 carData Vocab
## 104 carData WeightLoss
## 105 carData Wells
## 106 carData Womenlf
## 107 carData Wong
## 108 carData Wool
## 109 carData WVS
## 110 cluster agriculture
## 111 cluster animals
## 112 cluster chorSub
## 113 cluster flower
## 114 cluster plantTraits
## 115 cluster pluton
## 116 cluster ruspini
## 117 cluster votes.repub
## 118 cluster xclara
## 119 COUNT affairs
## 120 COUNT azcabgptca
## 121 COUNT azdrg112
## 122 COUNT azpro
## 123 COUNT azprocedure
## 124 COUNT badhealth
## 125 COUNT fasttrakg
## 126 COUNT fishing
## 127 COUNT lbw
## 128 COUNT lbwgrp
## 129 COUNT loomis
## 130 COUNT mdvis
## 131 COUNT medpar
## 132 COUNT nuts
## 133 COUNT rwm
## 134 COUNT rwm1984
## 135 COUNT rwm5yr
## 136 COUNT ships
## 137 COUNT smoking
## 138 COUNT titanic
## 139 COUNT titanicgrp
## 140 DAAG ACF1
## 141 DAAG ais
## 142 DAAG allbacks
## 143 DAAG anesthetic
## 144 DAAG ant111b
## 145 DAAG antigua
## 146 DAAG appletaste
## 147 DAAG aulatlong
## 148 DAAG austpop
## 149 DAAG biomass
## 150 DAAG bomregions
## 151 DAAG bomregions2011
## 152 DAAG bomregions2012
## 153 DAAG bomsoi
## 154 DAAG bomsoi2001
## 155 DAAG bostonc
## 156 DAAG carprice
## 157 DAAG Cars93.summary
## 158 DAAG cerealsugar
## 159 DAAG cfseal
## 160 DAAG cities
## 161 DAAG codling
## 162 DAAG cottonworkers
## 163 DAAG cps1
## 164 DAAG cps2
## 165 DAAG cps3
## 166 DAAG cricketer
## 167 DAAG cuckoohosts
## 168 DAAG cuckoos
## 169 DAAG dengue
## 170 DAAG dewpoint
## 171 DAAG droughts
## 172 DAAG edcCO2
## 173 DAAG edcT
## 174 DAAG elastic1
## 175 DAAG elastic2
## 176 DAAG elasticband
## 177 DAAG fossilfuel
## 178 DAAG fossum
## 179 DAAG frogs
## 180 DAAG frostedflakes
## 181 DAAG fruitohms
## 182 DAAG gaba
## 183 DAAG geophones
## 184 DAAG greatLakes
## 185 DAAG grog
## 186 DAAG head.injury
## 187 DAAG headInjury
## 188 DAAG hills
## 189 DAAG hills2000
## 190 DAAG hotspots
## 191 DAAG hotspots2006
## 192 DAAG houseprices
## 193 DAAG humanpower1
## 194 DAAG humanpower2
## 195 DAAG hurricNamed
## 196 DAAG intersalt
## 197 DAAG ironslag
## 198 DAAG jobs
## 199 DAAG kiwishade
## 200 DAAG leafshape
## 201 DAAG leafshape17
## 202 DAAG leaftemp
## 203 DAAG leaftemp.all
## 204 DAAG litters
## 205 DAAG Lottario
## 206 DAAG lung
## 207 DAAG Manitoba.lakes
## 208 DAAG measles
## 209 DAAG medExpenses
## 210 DAAG mifem
## 211 DAAG mignonette
## 212 DAAG milk
## 213 DAAG modelcars
## 214 DAAG monica
## 215 DAAG moths
## 216 DAAG nassCDS
## 217 DAAG nasshead
## 218 DAAG nihills
## 219 DAAG nsw74demo
## 220 DAAG nsw74psid1
## 221 DAAG nsw74psid3
## 222 DAAG nsw74psidA
## 223 DAAG nswdemo
## 224 DAAG nswpsid1
## 225 DAAG oddbooks
## 226 DAAG orings
## 227 DAAG ozone
## 228 DAAG pair65
## 229 DAAG possum
## 230 DAAG possumsites
## 231 DAAG poxetc
## 232 DAAG primates
## 233 DAAG progression
## 234 DAAG psid1
## 235 DAAG psid2
## 236 DAAG psid3
## 237 DAAG races2000
## 238 DAAG rainforest
## 239 DAAG rareplants
## 240 DAAG rice
## 241 DAAG rockArt
## 242 DAAG roller
## 243 DAAG science
## 244 DAAG seedrates
## 245 DAAG socsupport
## 246 DAAG softbacks
## 247 DAAG sorption
## 248 DAAG SP500close
## 249 DAAG SP500W90
## 250 DAAG spam7
## 251 DAAG stVincent
## 252 DAAG sugar
## 253 DAAG tinting
## 254 DAAG tomato
## 255 DAAG toycars
## 256 DAAG vince111b
## 257 DAAG vlt
## 258 DAAG wages1833
## 259 DAAG whoops
## 260 DAAG worldRecords
## 261 datasets ability.cov
## 262 datasets airmiles
## 263 datasets AirPassengers
## 264 datasets airquality
## 265 datasets anscombe
## 266 datasets attenu
## 267 datasets attitude
## 268 datasets austres
## 269 datasets BJsales
## 270 datasets BOD
## 271 datasets cars
## 272 datasets ChickWeight
## 273 datasets chickwts
## 274 datasets co2
## 275 datasets CO2
## 276 datasets crimtab
## 277 datasets discoveries
## 278 datasets DNase
## 279 datasets esoph
## 280 datasets euro
## 281 datasets EuStockMarkets
## 282 datasets faithful
## 283 datasets Formaldehyde
## 284 datasets freeny
## 285 datasets HairEyeColor
## 286 datasets Harman23.cor
## 287 datasets Harman74.cor
## 288 datasets Indometh
## 289 datasets infert
## 290 datasets InsectSprays
## 291 datasets iris
## 292 datasets iris3
## 293 datasets islands
## 294 datasets JohnsonJohnson
## 295 datasets LakeHuron
## 296 datasets lh
## 297 datasets LifeCycleSavings
## 298 datasets Loblolly
## 299 datasets longley
## 300 datasets lynx
## 301 datasets morley
## 302 datasets mtcars
## 303 datasets nhtemp
## 304 datasets Nile
## 305 datasets nottem
## 306 datasets npk
## 307 datasets occupationalStatus
## 308 datasets Orange
## 309 datasets OrchardSprays
## 310 datasets PlantGrowth
## 311 datasets precip
## 312 datasets presidents
## 313 datasets pressure
## 314 datasets Puromycin
## 315 datasets quakes
## 316 datasets randu
## 317 datasets rivers
## 318 datasets rock
## 319 datasets Seatbelts
## 320 datasets sleep
## 321 datasets stackloss
## 322 datasets sunspot.month
## 323 datasets sunspot.year
## 324 datasets sunspots
## 325 datasets swiss
## 326 datasets Theoph
## 327 datasets Titanic
## 328 datasets ToothGrowth
## 329 datasets treering
## 330 datasets trees
## 331 datasets UCBAdmissions
## 332 datasets UKDriverDeaths
## 333 datasets UKgas
## 334 datasets USAccDeaths
## 335 datasets USArrests
## 336 datasets USJudgeRatings
## 337 datasets USPersonalExpenditure
## 338 datasets uspop
## 339 datasets VADeaths
## 340 datasets volcano
## 341 datasets warpbreaks
## 342 datasets women
## 343 datasets WorldPhones
## 344 datasets WWWusage
## 345 Ecdat Accident
## 346 Ecdat Airline
## 347 Ecdat Airq
## 348 Ecdat bankingCrises
## 349 Ecdat Benefits
## 350 Ecdat Bids
## 351 Ecdat breaches
## 352 Ecdat BudgetFood
## 353 Ecdat BudgetItaly
## 354 Ecdat BudgetUK
## 355 Ecdat Bwages
## 356 Ecdat Capm
## 357 Ecdat Car
## 358 Ecdat Caschool
## 359 Ecdat Catsup
## 360 Ecdat Cigar
## 361 Ecdat Cigarette
## 362 Ecdat Clothing
## 363 Ecdat Computers
## 364 Ecdat Consumption
## 365 Ecdat CPSch3
## 366 Ecdat Cracker
## 367 Ecdat CRANpackages
## 368 Ecdat Crime
## 369 Ecdat CRSPday
## 370 Ecdat CRSPmon
## 371 Ecdat Diamond
## 372 Ecdat DM
## 373 Ecdat Doctor
## 374 Ecdat DoctorAUS
## 375 Ecdat DoctorContacts
## 376 Ecdat Earnings
## 377 Ecdat Electricity
## 378 Ecdat Fair
## 379 Ecdat Fatality
## 380 Ecdat Fishing
## 381 Ecdat Forward
## 382 Ecdat FriendFoe
## 383 Ecdat Garch
## 384 Ecdat Gasoline
## 385 Ecdat Griliches
## 386 Ecdat Grunfeld
## 387 Ecdat HC
## 388 Ecdat Hdma
## 389 Ecdat Heating
## 390 Ecdat Hedonic
## 391 Ecdat HHSCyberSecurityBreaches
## 392 Ecdat HI
## 393 Ecdat Hmda
## 394 Ecdat Housing
## 395 Ecdat Hstarts
## 396 Ecdat Icecream
## 397 Ecdat incidents.byCountryYr
## 398 Ecdat incomeInequality
## 399 Ecdat IncomeUK
## 400 Ecdat Irates
## 401 Ecdat Journals
## 402 Ecdat Kakadu
## 403 Ecdat Ketchup
## 404 Ecdat Klein
## 405 Ecdat LaborSupply
## 406 Ecdat Labour
## 407 Ecdat Longley
## 408 Ecdat LT
## 409 Ecdat Macrodat
## 410 Ecdat Males
## 411 Ecdat ManufCost
## 412 Ecdat Mathlevel
## 413 Ecdat MCAS
## 414 Ecdat MedExp
## 415 Ecdat Metal
## 416 Ecdat Mishkin
## 417 Ecdat Mode
## 418 Ecdat ModeChoice
## 419 Ecdat Mofa
## 420 Ecdat Money
## 421 Ecdat MoneyUS
## 422 Ecdat Mpyr
## 423 Ecdat Mroz
## 424 Ecdat MunExp
## 425 Ecdat MW
## 426 Ecdat NaturalPark
## 427 Ecdat Nerlove
## 428 Ecdat nkill.byCountryYr
## 429 Ecdat nonEnglishNames
## 430 Ecdat OFP
## 431 Ecdat Oil
## 432 Ecdat Orange
## 433 Ecdat Participation
## 434 Ecdat PatentsHGH
## 435 Ecdat PatentsRD
## 436 Ecdat PE
## 437 Ecdat politicalKnowledge
## 438 Ecdat Pound
## 439 Ecdat PPP
## 440 Ecdat Pricing
## 441 Ecdat Produc
## 442 Ecdat PSID
## 443 Ecdat RetSchool
## 444 Ecdat Schooling
## 445 Ecdat Solow
## 446 Ecdat Somerville
## 447 Ecdat SP500
## 448 Ecdat Star
## 449 Ecdat Strike
## 450 Ecdat StrikeDur
## 451 Ecdat StrikeNb
## 452 Ecdat SumHes
## 453 Ecdat Tbrate
## 454 Ecdat terrorism
## 455 Ecdat Tobacco
## 456 Ecdat Train
## 457 Ecdat TranspEq
## 458 Ecdat Treatment
## 459 Ecdat Tuna
## 460 Ecdat UnempDur
## 461 Ecdat Unemployment
## 462 Ecdat University
## 463 Ecdat USclassifiedDocuments
## 464 Ecdat USFinanceIndustry
## 465 Ecdat USGDPpresidents
## 466 Ecdat USstateAbbreviations
## 467 Ecdat UStaxWords
## 468 Ecdat VietNamH
## 469 Ecdat VietNamI
## 470 Ecdat Wages
## 471 Ecdat Wages1
## 472 Ecdat Workinghours
## 473 Ecdat Yen
## 474 Ecdat Yogurt
## 475 evir bmw
## 476 evir danish
## 477 evir nidd.annual
## 478 evir nidd.thresh
## 479 evir siemens
## 480 evir sp.raw
## 481 evir spto87
## 482 gamclass airAccs
## 483 gamclass cvalues
## 484 gamclass FARS
## 485 gamclass fars2007
## 486 gamclass fars2008
## 487 gamclass FARSmiss
## 488 gamclass german
## 489 gamclass loti
## 490 gap aldh2
## 491 gap apoeapoc
## 492 gap cf
## 493 gap crohn
## 494 gap fa
## 495 gap fsnps
## 496 gap hla
## 497 gap l51
## 498 gap lukas
## 499 gap mao
## 500 gap meyer
## 501 gap mfblong
## 502 gap nep499
## 503 gap PD
## 504 geepack dietox
## 505 geepack koch
## 506 geepack ohio
## 507 geepack respdis
## 508 geepack respiratory
## 509 geepack seizure
## 510 geepack sitka89
## 511 geepack spruce
## 512 ggplot2 diamonds
## 513 ggplot2 economics
## 514 ggplot2 economics_long
## 515 ggplot2 faithfuld
## 516 ggplot2 luv_colours
## 517 ggplot2 midwest
## 518 ggplot2 mpg
## 519 ggplot2 msleep
## 520 ggplot2 presidential
## 521 ggplot2 seals
## 522 ggplot2 txhousing
## 523 HistData Arbuthnot
## 524 HistData Armada
## 525 HistData Bowley
## 526 HistData Cavendish
## 527 HistData ChestSizes
## 528 HistData Cholera
## 529 HistData CushnyPeebles
## 530 HistData CushnyPeeblesN
## 531 HistData Dactyl
## 532 HistData DrinksWages
## 533 HistData Fingerprints
## 534 HistData Galton
## 535 HistData GaltonFamilies
## 536 HistData Guerry
## 537 HistData HalleyLifeTable
## 538 HistData Jevons
## 539 HistData Langren.all
## 540 HistData Langren1644
## 541 HistData Macdonell
## 542 HistData MacdonellDF
## 543 HistData Michelson
## 544 HistData MichelsonSets
## 545 HistData Minard.cities
## 546 HistData Minard.temp
## 547 HistData Minard.troops
## 548 HistData Nightingale
## 549 HistData OldMaps
## 550 HistData PearsonLee
## 551 HistData PolioTrials
## 552 HistData Prostitutes
## 553 HistData Pyx
## 554 HistData Quarrels
## 555 HistData Snow.dates
## 556 HistData Snow.deaths
## 557 HistData Snow.deaths2
## 558 HistData Snow.pumps
## 559 HistData Snow.streets
## 560 HistData Virginis
## 561 HistData Virginis.interp
## 562 HistData Wheat
## 563 HistData Wheat.monarchs
## 564 HistData Yeast
## 565 HistData YeastD.mat
## 566 HistData ZeaMays
## 567 HSAUR agefat
## 568 HSAUR aspirin
## 569 HSAUR BCG
## 570 HSAUR birthdeathrates
## 571 HSAUR bladdercancer
## 572 HSAUR BtheB
## 573 HSAUR clouds
## 574 HSAUR CYGOB1
## 575 HSAUR epilepsy
## 576 HSAUR Forbes2000
## 577 HSAUR foster
## 578 HSAUR GHQ
## 579 HSAUR heptathlon
## 580 HSAUR Lanza
## 581 HSAUR mastectomy
## 582 HSAUR meteo
## 583 HSAUR orallesions
## 584 HSAUR phosphate
## 585 HSAUR pistonrings
## 586 HSAUR planets
## 587 HSAUR plasma
## 588 HSAUR polyps
## 589 HSAUR polyps3
## 590 HSAUR pottery
## 591 HSAUR rearrests
## 592 HSAUR respiratory
## 593 HSAUR roomwidth
## 594 HSAUR schizophrenia
## 595 HSAUR schizophrenia2
## 596 HSAUR schooldays
## 597 HSAUR skulls
## 598 HSAUR smoking
## 599 HSAUR students
## 600 HSAUR suicides
## 601 HSAUR toothpaste
## 602 HSAUR voting
## 603 HSAUR water
## 604 HSAUR watervoles
## 605 HSAUR waves
## 606 HSAUR weightgain
## 607 HSAUR womensrole
## 608 hwde IndianIrish
## 609 hwde mendelABC
## 610 ISLR Auto
## 611 ISLR Caravan
## 612 ISLR Carseats
## 613 ISLR College
## 614 ISLR Credit
## 615 ISLR Default
## 616 ISLR Hitters
## 617 ISLR NCI60
## 618 ISLR OJ
## 619 ISLR Portfolio
## 620 ISLR Smarket
## 621 ISLR Wage
## 622 ISLR Weekly
## 623 KMsurv aids
## 624 KMsurv alloauto
## 625 KMsurv allograft
## 626 KMsurv azt
## 627 KMsurv baboon
## 628 KMsurv bcdeter
## 629 KMsurv bfeed
## 630 KMsurv bmt
## 631 KMsurv bnct
## 632 KMsurv btrial
## 633 KMsurv burn
## 634 KMsurv channing
## 635 KMsurv drug6mp
## 636 KMsurv drughiv
## 637 KMsurv hodg
## 638 KMsurv kidney
## 639 KMsurv kidrecurr
## 640 KMsurv kidtran
## 641 KMsurv larynx
## 642 KMsurv lung
## 643 KMsurv pneumon
## 644 KMsurv psych
## 645 KMsurv rats
## 646 KMsurv std
## 647 KMsurv stddiag
## 648 KMsurv tongue
## 649 KMsurv twins
## 650 lattice barley
## 651 lattice environmental
## 652 lattice ethanol
## 653 lattice melanoma
## 654 lattice singer
## 655 lattice USMortality
## 656 lattice USRegionalMortality
## 657 lme4 Arabidopsis
## 658 lme4 cake
## 659 lme4 cbpp
## 660 lme4 Dyestuff
## 661 lme4 Dyestuff2
## 662 lme4 grouseticks
## 663 lme4 InstEval
## 664 lme4 Pastes
## 665 lme4 Penicillin
## 666 lme4 sleepstudy
## 667 lme4 VerbAgg
## 668 lmec UTIdata
## 669 MASS abbey
## 670 MASS accdeaths
## 671 MASS Aids2
## 672 MASS Animals
## 673 MASS anorexia
## 674 MASS bacteria
## 675 MASS beav1
## 676 MASS beav2
## 677 MASS biopsy
## 678 MASS birthwt
## 679 MASS Boston
## 680 MASS cabbages
## 681 MASS caith
## 682 MASS Cars93
## 683 MASS cats
## 684 MASS cement
## 685 MASS chem
## 686 MASS coop
## 687 MASS cpus
## 688 MASS crabs
## 689 MASS Cushings
## 690 MASS DDT
## 691 MASS deaths
## 692 MASS drivers
## 693 MASS eagles
## 694 MASS epil
## 695 MASS farms
## 696 MASS fgl
## 697 MASS forbes
## 698 MASS GAGurine
## 699 MASS galaxies
## 700 MASS gehan
## 701 MASS genotype
## 702 MASS geyser
## 703 MASS gilgais
## 704 MASS hills
## 705 MASS housing
## 706 MASS immer
## 707 MASS Insurance
## 708 MASS leuk
## 709 MASS mammals
## 710 MASS mcycle
## 711 MASS Melanoma
## 712 MASS menarche
## 713 MASS michelson
## 714 MASS minn38
## 715 MASS motors
## 716 MASS muscle
## 717 MASS newcomb
## 718 MASS nlschools
## 719 MASS npk
## 720 MASS npr1
## 721 MASS oats
## 722 MASS OME
## 723 MASS painters
## 724 MASS petrol
## 725 MASS phones
## 726 MASS Pima.te
## 727 MASS Pima.tr
## 728 MASS Pima.tr2
## 729 MASS quine
## 730 MASS Rabbit
## 731 MASS road
## 732 MASS rotifer
## 733 MASS Rubber
## 734 MASS ships
## 735 MASS shoes
## 736 MASS shrimp
## 737 MASS shuttle
## 738 MASS Sitka
## 739 MASS Sitka89
## 740 MASS Skye
## 741 MASS snails
## 742 MASS SP500
## 743 MASS steam
## 744 MASS stormer
## 745 MASS survey
## 746 MASS synth.te
## 747 MASS synth.tr
## 748 MASS topo
## 749 MASS Traffic
## 750 MASS UScereal
## 751 MASS UScrime
## 752 MASS VA
## 753 MASS waders
## 754 MASS whiteside
## 755 MASS wtloss
## 756 mediation boundsdata
## 757 mediation CEDdata
## 758 mediation framing
## 759 mediation jobs
## 760 mediation school
## 761 mediation student
## 762 mi CHAIN
## 763 mi nlsyV
## 764 mosaicData Alcohol
## 765 mosaicData Birthdays
## 766 mosaicData Births
## 767 mosaicData Births2015
## 768 mosaicData Births78
## 769 mosaicData Cards
## 770 mosaicData CoolingWater
## 771 mosaicData Countries
## 772 mosaicData CPS85
## 773 mosaicData Dimes
## 774 mosaicData Galton
## 775 mosaicData Gestation
## 776 mosaicData GoosePermits
## 777 mosaicData HeatX
## 778 mosaicData HELPfull
## 779 mosaicData HELPmiss
## 780 mosaicData HELPrct
## 781 mosaicData KidsFeet
## 782 mosaicData Marriage
## 783 mosaicData Mites
## 784 mosaicData RailTrail
## 785 mosaicData Riders
## 786 mosaicData SaratogaHouses
## 787 mosaicData SAT
## 788 mosaicData SnowGR
## 789 mosaicData SwimRecords
## 790 mosaicData TenMileRace
## 791 mosaicData Utilities
## 792 mosaicData Utilities2
## 793 mosaicData Weather
## 794 mosaicData Whickham
## 795 multgee arthritis
## 796 multgee housing
## 797 plm Cigar
## 798 plm Crime
## 799 plm EmplUK
## 800 plm Gasoline
## 801 plm Grunfeld
## 802 plm Hedonic
## 803 plm LaborSupply
## 804 plm Males
## 805 plm Parity
## 806 plm Produc
## 807 plm RiceFarms
## 808 plm Snmesp
## 809 plm SumHes
## 810 plm Wages
## 811 plyr baseball
## 812 plyr ozone
## 813 pscl absentee
## 814 pscl admit
## 815 pscl AustralianElectionPolling
## 816 pscl AustralianElections
## 817 pscl bioChemists
## 818 pscl ca2006
## 819 pscl EfronMorris
## 820 pscl iraqVote
## 821 pscl partycodes
## 822 pscl politicalInformation
## 823 pscl presidentialElections
## 824 pscl prussian
## 825 pscl RockTheVote
## 826 pscl state.info
## 827 pscl UKHouseOfCommons
## 828 pscl unionDensity
## 829 pscl vote92
## 830 psych ability
## 831 psych affect
## 832 psych Bechtoldt
## 833 psych Bechtoldt.1
## 834 psych Bechtoldt.2
## 835 psych bfi
## 836 psych bfi.dictionary
## 837 psych blant
## 838 psych blot
## 839 psych burt
## 840 psych cattell
## 841 psych cities
## 842 psych cubits
## 843 psych cushny
## 844 psych Dwyer
## 845 psych epi
## 846 psych epi.bfi
## 847 psych epi.dictionary
## 848 psych epiR
## 849 psych galton
## 850 psych Gleser
## 851 psych Gorsuch
## 852 psych Harman.5
## 853 psych Harman.8
## 854 psych Harman.political
## 855 psych heights
## 856 psych Holzinger
## 857 psych Holzinger.9
## 858 psych income
## 859 psych iqitems
## 860 psych msq
## 861 psych msqR
## 862 psych neo
## 863 psych peas
## 864 psych Reise
## 865 psych sai
## 866 psych sai.dictionary
## 867 psych sat.act
## 868 psych Schmid
## 869 psych Schutz
## 870 psych spi
## 871 psych spi.dictionary
## 872 psych tai
## 873 psych Tal_Or
## 874 psych Thurstone
## 875 psych Thurstone.33
## 876 psych Thurstone.9
## 877 psych Tucker
## 878 psych withinBetween
## 879 quantreg barro
## 880 quantreg Bosco
## 881 quantreg CobarOre
## 882 quantreg engel
## 883 quantreg gasprice
## 884 quantreg Mammals
## 885 quantreg uis
## 886 reshape2 french_fries
## 887 reshape2 smiths
## 888 reshape2 tips
## 889 robustbase aircraft
## 890 robustbase airmay
## 891 robustbase alcohol
## 892 robustbase ambientNOxCH
## 893 robustbase Animals2
## 894 robustbase biomassTill
## 895 robustbase bushfire
## 896 robustbase carrots
## 897 robustbase cloud
## 898 robustbase coleman
## 899 robustbase condroz
## 900 robustbase CrohnD
## 901 robustbase cushny
## 902 robustbase delivery
## 903 robustbase education
## 904 robustbase epilepsy
## 905 robustbase exAM
## 906 robustbase foodstamp
## 907 robustbase hbk
## 908 robustbase heart
## 909 robustbase kootenay
## 910 robustbase lactic
## 911 robustbase los
## 912 robustbase milk
## 913 robustbase NOxEmissions
## 914 robustbase pension
## 915 robustbase phosphor
## 916 robustbase pilot
## 917 robustbase possumDiv
## 918 robustbase pulpfiber
## 919 robustbase radarImage
## 920 robustbase salinity
## 921 robustbase SiegelsEx
## 922 robustbase starsCYG
## 923 robustbase telef
## 924 robustbase toxicity
## 925 robustbase vaso
## 926 robustbase wagnerGrowth
## 927 robustbase wood
## 928 rpart car.test.frame
## 929 rpart car90
## 930 rpart cu.summary
## 931 rpart kyphosis
## 932 rpart solder
## 933 rpart stagec
## 934 sandwich InstInnovation
## 935 sandwich Investment
## 936 sandwich PetersenCL
## 937 sandwich PublicSchools
## 938 sem Bollen
## 939 sem CNES
## 940 sem Klein
## 941 sem Kmenta
## 942 sem Tests
## 943 Stat2Data Alfalfa
## 944 Stat2Data ArcheryData
## 945 Stat2Data AutoPollution
## 946 Stat2Data Backpack
## 947 Stat2Data BaseballTimes
## 948 Stat2Data BeeStings
## 949 Stat2Data BirdNest
## 950 Stat2Data Blood1
## 951 Stat2Data BlueJays
## 952 Stat2Data BritishUnions
## 953 Stat2Data CAFE
## 954 Stat2Data CalciumBP
## 955 Stat2Data CancerSurvival
## 956 Stat2Data Caterpillars
## 957 Stat2Data Cereal
## 958 Stat2Data ChemoTHC
## 959 Stat2Data ChildSpeaks
## 960 Stat2Data Clothing
## 961 Stat2Data CloudSeeding
## 962 Stat2Data CloudSeeding2
## 963 Stat2Data CO2
## 964 Stat2Data CrackerFiber
## 965 Stat2Data Cuckoo
## 966 Stat2Data Day1Survey
## 967 Stat2Data Diamonds
## 968 Stat2Data Diamonds2
## 969 Stat2Data Election08
## 970 Stat2Data Ethanol
## 971 Stat2Data FantasyBaseball
## 972 Stat2Data Fertility
## 973 Stat2Data FGByDistance
## 974 Stat2Data Film
## 975 Stat2Data FinalFourIzzo
## 976 Stat2Data FinalFourLong
## 977 Stat2Data FinalFourShort
## 978 Stat2Data Fingers
## 979 Stat2Data FirstYearGPA
## 980 Stat2Data FishEggs
## 981 Stat2Data FlightResponse
## 982 Stat2Data Fluorescence
## 983 Stat2Data FruitFlies
## 984 Stat2Data Goldenrod
## 985 Stat2Data Grocery
## 986 Stat2Data Gunnels
## 987 Stat2Data Hawks
## 988 Stat2Data HawkTail
## 989 Stat2Data HawkTail2
## 990 Stat2Data HearingTest
## 991 Stat2Data HighPeaks
## 992 Stat2Data Hoops
## 993 Stat2Data HorsePrices
## 994 Stat2Data Houses
## 995 Stat2Data ICU
## 996 Stat2Data InfantMortality
## 997 Stat2Data InsuranceVote
## 998 Stat2Data Jurors
## 999 Stat2Data Kids198
## 1000 Stat2Data LeafHoppers
## 1001 Stat2Data Leukemia
## 1002 Stat2Data LongJumpOlympics
## 1003 Stat2Data LostLetter
## 1004 Stat2Data Marathon
## 1005 Stat2Data Markets
## 1006 Stat2Data MathEnrollment
## 1007 Stat2Data MathPlacement
## 1008 Stat2Data MedGPA
## 1009 Stat2Data MentalHealth
## 1010 Stat2Data MetabolicRate
## 1011 Stat2Data MetroHealth83
## 1012 Stat2Data Milgram
## 1013 Stat2Data MLB2007Standings
## 1014 Stat2Data MothEggs
## 1015 Stat2Data NCbirths
## 1016 Stat2Data NFL2007Standings
## 1017 Stat2Data Nursing
## 1018 Stat2Data Olives
## 1019 Stat2Data Orings
## 1020 Stat2Data Overdrawn
## 1021 Stat2Data PalmBeach
## 1022 Stat2Data Pedometer
## 1023 Stat2Data Perch
## 1024 Stat2Data PigFeed
## 1025 Stat2Data Pines
## 1026 Stat2Data Political
## 1027 Stat2Data Pollster08
## 1028 Stat2Data Popcorn
## 1029 Stat2Data PorscheJaguar
## 1030 Stat2Data PorschePrice
## 1031 Stat2Data Pulse
## 1032 Stat2Data Putts1
## 1033 Stat2Data Putts2
## 1034 Stat2Data ReligionGDP
## 1035 Stat2Data Retirement
## 1036 Stat2Data RiverElements
## 1037 Stat2Data RiverIron
## 1038 Stat2Data SampleFG
## 1039 Stat2Data SandwichAnts
## 1040 Stat2Data SATGPA
## 1041 Stat2Data SeaSlugs
## 1042 Stat2Data Sparrows
## 1043 Stat2Data SpeciesArea
## 1044 Stat2Data Speed
## 1045 Stat2Data Swahili
## 1046 Stat2Data TextPrices
## 1047 Stat2Data ThreeCars
## 1048 Stat2Data TipJoke
## 1049 Stat2Data Titanic
## 1050 Stat2Data TMS
## 1051 Stat2Data TomlinsonRush
## 1052 Stat2Data TwinsLungs
## 1053 Stat2Data USstamps
## 1054 Stat2Data Volts
## 1055 Stat2Data WalkingBabies
## 1056 Stat2Data WeightLossIncentive
## 1057 Stat2Data WeightLossIncentive4
## 1058 Stat2Data WeightLossIncentive7
## 1059 Stat2Data WordMemory
## 1060 Stat2Data YouthRisk2007
## 1061 Stat2Data YouthRisk2009
## 1062 survival bladder
## 1063 survival cancer
## 1064 survival cgd
## 1065 survival colon
## 1066 survival flchain
## 1067 survival genfan
## 1068 survival heart
## 1069 survival kidney
## 1070 survival leukemia
## 1071 survival logan
## 1072 survival lung
## 1073 survival mgus
## 1074 survival mgus2
## 1075 survival myeloid
## 1076 survival nwtco
## 1077 survival ovarian
## 1078 survival pbc
## 1079 survival rats
## 1080 survival retinopathy
## 1081 survival rhDNase
## 1082 survival stanford2
## 1083 survival tobin
## 1084 survival transplant
## 1085 survival uspop2
## 1086 survival veteran
## 1087 texmex liver
## 1088 texmex nidd
## 1089 texmex portpirie
## 1090 texmex rain
## 1091 texmex summer
## 1092 texmex wavesurge
## 1093 texmex winter
## 1094 vcd Arthritis
## 1095 vcd Baseball
## 1096 vcd BrokenMarriage
## 1097 vcd Bundesliga
## 1098 vcd Bundestag2005
## 1099 vcd Butterfly
## 1100 vcd CoalMiners
## 1101 vcd DanishWelfare
## 1102 vcd Employment
## 1103 vcd Federalist
## 1104 vcd Hitters
## 1105 vcd HorseKicks
## 1106 vcd Hospital
## 1107 vcd JobSatisfaction
## 1108 vcd JointSports
## 1109 vcd Lifeboats
## 1110 vcd MSPatients
## 1111 vcd NonResponse
## 1112 vcd OvaryCancer
## 1113 vcd PreSex
## 1114 vcd Punishment
## 1115 vcd RepVict
## 1116 vcd Rochdale
## 1117 vcd Saxony
## 1118 vcd SexualFun
## 1119 vcd SpaceShuttle
## 1120 vcd Suicide
## 1121 vcd Trucks
## 1122 vcd UKSoccer
## 1123 vcd VisualAcuity
## 1124 vcd VonBort
## 1125 vcd WeldonDice
## 1126 vcd WomenQueue
## 1127 Zelig approval
## 1128 Zelig bivariate
## 1129 Zelig CigarettesSW
## 1130 Zelig coalition
## 1131 Zelig coalition2
## 1132 Zelig eidat
## 1133 Zelig free1
## 1134 Zelig free2
## 1135 Zelig friendship
## 1136 Zelig grunfeld
## 1137 Zelig hoff
## 1138 Zelig homerun
## 1139 Zelig immi1
## 1140 Zelig immi2
## 1141 Zelig immi3
## 1142 Zelig immi4
## 1143 Zelig immi5
## 1144 Zelig immigration
## 1145 Zelig klein
## 1146 Zelig kmenta
## 1147 Zelig macro
## 1148 Zelig MatchIt.url
## 1149 Zelig mexico
## 1150 Zelig mid
## 1151 Zelig newpainters
## 1152 Zelig PErisk
## 1153 Zelig sanction
## 1154 Zelig seatshare
## 1155 Zelig sna.ex
## 1156 Zelig SupremeCourt
## 1157 Zelig swiss
## 1158 Zelig tobin
## 1159 Zelig turnout
## 1160 Zelig voteincome
## 1161 Zelig Weimar
## 1162 Zelig Zelig.url
## Title
## 1 Monthly Excess Returns
## 2 Delay in AIDS Reporting in England and Wales
## 3 Failures of Air-conditioning Equipment
## 4 Failures of Air-conditioning Equipment
## 5 Car Speeding and Warning Signs
## 6 Remission Times for Acute Myelogenous Leukaemia
## 7 Beaver Body Temperature Data
## 8 Population of U.S. Cities
## 9 Spatial Location of Bramble Canes
## 10 Smoking Deaths Among Doctors
## 11 Calcium Uptake Data
## 12 Sugar-cane Disease Data
## 13 Simulated Manufacturing Process Data
## 14 Weight Data for Domestic Cats
## 15 Position of Muscle Caveolae
## 16 CD4 Counts for HIV-Positive Patients
## 17 Nested Bootstrap of cd4 data
## 18 Channing House Data
## 19 Population of U.S. Cities
## 20 Genetic Links to Left-handedness
## 21 Number of Flaws in Cloth
## 22 Carbon Monoxide Transfer
## 23 Dates of Coal Mining Disasters
## 24 Darwin's Plant Height Differences
## 25 Cardiac Data for Domestic Dogs
## 26 Incidence of Down's Syndrome in British Columbia
## 27 Behavioral and Plumage Characteristics of Hybrid Ducks
## 28 Counts of Balsam-fir Seedlings
## 29 Head Dimensions in Brothers
## 30 Acceleration Due to Gravity
## 31 Acceleration Due to Gravity
## 32 Failure Time of PET Film
## 33 Jura Quartzite Azimuths on Islay
## 34 Average Heights of the Rio Negro river at Manaus
## 35 Survival from Malignant Melanoma
## 36 Data from a Simulated Motorcycle Accident
## 37 Neurophysiological Point Process Data
## 38 Toxicity of Nitrofen in Aquatic Systems
## 39 Nodal Involvement in Prostate Cancer
## 40 Nuclear Power Station Construction Data
## 41 Neurotransmission in Guinea Pig Brains
## 42 Animal Survival Times
## 43 Pole Positions of New Caledonian Laterites
## 44 Cancer Remission and Cell Activity
## 45 Water Salinity and River Discharge
## 46 Survival of Rats after Radiation Doses
## 47 Tau Particle Decay Modes
## 48 Tuna Sighting Data
## 49 Urine Analysis Data
## 50 Australian Relative Wool Prices
## 51 Experimenter Expectations
## 52 American Math Society Survey Data
## 53 Moral Integration of American Cities
## 54 U. S. State Public-School Expenditures
## 55 Arrests for Marijuana Possession
## 56 Methods of Teaching Reading Comprehension
## 57 British Election Panel Study
## 58 Canadian Women's Labour-Force Participation
## 59 Exercise Histories of Eating-Disordered and Control Subjects
## 60 Fraudulent Data on IQs of Twins Raised Apart
## 61 Canadian Population Data
## 62 Voting Intentions in the 1988 Chilean Plebiscite
## 63 The 1907 Romanian Peasant Rebellion
## 64 Cowles and Davis's Data on Volunteering
## 65 Self-Reports of Height and Weight
## 66 Davis's Data on Drive for Thinness
## 67 Minnesota Wolf Depredation Data
## 68 Duncan's Occupational Prestige Data
## 69 The 1980 U.S. Census Undercount
## 70 Florida County Voting
## 71 Crowding and Crime in U. S. Metropolitan Areas
## 72 Format Effects on Recall
## 73 Data on Depression
## 74 Refugee Appeals
## 75 Data from the General Social Survey (GSS) from the National Opinion Research Center of the University of Chicago.
## 76 Anonymity and Cooperation
## 77 Canadian Crime-Rates Time Series
## 78 Highway Accidents
## 79 Treatment of Migraine Headaches
## 80 Data on Infant-Mortality
## 81 Cancer drug data use to provide an example of the use of the skew power distributions.
## 82 Contrived Collinear Data
## 83 Canadian Interprovincial Migration Data
## 84 Status, Authoritarianism, and Conformity
## 85 Minneapolis Demographic Data 2015, by Neighborhood
## 86 Minneapolis Police Department 2017 Stop Data
## 87 U.S. Women's Labor-Force Participation
## 88 O'Brien and Kaiser's Repeated-Measures Data
## 89 Interlocking Directorates Among Major Canadian Firms
## 90 Chemical Composition of Pottery
## 91 Prestige of Canadian Occupations
## 92 Four Regression Datasets
## 93 Fertility and Contraception
## 94 Agricultural Production in Mazulu Village
## 95 Salaries for Professors
## 96 Survey of Labour and Income Dynamics
## 97 Soil Compositions of Physical and Chemical Characteristics
## 98 Education and Related Statistics for the U.S. States
## 99 Survival of Passengers on the Titanic
## 100 Transaction data
## 101 National Statistics from the United Nations, Mostly From 2009-2011
## 102 Population of the United States
## 103 Vocabulary and Education
## 104 Weight Loss Data
## 105 Well Switching in Bangladesh
## 106 Canadian Women's Labour-Force Participation
## 107 Post-Coma Recovery of IQ
## 108 Wool data
## 109 World Values Surveys
## 110 European Union Agricultural Workforces
## 111 Attributes of Animals
## 112 Subset of C-horizon of Kola Data
## 113 Flower Characteristics
## 114 Plant Species Traits Data
## 115 Isotopic Composition Plutonium Batches
## 116 Ruspini Data
## 117 Votes for Republican Candidate in Presidential Elections
## 118 Bivariate Data Set with 3 Clusters
## 119 affairs
## 120 azcabgptca
## 121 azdrg112
## 122 azpro
## 123 azprocedure
## 124 badhealth
## 125 fasttrakg
## 126 fishing
## 127 lbw
## 128 lbwgrp
## 129 loomis
## 130 mdvis
## 131 medpar
## 132 nuts
## 133 rwm
## 134 rwm1984
## 135 rwm5yr
## 136 ships
## 137 smoking
## 138 titanic
## 139 titanicgrp
## 140 Aberrant Crypt Foci in Rat Colons
## 141 Australian athletes data set
## 142 Measurements on a Selection of Books
## 143 Anesthetic Effectiveness
## 144 Averages by block of corn yields, for treatment 111 only
## 145 Averages by block of yields for the Antigua Corn data
## 146 Tasting experiment that compared four apple varieties
## 147 Latitudes and longitudes for ten Australian cities
## 148 Population figures for Australian States and Territories
## 149 Biomass Data
## 150 Australian and Related Historical Annual Climate Data, by region
## 151 Australian and Related Historical Annual Climate Data, by region
## 152 Australian and Related Historical Annual Climate Data, by region
## 153 Southern Oscillation Index Data
## 154 Southern Oscillation Index Data
## 155 Boston Housing Data - Corrected
## 156 US Car Price Data
## 157 A Summary of the Cars93 Data set
## 158 Percentage of Sugar in Breakfast Cereal
## 159 Cape Fur Seal Data
## 160 Populations of Major Canadian Cities (1992-96)
## 161 Dose-mortality data, for fumigation of codling moth with methyl bromide
## 162 Occupation and wage profiles of British cotton workers
## 163 Labour Training Evaluation Data
## 164 Labour Training Evaluation Data
## 165 Labour Training Evaluation Data
## 166 Lifespans of UK 1st class cricketers born 1840-1960
## 167 Comparison of cuckoo eggs with host eggs
## 168 Cuckoo Eggs Data
## 169 Dengue prevalence, by administrative region
## 170 Dewpoint Data
## 171 Periods Between Rain Events
## 172 EPICA Dome C Ice Core 800KYr Carbon Dioxide Data
## 173 EPICA Dome C Ice Core 800KYr Temperature Estimates
## 174 Elastic Band Data Replicated
## 175 Elastic Band Data Replicated Again
## 176 Elastic Band Data
## 177 Fossil Fuel Data
## 178 Female Possum Measurements
## 179 Frogs Data
## 180 Frosted Flakes data
## 181 Electrical Resistance of Kiwi Fruit
## 182 Effect of pentazocine on post-operative pain (average VAS scores)
## 183 Seismic Timing Data
## 184 Yearly averages of Great Lake heights: 1918 - 2009
## 185 Alcohol consumption in Australia and New Zealand
## 186 Minor Head Injury (Simulated) Data
## 187 Minor Head Injury (Simulated) Data
## 188 Scottish Hill Races Data
## 189 Scottish Hill Races Data - 2000
## 190 Hawaian island chain hotspot Potassium-Argon ages
## 191 Hawaian island chain hotspot Argon-Argon ages
## 192 Aranda House Prices
## 193 Oxygen uptake versus mechanical power, for humans
## 194 Oxygen uptake versus mechanical power, for humans
## 195 Named US Atlantic Hurricanes
## 196 Blood pressure versus Salt; inter-population data
## 197 Iron Content Measurements
## 198 Canadian Labour Force Summary Data (1995-96)
## 199 Kiwi Shading Data
## 200 Full Leaf Shape Data Set
## 201 Subset of Leaf Shape Data Set
## 202 Leaf and Air Temperature Data
## 203 Full Leaf and Air Temperature Data Set
## 204 Mouse Litters
## 205 Ontario Lottery Data
## 206 Cape Fur Seal Lung Measurements
## 207 The Nine Largest Lakes in Manitoba
## 208 Deaths in London from measles
## 209 Family Medical Expenses
## 210 Mortality Outcomes for Females Suffering Myocardial Infarction
## 211 Darwin's Wild Mignonette Data
## 212 Milk Sweetness Study
## 213 Model Car Data
## 214 WHO Monica Data
## 215 Moths Data
## 216 Airbag and other influences on accident fatalities
## 217 Documentation of names of columns in nass9702cor
## 218 Record times for Northern Ireland mountain running events
## 219 Labour Training Evaluation Data
## 220 Labour Training Evaluation Data
## 221 Labour Training Evaluation Data
## 222 A Subset of the nsw74psid1 Data Set
## 223 Labour Training Evaluation Data
## 224 Labour Training Evaluation Data
## 225 Measurements on 12 books
## 226 Challenger O-rings Data
## 227 Ozone Data
## 228 Heated Elastic Bands
## 229 Possum Measurements
## 230 Possum Sites
## 231 Deaths from various causes, in London from 1629 till 1881, with gaps
## 232 Primate Body and Brain Weights
## 233 Progression of Record times for track races, 1912 - 2008
## 234 Labour Training Evaluation Data
## 235 Labour Training Evaluation Data
## 236 Labour Training Evaluation Data
## 237 Scottish Hill Races Data - 2000
## 238 Rainforest Data
## 239 Rare and Endangered Plant Species
## 240 Genetically Modified and Wild Type Rice Data
## 241 Pacific Rock Art features
## 242 Lawn Roller Data
## 243 School Science Survey Data
## 244 Barley Seeding Rate Data
## 245 Social Support Data
## 246 Measurements on a Selection of Paperback Books
## 247 sorption data set
## 248 Closing Numbers for S and P 500 Index
## 249 Closing Numbers for S and P 500 Index - First 100 Days of 1990
## 250 Spam E-mail Data
## 251 Averages by block of yields for the St. Vincent Corn data
## 252 Sugar Data
## 253 Car Window Tinting Experiment Data
## 254 Root weights of tomato plants exposed to 4 different treatments
## 255 Toy Cars Data
## 256 Averages by block of corn yields, for treatment 111 only
## 257 Video Lottery Terminal Data
## 258 Wages of Lancashire Cotton Factory Workers in 1833
## 259 Deaths from whooping cough, in London
## 260 Record times for track and road races, at August 9th 2006
## 261 Ability and Intelligence Tests
## 262 Passenger Miles on Commercial US Airlines, 1937-1960
## 263 Monthly Airline Passenger Numbers 1949-1960
## 264 New York Air Quality Measurements
## 265 Anscombe's Quartet of 'Identical' Simple Linear Regressions
## 266 The Joyner-Boore Attenuation Data
## 267 The Chatterjee-Price Attitude Data
## 268 Quarterly Time Series of the Number of Australian Residents
## 269 Sales Data with Leading Indicator
## 270 Biochemical Oxygen Demand
## 271 Speed and Stopping Distances of Cars
## 272 Weight versus age of chicks on different diets
## 273 Chicken Weights by Feed Type
## 274 Mauna Loa Atmospheric CO2 Concentration
## 275 Carbon Dioxide Uptake in Grass Plants
## 276 Student's 3000 Criminals Data
## 277 Yearly Numbers of Important Discoveries
## 278 Elisa assay of DNase
## 279 Smoking, Alcohol and (O)esophageal Cancer
## 280 Conversion Rates of Euro Currencies
## 281 Daily Closing Prices of Major European Stock Indices, 1991-1998
## 282 Old Faithful Geyser Data
## 283 Determination of Formaldehyde
## 284 Freeny's Revenue Data
## 285 Hair and Eye Color of Statistics Students
## 286 Harman Example 2.3
## 287 Harman Example 7.4
## 288 Pharmacokinetics of Indomethacin
## 289 Infertility after Spontaneous and Induced Abortion
## 290 Effectiveness of Insect Sprays
## 291 Edgar Anderson's Iris Data
## 292 Edgar Anderson's Iris Data
## 293 Areas of the World's Major Landmasses
## 294 Quarterly Earnings per Johnson & Johnson Share
## 295 Level of Lake Huron 1875-1972
## 296 Luteinizing Hormone in Blood Samples
## 297 Intercountry Life-Cycle Savings Data
## 298 Growth of Loblolly pine trees
## 299 Longley's Economic Regression Data
## 300 Annual Canadian Lynx trappings 1821-1934
## 301 Michelson Speed of Light Data
## 302 Motor Trend Car Road Tests
## 303 Average Yearly Temperatures in New Haven
## 304 Flow of the River Nile
## 305 Average Monthly Temperatures at Nottingham, 1920-1939
## 306 Classical N, P, K Factorial Experiment
## 307 Occupational Status of Fathers and their Sons
## 308 Growth of Orange Trees
## 309 Potency of Orchard Sprays
## 310 Results from an Experiment on Plant Growth
## 311 Annual Precipitation in US Cities
## 312 Quarterly Approval Ratings of US Presidents
## 313 Vapor Pressure of Mercury as a Function of Temperature
## 314 Reaction Velocity of an Enzymatic Reaction
## 315 Locations of Earthquakes off Fiji
## 316 Random Numbers from Congruential Generator RANDU
## 317 Lengths of Major North American Rivers
## 318 Measurements on Petroleum Rock Samples
## 319 Road Casualties in Great Britain 1969-84
## 320 Student's Sleep Data
## 321 Brownlee's Stack Loss Plant Data
## 322 Monthly Sunspot Data, from 1749 to "Present"
## 323 Yearly Sunspot Data, 1700-1988
## 324 Monthly Sunspot Numbers, 1749-1983
## 325 Swiss Fertility and Socioeconomic Indicators (1888) Data
## 326 Pharmacokinetics of Theophylline
## 327 Survival of passengers on the Titanic
## 328 The Effect of Vitamin C on Tooth Growth in Guinea Pigs
## 329 Yearly Treering Data, -6000-1979
## 330 Girth, Height and Volume for Black Cherry Trees
## 331 Student Admissions at UC Berkeley
## 332 Road Casualties in Great Britain 1969-84
## 333 UK Quarterly Gas Consumption
## 334 Accidental Deaths in the US 1973-1978
## 335 Violent Crime Rates by US State
## 336 Lawyers' Ratings of State Judges in the US Superior Court
## 337 Personal Expenditure Data
## 338 Populations Recorded by the US Census
## 339 Death Rates in Virginia (1940)
## 340 Topographic Information on Auckland's Maunga Whau Volcano
## 341 The Number of Breaks in Yarn during Weaving
## 342 Average Heights and Weights for American Women
## 343 The World's Telephones
## 344 Internet Usage per Minute
## 345 Ship Accidents
## 346 Cost for U.S. Airlines
## 347 Air Quality for Californian Metropolitan Areas
## 348 Countries in Banking Crises
## 349 Unemployment of Blue Collar Workers
## 350 Bids Received By U.S. Firms
## 351 Cyber Security Breaches
## 352 Budget Share of Food for Spanish Households
## 353 Budget Shares for Italian Households
## 354 Budget Shares of British Households
## 355 Wages in Belgium
## 356 Stock Market Data
## 357 Stated Preferences for Car Choice
## 358 The California Test Score Data Set
## 359 Choice of Brand for Catsup
## 360 Cigarette Consumption
## 361 The Cigarette Consumption Panel Data Set
## 362 Sales Data of Men's Fashion Stores
## 363 Prices of Personal Computers
## 364 Quarterly Data on Consumption and Expenditure
## 365 Earnings from the Current Population Survey
## 366 Choice of Brand for Crakers
## 367 Growth of CRAN
## 368 Crime in North Carolina
## 369 Daily Returns from the CRSP Database
## 370 Monthly Returns from the CRSP Database
## 371 Pricing the C's of Diamond Stones
## 372 DM Dollar Exchange Rate
## 373 Number of Doctor Visits
## 374 Doctor Visits in Australia
## 375 Contacts With Medical Doctor
## 376 Earnings for Three Age Groups
## 377 Cost Function for Electricity Producers
## 378 Extramarital Affairs Data
## 379 Drunk Driving Laws and Traffic Deaths
## 380 Choice of Fishing Mode
## 381 Exchange Rates of US Dollar Against Other Currencies
## 382 Data from the Television Game Show Friend Or Foe ?
## 383 Daily Observations on Exchange Rates of the US Dollar Against Other Currencies
## 384 Gasoline Consumption
## 385 Wage Datas
## 386 Grunfeld Investment Data
## 387 Heating and Cooling System Choice in Newly Built Houses in California
## 388 The Boston HMDA Data Set
## 389 Heating System Choice in California Houses
## 390 Hedonic Prices of Census Tracts in Boston
## 391 Cybersecurity breaches reported to the US Department of Health and Human Services
## 392 Health Insurance and Hours Worked By Wives
## 393 The Boston HMDA Data Set
## 394 Sales Prices of Houses in the City of Windsor
## 395 Housing Starts
## 396 Ice Cream Consumption
## 397 Global Terrorism Database yearly summaries
## 398 Income Inequality in the US
## 399 Seasonally Unadjusted Quarterly Data on Disposable Income and Expenditure
## 400 Monthly Interest Rates
## 401 Economic Journals Dat Set
## 402 Willingness to Pay for the Preservation of the Kakadu National Park
## 403 Choice of Brand for Ketchup
## 404 Klein's Model I
## 405 Wages and Hours Worked
## 406 Belgian Firms
## 407 The Longley Data
## 408 Dollar Sterling Exchange Rate
## 409 Macroeconomic Time Series for the United States
## 410 Wages and Education of Young Males
## 411 Manufacturing Costs
## 412 Level of Calculus Attained for Students Taking Advanced Micro-economics
## 413 The Massachusetts Test Score Data Set
## 414 Structure of Demand for Medical Care
## 415 Production for SIC 33
## 416 Inflation and Interest Rates
## 417 Mode Choice
## 418 Data to Study Travel Mode Choice
## 419 International Expansion of U.S. Mofa's (majority-owned Foreign Affiliates in Fire (finance, Insurance and Real Estate)
## 420 Money, GDP and Interest Rate in Canada
## 421 Macroeconomic Series for the United States
## 422 Money, National Product and Interest Rate
## 423 Labor Supply Data
## 424 Municipal Expenditure Data
## 425 Growth of Disposable Income and Treasury Bill Rate
## 426 Willingness to Pay for the Preservation of the Alentejo Natural Park
## 427 Cost Function for Electricity Producers, 1955
## 428 Global Terrorism Database yearly summaries
## 429 Names with Character Set Problems
## 430 Visits to Physician Office
## 431 Oil Investment
## 432 The Orange Juice Data Set
## 433 Labor Force Participation
## 434 Dynamic Relation Between Patents and R&D
## 435 Patents, R&D and Technological Spillovers for a Panel of Firms
## 436 Price and Earnings Index
## 437 Political knowledge in the US and Europe
## 438 Pound-dollar Exchange Rate
## 439 Exchange Rates and Price Indices for France and Italy
## 440 Returns of Size-based Portfolios
## 441 Us States Production
## 442 Panel Survey of Income Dynamics
## 443 Return to Schooling
## 444 Wages and Schooling
## 445 Solow's Technological Change Data
## 446 Visits to Lake Somerville
## 447 Returns on Standard & Poor's 500 Index
## 448 Effects on Learning of Small Class Sizes
## 449 Strike Duration Data
## 450 Strikes Duration
## 451 Number of Strikes in Us Manufacturing
## 452 The Penn Table
## 453 Interest Rate, GDP and Inflation
## 454 Global Terrorism Database yearly summaries
## 455 Households Tobacco Budget Share
## 456 Stated Preferences for Train Traveling
## 457 Statewide Data on Transportation Equipment Manufacturing
## 458 Evaluating Treatment Effect of Training on Earnings
## 459 Choice of Brand for Tuna
## 460 Unemployment Duration
## 461 Unemployment Duration
## 462 Provision of University Teaching and Research
## 463 Official Secrecy of the United States Government
## 464 US Finance Industry Profits
## 465 US GDP per capita with presidents and wars
## 466 Standard abbreviations for states of the United States
## 467 Number of Words in US Tax Law
## 468 Medical Expenses in Viet-nam (household Level)
## 469 Medical Expenses in Viet-nam (individual Level)
## 470 Panel Datas of Individual Wages
## 471 Wages, Experience and Schooling
## 472 Wife Working Hours
## 473 Yen-dollar Exchange Rate
## 474 Choice of Brand for Yogurts
## 475 Daily Log Returns on BMW Share Price
## 476 Danish Fire Insurance Claims
## 477 The River Nidd Data
## 478 The River Nidd Data
## 479 Daily Log Returns on Siemens Share Price
## 480 SP Data to June 1993
## 481 SP Return Data to October 1987
## 482 Aircraft Crash data
## 483 Historical speed of light measurements
## 484 US fatal road accident data for automobiles, 1998 to 2010
## 485 US fatal road accident data, 2007 and 2008
## 486 US fatal road accident data, 2007 and 2008
## 487 Summary information on records omitted from the 'FARS' dataset
## 488 German credit scoring data
## 489 Global temperature anomalies
## 490 ALDH2 markers and Alcoholism
## 491 APOE/APOC1 markers and Alzheimer's
## 492 Cystic fibrosis data
## 493 Crohn's disease data
## 494 Friedreich Ataxia data
## 495 A case-control data involving four SNPs with missing genotype
## 496 The HLA data
## 497 An example pedigree data
## 498 An example pedigree
## 499 A study of Parkinson's disease and MAO gene
## 500 A pedigree data on 282 animals deriving from two generations
## 501 Example data for ACEnucfam
## 502 A study of Alzheimer's disease with eight SNPs and APOE
## 503 A study of Parkinson's disease and APOE, LRRK2, SNCA makers
## 504 Growth curves of pigs in a 3x3 factorial experiment
## 505 Ordinal Data from Koch
## 506 Ohio Children Wheeze Status
## 507 Clustered Ordinal Respiratory Disorder
## 508 Data from a clinical trial comparing two treatments for a respiratory illness
## 509 Epiliptic Seizures
## 510 Growth of Sitka Spruce Trees
## 511 Log-size of 79 Sitka spruce trees
## 512 Prices of 50,000 round cut diamonds
## 513 US economic time series
## 514 US economic time series
## 515 2d density estimate of Old Faithful data
## 516 'colors()' in Luv space
## 517 Midwest demographics
## 518 Fuel economy data from 1999 and 2008 for 38 popular models of car
## 519 An updated and expanded version of the mammals sleep dataset
## 520 Terms of 11 presidents from Eisenhower to Obama
## 521 Vector field of seal movements
## 522 Housing sales in TX
## 523 Arbuthnot's data on male and female birth ratios in London from 1629-1710.
## 524 La Felicisima Armada
## 525 Bowley's data on values of British and Irish trade, 1855-1899
## 526 Cavendish's Determinations of the Density of the Earth
## 527 Chest measurements of 5738 Scottish Militiamen
## 528 William Farr's Data on Cholera in London, 1849
## 529 Cushny-Peebles Data: Soporific Effects of Scopolamine Derivatives
## 530 Cushny-Peebles Data: Soporific Effects of Scopolamine Derivatives
## 531 Edgeworth's counts of dactyls in Virgil's Aeneid
## 532 Elderton and Pearson's (1910) data on drinking and wages
## 533 Waite's data on Patterns in Fingerprints
## 534 Galton's data on the heights of parents and their children
## 535 Galton's data on the heights of parents and their children, by child
## 536 Data from A.-M. Guerry, "Essay on the Moral Statistics of France"
## 537 Halley's Life Table
## 538 W. Stanley Jevons' data on numerical discrimination
## 539 van Langren's Data on Longitude Distance between Toledo and Rome
## 540 van Langren's Data on Longitude Distance between Toledo and Rome
## 541 Macdonell's Data on Height and Finger Length of Criminals, used by Gosset (1908)
## 542 Macdonell's Data on Height and Finger Length of Criminals, used by Gosset (1908)
## 543 Michelson's Determinations of the Velocity of Light
## 544 Michelson's Determinations of the Velocity of Light
## 545 Data from Minard's famous graphic map of Napoleon's march on Moscow
## 546 Data from Minard's famous graphic map of Napoleon's march on Moscow
## 547 Data from Minard's famous graphic map of Napoleon's march on Moscow
## 548 Florence Nightingale's data on deaths from various causes in the Crimean War
## 549 Latitudes and Longitudes of 39 Points in 11 Old Maps
## 550 Pearson and Lee's data on the heights of parents and children classified by gender
## 551 Polio Field Trials Data
## 552 Parent-Duchatelet's time-series data on the number of prostitutes in Paris
## 553 Trial of the Pyx
## 554 Statistics of Deadly Quarrels
## 555 John Snow's Map and Data on the 1854 London Cholera Outbreak
## 556 John Snow's Map and Data on the 1854 London Cholera Outbreak
## 557 John Snow's Map and Data on the 1854 London Cholera Outbreak
## 558 John Snow's Map and Data on the 1854 London Cholera Outbreak
## 559 John Snow's Map and Data on the 1854 London Cholera Outbreak
## 560 John F. W. Herschel's Data on the Orbit of the Twin Stars gamma _Virginis_
## 561 John F. W. Herschel's Data on the Orbit of the Twin Stars gamma _Virginis_
## 562 Playfair's Data on Wages and the Price of Wheat
## 563 Playfair's Data on Wages and the Price of Wheat
## 564 Student's (1906) Yeast Cell Counts
## 565 Student's (1906) Yeast Cell Counts
## 566 Darwin's Heights of Cross- and Self-fertilized Zea May Pairs
## 567 Total Body Composision Data
## 568 Aspirin Data
## 569 BCG Vaccine Data
## 570 Birth and Death Rates Data
## 571 Bladder Cancer Data
## 572 Beat the Blues Data
## 573 Cloud Seeding Data
## 574 CYG OB1 Star Cluster Data
## 575 Epilepsy Data
## 576 The Forbes 2000 Ranking of the World's Biggest Companies (Year 2004)
## 577 Foster Feeding Experiment
## 578 General Health Questionnaire
## 579 Olympic Heptathlon Seoul 1988
## 580 Prevention of Gastointestinal Damages
## 581 Survival Times after Mastectomy of Breast Cancer Patients
## 582 Meteorological Measurements for 11 Years
## 583 Oral Lesions in Rural India
## 584 Phosphate Level Data
## 585 Piston Rings Failures
## 586 Exoplanets Data
## 587 Blood Screening Data
## 588 Familial Andenomatous Polyposis
## 589 Familial Andenomatous Polyposis
## 590 Romano-British Pottery Data
## 591 Rearrests of Juvenile Felons
## 592 Respiratory Illness Data
## 593 Students Estimates of Lecture Room Width
## 594 Age of Onset of Schizophrenia Data
## 595 Schizophrenia Data
## 596 Days not Spent at School
## 597 Egyptian Skulls
## 598 Nicotine Gum and Smoking Cessation
## 599 Student Risk Taking
## 600 Crowd Baiting Behaviour and Suicides
## 601 Toothpaste Data
## 602 House of Representatives Voting Data
## 603 Mortality and Water Hardness
## 604 Water Voles Data
## 605 Electricity from Wave Power at Sea
## 606 Gain in Weight of Rats
## 607 Womens Role in Society
## 608 Observed genotype frequencies at MN and S loci, for 2 populations
## 609 Mendel's F2 trifactorial data for seed shape (A: round or wrinkled), cotyledon color (B: albumen yellow or green), and seed coat color (C: grey-brown or white)
## 610 Auto Data Set
## 611 The Insurance Company (TIC) Benchmark
## 612 Sales of Child Car Seats
## 613 U.S. News and World Report's College Data
## 614 Credit Card Balance Data
## 615 Credit Card Default Data
## 616 Baseball Data
## 617 NCI 60 Data
## 618 Orange Juice Data
## 619 Portfolio Data
## 620 S&P Stock Market Data
## 621 Mid-Atlantic Wage Data
## 622 Weekly S&P Stock Market Data
## 623 data from Section 1.19
## 624 data from Section 1.9
## 625 data from Exercise 13.1, p418
## 626 data from Exercise 4.7, p122
## 627 data from Exercise 5.8, p147
## 628 data from Section 1.18
## 629 data from Section 1.14
## 630 data from Section 1.3
## 631 data from Exercise 7.7, p223
## 632 data from Section 1.5
## 633 data from Section 1.6
## 634 data from Section 1.16
## 635 data from Section 1.2
## 636 data from Exercise 7.6, p222
## 637 data from Section 1.10
## 638 data from Section 1.4
## 639 Data on 38 individuals using a kidney dialysis machine
## 640 data from Section 1.7
## 641 data from Section 1.8
## 642 data from Exercise 4.4, p120
## 643 data from Section 1.13
## 644 data from Section 1.15
## 645 data from Exercise 7.13, p225
## 646 data from Section 1.12
## 647 data from Exercise 5.6, p146
## 648 data from Section 1.11
## 649 data from Exercise 7.14, p225
## 650 Yield data from a Minnesota barley trial
## 651 Atmospheric environmental conditions in New York City
## 652 Engine exhaust fumes from burning ethanol
## 653 Melanoma skin cancer incidence
## 654 Heights of New York Choral Society singers
## 655 Mortality Rates in US by Cause and Gender
## 656 Mortality Rates in US by Cause and Gender
## 657 Arabidopsis clipping/fertilization data
## 658 Breakage Angle of Chocolate Cakes
## 659 Contagious bovine pleuropneumonia
## 660 Yield of dyestuff by batch
## 661 Yield of dyestuff by batch
## 662 Data on red grouse ticks from Elston et al. 2001
## 663 University Lecture/Instructor Evaluations by Students at ETH
## 664 Paste strength by batch and cask
## 665 Variation in penicillin testing
## 666 Reaction times in a sleep deprivation study
## 667 Verbal Aggression item responses
## 668 Data set for Unstructured Treatment Interruption Study
## 669 Determinations of Nickel Content
## 670 Accidental Deaths in the US 1973-1978
## 671 Australian AIDS Survival Data
## 672 Brain and Body Weights for 28 Species
## 673 Anorexia Data on Weight Change
## 674 Presence of Bacteria after Drug Treatments
## 675 Body Temperature Series of Beaver 1
## 676 Body Temperature Series of Beaver 2
## 677 Biopsy Data on Breast Cancer Patients
## 678 Risk Factors Associated with Low Infant Birth Weight
## 679 Housing Values in Suburbs of Boston
## 680 Data from a cabbage field trial
## 681 Colours of Eyes and Hair of People in Caithness
## 682 Data from 93 Cars on Sale in the USA in 1993
## 683 Anatomical Data from Domestic Cats
## 684 Heat Evolved by Setting Cements
## 685 Copper in Wholemeal Flour
## 686 Co-operative Trial in Analytical Chemistry
## 687 Performance of Computer CPUs
## 688 Morphological Measurements on Leptograpsus Crabs
## 689 Diagnostic Tests on Patients with Cushing's Syndrome
## 690 DDT in Kale
## 691 Monthly Deaths from Lung Diseases in the UK
## 692 Deaths of Car Drivers in Great Britain 1969-84
## 693 Foraging Ecology of Bald Eagles
## 694 Seizure Counts for Epileptics
## 695 Ecological Factors in Farm Management
## 696 Measurements of Forensic Glass Fragments
## 697 Forbes' Data on Boiling Points in the Alps
## 698 Level of GAG in Urine of Children
## 699 Velocities for 82 Galaxies
## 700 Remission Times of Leukaemia Patients
## 701 Rat Genotype Data
## 702 Old Faithful Geyser Data
## 703 Line Transect of Soil in Gilgai Territory
## 704 Record Times in Scottish Hill Races
## 705 Frequency Table from a Copenhagen Housing Conditions Survey
## 706 Yields from a Barley Field Trial
## 707 Numbers of Car Insurance claims
## 708 Survival Times and White Blood Counts for Leukaemia Patients
## 709 Brain and Body Weights for 62 Species of Land Mammals
## 710 Data from a Simulated Motorcycle Accident
## 711 Survival from Malignant Melanoma
## 712 Age of Menarche in Warsaw
## 713 Michelson's Speed of Light Data
## 714 Minnesota High School Graduates of 1938
## 715 Accelerated Life Testing of Motorettes
## 716 Effect of Calcium Chloride on Muscle Contraction in Rat Hearts
## 717 Newcomb's Measurements of the Passage Time of Light
## 718 Eighth-Grade Pupils in the Netherlands
## 719 Classical N, P, K Factorial Experiment
## 720 US Naval Petroleum Reserve No. 1 data
## 721 Data from an Oats Field Trial
## 722 Tests of Auditory Perception in Children with OME
## 723 The Painter's Data of de Piles
## 724 N. L. Prater's Petrol Refinery Data
## 725 Belgium Phone Calls 1950-1973
## 726 Diabetes in Pima Indian Women
## 727 Diabetes in Pima Indian Women
## 728 Diabetes in Pima Indian Women
## 729 Absenteeism from School in Rural New South Wales
## 730 Blood Pressure in Rabbits
## 731 Road Accident Deaths in US States
## 732 Numbers of Rotifers by Fluid Density
## 733 Accelerated Testing of Tyre Rubber
## 734 Ships Damage Data
## 735 Shoe wear data of Box, Hunter and Hunter
## 736 Percentage of Shrimp in Shrimp Cocktail
## 737 Space Shuttle Autolander Problem
## 738 Growth Curves for Sitka Spruce Trees in 1988
## 739 Growth Curves for Sitka Spruce Trees in 1989
## 740 AFM Compositions of Aphyric Skye Lavas
## 741 Snail Mortality Data
## 742 Returns of the Standard and Poors 500
## 743 The Saturated Steam Pressure Data
## 744 The Stormer Viscometer Data
## 745 Student Survey Data
## 746 Synthetic Classification Problem
## 747 Synthetic Classification Problem
## 748 Spatial Topographic Data
## 749 Effect of Swedish Speed Limits on Accidents
## 750 Nutritional and Marketing Information on US Cereals
## 751 The Effect of Punishment Regimes on Crime Rates
## 752 Veteran's Administration Lung Cancer Trial
## 753 Counts of Waders at 15 Sites in South Africa
## 754 House Insulation: Whiteside's Data
## 755 Weight Loss Data from an Obese Patient
## 756 Example Data for the Design Functions
## 757 Example Data for the Crossover Encouragement Design
## 758 Brader, Valentino and Suhay (2008) Framing Experiment Data
## 759 JOBS II data
## 760 School-level data
## 761 Hypothetical student-level data
## 762 Subset of variables from the CHAIN project
## 763 National Longitudinal Survey of Youth Extract
## 764 Alcohol Consumption per Capita
## 765 US Births in 1969 - 1988
## 766 US Births
## 767 US Births in 2015
## 768 US Births in 1978
## 769 Standard Deck of Cards
## 770 CoolingWater
## 771 Countries
## 772 Data from the 1985 Current Population Survey (CPS85)
## 773 Weight of dimes
## 774 Galton's dataset of parent and child heights
## 775 Data from the Child Health and Development Studies
## 776 Goose Permit Study
## 777 Data from a heat exchanger laboratory
## 778 Health Evaluation and Linkage to Primary Care
## 779 Health Evaluation and Linkage to Primary Care
## 780 Health Evaluation and Linkage to Primary Care
## 781 Foot measurements in children
## 782 Marriage records
## 783 Mites and Wilt Disease
## 784 Volume of Users of a Rail Trail
## 785 Volume of Users of a Massachusetts Rail Trail
## 786 Houses in Saratoga County (2006)
## 787 State by State SAT data
## 788 Snowfall data for Grand Rapids, MI
## 789 100 m Swimming World Records
## 790 Cherry Blossom Race
## 791 Utility bills
## 792 Utility bills
## 793 Weather
## 794 Data from the Whickham survey
## 795 Rheumatoid Arthritis Clinical Trial
## 796 Homeless Data
## 797 Cigarette Consumption
## 798 Crime in North Carolina
## 799 Employment and Wages in the United Kingdom
## 800 Gasoline Consumption
## 801 Grunfeld's Investment Data
## 802 Hedonic Prices of Census Tracts in the Boston Area
## 803 Wages and Hours Worked
## 804 Wages and Education of Young Males
## 805 Purchasing Power Parity and other parity relationships
## 806 US States Production
## 807 Production of Rice in Indonesia
## 808 Employment and Wages in Spain
## 809 The Penn World Table, v. 5
## 810 Panel Data of Individual Wages
## 811 Yearly batting records for all major league baseball players
## 812 Monthly ozone measurements over Central America.
## 813 Absentee and Machine Ballots in Pennsylvania State Senate Races
## 814 Applications to a Political Science PhD Program
## 815 Political opinion polls in Australia, 2004-07
## 816 elections to Australian House of Representatives, 1949-2016
## 817 article production by graduate students in biochemistry Ph.D. programs
## 818 California Congressional Districts in 2006
## 819 Batting Averages for 18 major league baseball players, 1970
## 820 U.S. Senate vote on the use of force against Iraq, 2002.
## 821 political parties appearing in the U.S. Congress
## 822 Interviewer ratings of respondent levels of political information
## 823 elections for U.S. President, 1932-2016, by state
## 824 Prussian army horse kick data
## 825 Voter turnout experiment, using Rock The Vote ads
## 826 information about the American states needed for U.S. Congress
## 827 1992 United Kingdom electoral returns
## 828 cross national rates of trade union density
## 829 Reports of voting in the 1992 U.S. Presidential election.
## 830 16 ability items scored as correct or incorrect.
## 831 Two data sets of affect and arousal scores as a function of personality and movie conditions
## 832 Seven data sets showing a bifactor solution.
## 833 Seven data sets showing a bifactor solution.
## 834 Seven data sets showing a bifactor solution.
## 835 25 Personality items representing 5 factors
## 836 25 Personality items representing 5 factors
## 837 A 29 x 29 matrix that produces weird factor analytic results
## 838 Bond's Logical Operations Test - BLOT
## 839 11 emotional variables from Burt (1915)
## 840 12 cognitive variables from Cattell (1963)
## 841 Distances between 11 US cities
## 842 Galton's example of the relationship between height and 'cubit' or forearm length
## 843 A data set from Cushny and Peebles (1905) on the effect of three drugs on hours of sleep, used by Student (1908)
## 844 8 cognitive variables used by Dwyer for an example.
## 845 Eysenck Personality Inventory (EPI) data for 3570 participants
## 846 13 personality scales from the Eysenck Personality Inventory and Big 5 inventory
## 847 Eysenck Personality Inventory (EPI) data for 3570 participants
## 848 Eysenck Personality Inventory (EPI) data for 3570 participants
## 849 Galton's Mid parent child height data
## 850 Example data from Gleser, Cronbach and Rajaratnam (1965) to show basic principles of generalizability theory.
## 851 Example data set from Gorsuch (1997) for an example factor extension.
## 852 Five data sets from Harman (1967). 9 cognitive variables from Holzinger and 8 emotional variables from Burt
## 853 Five data sets from Harman (1967). 9 cognitive variables from Holzinger and 8 emotional variables from Burt
## 854 Five data sets from Harman (1967). 9 cognitive variables from Holzinger and 8 emotional variables from Burt
## 855 A data.frame of the Galton (1888) height and cubit data set.
## 856 Seven data sets showing a bifactor solution.
## 857 Seven data sets showing a bifactor solution.
## 858 US family income from US census 2008
## 859 16 multiple choice IQ items
## 860 75 mood items from the Motivational State Questionnaire for 3896 participants
## 861 75 mood items from the Motivational State Questionnaire for 3032 unique participants
## 862 NEO correlation matrix from the NEO_PI_R manual
## 863 Galton's Peas
## 864 Seven data sets showing a bifactor solution.
## 865 State Anxiety data from the PMC lab over multiple occasions.
## 866 State Anxiety data from the PMC lab over multiple occasions.
## 867 3 Measures of ability: SATV, SATQ, ACT
## 868 12 variables created by Schmid and Leiman to show the Schmid-Leiman Transformation
## 869 The Schutz correlation matrix example from Shapiro and ten Berge
## 870 A sample from the SAPA Personality Inventory including an item dictionary and scoring keys.
## 871 A sample from the SAPA Personality Inventory including an item dictionary and scoring keys.
## 872 State Anxiety data from the PMC lab over multiple occasions.
## 873 Data set testing causal direction in presumed media influence
## 874 Seven data sets showing a bifactor solution.
## 875 Seven data sets showing a bifactor solution.
## 876 Seven data sets showing a bifactor solution.
## 877 9 Cognitive variables discussed by Tucker and Lewis (1973)
## 878 An example of the distinction between within group and between group correlations
## 879 Barro Data
## 880 Boscovich Data
## 881 Cobar Ore data
## 882 Engel Data
## 883 Time Series of US Gasoline Prices
## 884 Garland(1983) Data on Running Speed of Mammals
## 885 UIS Drug Treatment study data
## 886 Sensory data from a french fries experiment.
## 887 Demo data describing the Smiths.
## 888 Tipping data
## 889 Aircraft Data
## 890 Air Quality Data
## 891 Alcohol Solubility in Water Data
## 892 Daily Means of NOx (mono-nitrogen oxides) in air
## 893 Brain and Body Weights for 65 Species of Land Animals
## 894 Biomass Tillage Data
## 895 Campbell Bushfire Data
## 896 Insect Damages on Carrots
## 897 Cloud point of a Liquid
## 898 Coleman Data Set
## 899 Condroz Data
## 900 Crohn's Disease Adverse Events Data
## 901 Cushny and Peebles Prolongation of Sleep Data
## 902 Delivery Time Data
## 903 Education Expenditure Data
## 904 Epilepsy Attacks Data Set
## 905 Example Data of Antille and May - for Simple Regression
## 906 Food Stamp Program Participation
## 907 Hawkins, Bradu, Kass's Artificial Data
## 908 Heart Catherization Data
## 909 Waterflow Measurements of Kootenay River in Libby and Newgate
## 910 Lactic Acid Concentration Measurement Data
## 911 Length of Stay Data
## 912 Daudin's Milk Composition Data
## 913 NOx Air Pollution Data
## 914 Pension Funds Data
## 915 Phosphorus Content Data
## 916 Pilot-Plant Data
## 917 Possum Diversity Data
## 918 Pulp Fiber and Paper Data
## 919 Satellite Radar Image Data from near Munich
## 920 Salinity Data
## 921 Siegel's Exact Fit Example Data
## 922 Hertzsprung-Russell Diagram Data of Star Cluster CYG OB1
## 923 Number of International Calls from Belgium
## 924 Toxicity of Carboxylic Acids Data
## 925 Vaso Constriction Skin Data Set
## 926 Wagner's Hannover Employment Growth Data
## 927 Modified Data on Wood Specific Gravity
## 928 Automobile Data from 'Consumer Reports' 1990
## 929 Automobile Data from 'Consumer Reports' 1990
## 930 Automobile Data from 'Consumer Reports' 1990
## 931 Data on Children who have had Corrective Spinal Surgery
## 932 Soldering of Components on Printed-Circuit Boards
## 933 Stage C Prostate Cancer
## 934 Innovation and Institutional Ownership
## 935 US Investment Data
## 936 Petersen's Simulated Data for Assessing Clustered Standard Errors
## 937 US Expenditures for Public Schools
## 938 Bollen's Data on Industrialization and Political Democracy
## 939 Variables from the 1997 Canadian National Election Study
## 940 Klein's Data on the U. S. Economy
## 941 Partly Artificial Data on the U. S. Economy
## 942 Six Mental Tests
## 943 Alfalfa
## 944 ArcheryData
## 945 AutoPollution
## 946 Backpack
## 947 BaseballTimes
## 948 BeeStings
## 949 BirdNest
## 950 Blood1
## 951 Blue Jays
## 952 BritishUnions
## 953 CAFE
## 954 CalciumBP
## 955 CancerSurvival
## 956 Caterpillars
## 957 Cereal
## 958 ChemoTHC
## 959 ChildSpeaks
## 960 Clothing
## 961 Cloud Seeding
## 962 Cloud Seeding 2
## 963 CO2
## 964 Cracker Fiber in Diets
## 965 Cuckoo
## 966 Day1Survey
## 967 Diamonds
## 968 Diamonds2
## 969 Election08
## 970 Ethanol
## 971 FantasyBaseball
## 972 Fertility
## 973 FGByDistance
## 974 Film
## 975 FinalFourIzzo
## 976 FinalFourLong
## 977 FinalFourShort
## 978 Fingers
## 979 FirstYearGPA
## 980 FishEggs
## 981 FlightResponse
## 982 Fluorescence
## 983 FruitFlies
## 984 Goldenrod Galls
## 985 Grocery
## 986 Gunnels
## 987 Hawks
## 988 HawkTail
## 989 HawkTail2
## 990 HearingTest
## 991 HighPeaks
## 992 Hoops
## 993 HorsePrices
## 994 Houses
## 995 ICU
## 996 InfantMortality
## 997 InsuranceVote
## 998 Jurors
## 999 Kids198
## 1000 LeafHoppers
## 1001 Leukemia
## 1002 LongJumpOlympics
## 1003 LostLetter
## 1004 Marathon
## 1005 Markets
## 1006 Math Enrollments
## 1007 Math Placement
## 1008 MedGPA
## 1009 Mental Health Admissions
## 1010 Metabolic Rate of Caterpillars
## 1011 MetroHealth83
## 1012 Milgram
## 1013 MLB2007Standings
## 1014 Moth Eggs
## 1015 NCbirths
## 1016 NFL2007Standings
## 1017 Nursing
## 1018 Olives
## 1019 Orings
## 1020 Overdrawn
## 1021 PalmBeach
## 1022 Pedometer
## 1023 Perch
## 1024 PigFeed
## 1025 Pines
## 1026 Political
## 1027 Pollster08
## 1028 Popcorn
## 1029 PorscheJaguar
## 1030 PorschePrice
## 1031 Pulse
## 1032 Putts1
## 1033 Putts2
## 1034 ReligionGDP
## 1035 Retirement
## 1036 RiverElements
## 1037 River Iron
## 1038 SampleFG
## 1039 Sandwich Ants
## 1040 SAT scores and GPA
## 1041 Sea Slugs
## 1042 Sparrows
## 1043 Species Area
## 1044 Speed
## 1045 Swahili
## 1046 Text Prices
## 1047 Three Cars
## 1048 Tip Joke
## 1049 Titanic
## 1050 TMS
## 1051 LaDainian Tomlinson Rushing Yards
## 1052 TwinsLungs
## 1053 USstamps
## 1054 Volts
## 1055 WalkingBabies
## 1056 WeightLossIncentive
## 1057 WeightLossIncentive4
## 1058 WeightLossIncentive7
## 1059 WordMemory
## 1060 YouthRisk2007
## 1061 YouthRisk2009
## 1062 Bladder Cancer Recurrences
## 1063 NCCTG Lung Cancer Data
## 1064 Chronic Granulotomous Disease data
## 1065 Chemotherapy for Stage B/C colon cancer
## 1066 Assay of serum free light chain for 7874 subjects.
## 1067 Generator fans
## 1068 Stanford Heart Transplant data
## 1069 Kidney catheter data
## 1070 Acute Myelogenous Leukemia survival data
## 1071 Data from the 1972-78 GSS data used by Logan
## 1072 NCCTG Lung Cancer Data
## 1073 Monoclonal gammapothy data
## 1074 Monoclonal gammapothy data
## 1075 Acute myeloid leukemia
## 1076 Data from the National Wilm's Tumor Study
## 1077 Ovarian Cancer Survival Data
## 1078 Mayo Clinic Primary Biliary Cirrhosis Data
## 1079 Rat treatment data from Mantel et al
## 1080 Diabetic Retinopathy
## 1081 rhDNASE data set
## 1082 More Stanford Heart Transplant data
## 1083 Tobin's Tobit data
## 1084 Liver transplant waiting list
## 1085 Projected US Population
## 1086 Veterans' Administration Lung Cancer study
## 1087 Liver related laboratory data
## 1088 Rain, wavesurge, portpirie and nidd datasets.
## 1089 Rain, wavesurge, portpirie and nidd datasets.
## 1090 Rain, wavesurge, portpirie and nidd datasets.
## 1091 Air pollution data, separately for summer and winter months
## 1092 Rain, wavesurge, portpirie and nidd datasets.
## 1093 Air pollution data, separately for summer and winter months
## 1094 Arthritis Treatment Data
## 1095 Baseball Data
## 1096 Broken Marriage Data
## 1097 Ergebnisse der Fussball-Bundesliga
## 1098 Votes in German Bundestag Election 2005
## 1099 Butterfly Species in Malaya
## 1100 Breathlessness and Wheeze in Coal Miners
## 1101 Danish Welfare Study Data
## 1102 Employment Status
## 1103 'May' in Federalist Papers
## 1104 Hitters Data
## 1105 Death by Horse Kicks
## 1106 Hospital data
## 1107 Job Satisfaction Data
## 1108 Opinions About Joint Sports
## 1109 Lifeboats on the Titanic
## 1110 Diagnosis of Multiple Sclerosis
## 1111 Non-Response Survey Data
## 1112 Ovary Cancer Data
## 1113 Pre-marital Sex and Divorce
## 1114 Corporal Punishment Data
## 1115 Repeat Victimization Data
## 1116 Rochdale Data
## 1117 Families in Saxony
## 1118 Sex is Fun
## 1119 Space Shuttle O-ring Failures
## 1120 Suicide Rates in Germany
## 1121 Truck Accidents Data
## 1122 UK Soccer Scores
## 1123 Visual Acuity in Left and Right Eyes
## 1124 Von Bortkiewicz Horse Kicks Data
## 1125 Weldon's Dice Data
## 1126 Women in Queues
## 1127 U.S. Presidential Approval Data
## 1128 Sample data for bivariate probit regression
## 1129 Cigarette Consumption Panel Data
## 1130 Coalition Dissolution in Parliamentary Democracies
## 1131 Coalition Dissolution in Parliamentary Democracies, Modified Version
## 1132 Simulation Data for Ecological Inference
## 1133 Freedom of Speech Data
## 1134 Freedom of Speech Data
## 1135 Simulated Example of Schoolchildren Friendship Network
## 1136 Simulation Data for model Seemingly Unrelated Regression (sur) that corresponds to method SUR of systemfit
## 1137 Social Security Expenditure Data
## 1138 Sample Data on Home Runs Hit By Mark McGwire and Sammy Sosa in 1998.
## 1139 Individual Preferences Over Immigration Policy
## 1140 Individual Preferences Over Immigration Policy
## 1141 Individual Preferences Over Immigration Policy
## 1142 Individual Preferences Over Immigration Policy
## 1143 Individual Preferences Over Immigration Policy
## 1144 Individual Preferences Over Immigration Policy
## 1145 Simulation Data for model Two-Stage Least Square (twosls) that corresponds to method 2SLS of systemfit
## 1146 Simulation Data for model Three-Stage Least Square (threesls) that corresponds to method 3SLS of systemfit
## 1147 Macroeconomic Data
## 1148 Table of links for Zelig
## 1149 Voting Data from the 1988 Mexican Presidental Election
## 1150 Militarized Interstate Disputes
## 1151 The Discretized Painter's Data of de Piles
## 1152 Political Economic Risk Data from 62 Countries in 1987
## 1153 Multilateral Economic Sanctions
## 1154 Left Party Seat Share in 11 OECD Countries
## 1155 Simulated Example of Social Network Data
## 1156 U.S. Supreme Court Vote Matrix
## 1157 Swiss Fertility and Socioeconomic Indicators (1888) Data
## 1158 Tobin's Tobit Data
## 1159 Turnout Data Set from the National Election Survey
## 1160 Sample Turnout and Demographic Data from the 2000 Current Population Survey
## 1161 1932 Weimar election data
## 1162 Table of links for Zelig
## Rows Cols has_logical has_binary has_numeric has_character
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