R Stata - Data and Statistical Services - Princeton University

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R Stata # Descriptive statiscs by groups using --tapply-- mean
R Stata library(car) head(Prestige) hist(Prestige$income) hist(Prestige$income, col="green") with(Prestige, hist(income)) # Histogram of income with a nicer title. with(Prestige, hist(income, breaks="FD", col="green")) # Applying Freedman/Diaconis rule p.120 ("Algorithm that chooses bin widths and locations automatically, based on the sample size and the spread of the data" http://www.mathworks.com/help/toolbox/stats/bquc g6n.html) box() hist(Prestige$income, breaks="FD") # Conditional histograms par(mfrow=c(1, 2)) hist(mydata$SAT[mydata$Gender=="Female"], breaks="FD", main="Female", xlab="SAT",col="green") hist(mydata$SAT[mydata$Gender=="Male"], breaks="FD", main="Male", xlab="SAT", col="green") # Braces indicate a compound command allowing several commands with 'with' command par(mfrow=c(1, 1)) with(Prestige, { hist(income, breaks="FD", freq=FALSE, col="green") lines(density(income), lwd=2) lines(density(income, adjust=0.5),lwd=1) rug(income) }) Histograms hist sat hist sat, normal hist sat, by(gender) 23
Page 1 and 2: Getting Started in R~Stata Notes on
Page 3 and 4: This is the R screen in Multiple-Do
Page 5 and 6: Stata’s screen (10.x version) See
Page 7 and 8: # Select the table from the excel f
Page 9 and 10: # To read SAS XPORT format (*.xpt)
Page 11 and 12: load("mydata.RData") load("mydata.r
Page 13 and 14: R Stata str(mydata) # Provides the
Page 15 and 16: # Use factor() for nominal data R S
Page 17 and 18: library(car) mydata$Age.rec
Page 19 and 20: R Stata install.packages("gmodels")
Page 21: R Stata mean(mydata) # Mean of all
Page 25 and 26: R Stata # Scatterplots. Useful to 1
Page 27 and 28: R Stata scatterplotMatrix(~ prestig
Page 29 and 30: References/Useful links • DSS Onl

R Stata - Data and Statistical Services - Princeton University

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