R Stata - Data and Statistical Services - Princeton University

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# Histograms overlaid hist(mydata$SAT, breaks="FD", col="green") hist(mydata$SAT[mydata$Gender=="Male"], breaks="FD", col="gray", add=TRUE) legend("topright", c("Female","Male"), fill=c("green","gray")) R Stata Histograms hist sat hist sat, normal hist sat, by(gender) 24
R Stata # Scatterplots. Useful to 1) study the mean and variance functions in the regression of y on x p.128; 2)to identify outliers and leverage points. # plot(x,y) plot(mydata$SAT) # Index plot plot(mydata$Age, mydata$SAT) plot(mydata$Age, mydata$SAT, main=“Age/SAT", xlab=“Age", ylab=“SAT", col="red") abline(lm(mydata$SAT~mydata$Age), col="blue") # regression line (y~x) lines(lowess(mydata$Age, mydata$SAT), col="green") # lowess line (x,y) identify(mydata$Age, mydata$SAT, row.names(mydata)) # On row.names to identify. "All data frames have a row names attribute, a character vector of length the number of rows with no duplicates nor missing values." (source link below). # "Use attr(x, "row.names") if you need an integer value.)" http://stat.ethz.ch/R-manual/Rdevel/library/base/html/row.names.html mydata$Names
Page 1 and 2: Getting Started in R~Stata Notes on
Page 3 and 4: This is the R screen in Multiple-Do
Page 5 and 6: Stata’s screen (10.x version) See
Page 7 and 8: # Select the table from the excel f
Page 9 and 10: # To read SAS XPORT format (*.xpt)
Page 11 and 12: load("mydata.RData") load("mydata.r
Page 13 and 14: R Stata str(mydata) # Provides the
Page 15 and 16: # Use factor() for nominal data R S
Page 17 and 18: library(car) mydata$Age.rec
Page 19 and 20: R Stata install.packages("gmodels")
Page 21 and 22: R Stata mean(mydata) # Mean of all
Page 23: R Stata library(car) head(Prestige)
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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