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R Examples

Examples you can copy and paste the code from into your R workspace

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Example 1:

Run the lm procedure to compute a regression model predicting miles per gallon (mpg) from engine dispacement (cid) and save the results in a data structure called lm0:

lm0<-lm(mpg ~ cid)

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Example 2: Same as example 1, but we do not necessarily assume that we have "attached" the data frame with the values of the independent and dependent variables (epa in this case):

lm0<-lm(epa$mpg ~ epa$cid)

If you run the first version and get an error message about mpg or cid not found, try the second form, or enter

attach(epa)

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Example 3: Run a two-way ANOVA with interaction predicting mileage (mpg) from city/highway (C.H) and car/truck (car.truck):

First use aov() so we can run Tukey's test as a follow up for individual differences:

lm0<-aov(mpg ~ C.H*car.truck)
drop1(lm0,~.,test="F")
TukeyHSD(lm0)

Next, use lm() so we can get estimates of the differences:

lm0<-lm(mpg ~ C.H*car.truck)
summary(lm0) 
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Example 4: Run a two-way ANOVA with interaction predicting mileage (mpg) from city/highway (C.H) and car/truck (car.truck) adjusting for engine displacement (i.e., using engine displacement (cid) as a covariate).

lm0<-lm(mpg ~ C.H*car.truck+cid)
drop1(lm0,~.,test="F")
summary(lm0) 

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Example 5: Run a multiple regression using rated horsepower (rhp), engine displacement (cid), and vehicle weight (etw) to predict mileage (mpg):

lm0<-lm(mpg ~ rhp+cid+etw)
drop1(lm0,~.,test="F")
summary(lm0) 

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