1. Create a dataframe called mydata

mydata <- data.frame ( v1 = c(49,80,79,41,41,52,28,8,76,8), v2 = c(95,46,3,100,1,59,65,82,17,20), v3 = c(32,96,48,96,61,54,36,18,73,67), v4 = c(11,56,96,48,47,84,5,84,47,16), v5 = c(21,41,73,47,6,20,69,77,26,79), v6 = c(3,46,90,42,89,48,78,82,16,65), gender = c(“F”,“F”,“M”,“F”,“M”,“M”,“F”,“M”,“M”,“F”), age = c(82,2,64,93,28,28,71,68,46,1) )

2. Create newdata

myvars <-c(“v1”, “v2”, “v3”) newdata <-mydata[myvars] newdata

datakeep <-mydata (sample code to keep mydata)

3. Create and keep newdata1

myvars1 <- names(mydata) %in% c(“v4”,“v5”, “v6”, “gender”, “age”) newdata1 <- mydata[myvars1] newdata1

datakeep <-newdata1

4. Exclude column 3 and 5 from mydata and keep in newdata2

newdata2 <- mydata[c(-3,-5)] newdata2

5. Remove the same columns using NULL value

newdata3 <-mydata newdata3\(v3 <- newdata3\)v5 <- NULL newdata3

6. Data for newdata5 and newdataGA

newdata5 <- mydata[1:5,] newdata5

newdataGA <- mydata[ which(mydata\(gender=="F" & mydata\)age >65),] newdataGA