Question

Question #1: (25 points) For this question, you will need to create several variables for use in later questions in this exam. Unless otherwise specified, you should provide summary statistics and interpret the mean, median, and range for each newly created variable. You should also comment on the normality (i.e., of the distribution of values) of each new variable. A) (6 points) Create a variable called subuse97 that is the sum of four other variables - cocaine97, drinkalc97, marijuana 97, and smoke97. Do the same for the 2001 (e.g., cocaine01, etc...) versions of each variable, and call the new variable subuse01. B) (7 points) Create a variable called bad_peers that is the sum of the following variables - peers_cutclass, peers_drunk, peers_drugs, peers_gang, and peers_smoke. Create another variable called good_peers that is the sum of the following variables - peers_church, peers_college, peers_sports, and peers_volunteer. C) (5 points) Create squared versions for each of the following variables: age97, arr97, crime97, and varscore97. You do not need to interpret these new variables and the name of each new variable should be suffixed with '_squared D) (7 points) Create logged versions for each of the foi cwing variables: arr01, crime01, grhhinc97, and varscore01. Remember that the log of 0 is undefined. Thes: new variable names should be suffixed with '_logged":
please use language R

Answer 1

1.

n <- 2001 > lhs1 <- paste("cocaine", 1:n, sep="") > lhs2 <- paste("drinkalc", 1:n, sep="") > lhs3 <- paste("marijuna", 1:n, sep="") > lhs4 <- paste("smoke", 1:n ,sep="") > out<-paste("subuse",1:n,sep="") > rhs <-paste(lhs1,lhs2,lhs3,lhs4,sep="+") > output<-paste(paste(out,rhs,sep="<-"),collapse=";")

2. peers_cutclass<-"" > peers_drunk<-"" > peers_drugs<-"" > peers_gang<-"" > bad_peers<-peers_cutclass+peers_drunk+peers_drufd+peers_gang > output<-paste(peers_cutclass,peers_drugs,peers_drunk,peers_gang, sep="+") > peers_church<-"" > peers_college<-"" > peers_sports<-"" > peers_vounteer<-"" > good_peers<-peers_church+peers_college+peers_sports+peers_vounteer 3. age97 = rnorm(100, mean=0, sd=1) arr97 = rnorm(100, mean=0, sd=1) crime97 = rnorm(100, mean=0, sd=1) varscore97 = rnorm(100, mean=0, sd=1) newage97_squared<-age97^2 newarr97_squared<-arr97^2 newcrime97_squared<-crime97^2 newvarscore97_squared<-varscore97^2

> 4. arr1 = rnorm(100,mean=0,sd=1) > crime01 = rnorm(100,mean=0,sd=1) > grhhinc97 = rnorm(100,mean=0,sd=1) > varscore01 = rnorm(100,mean=0,sd=1) > arr1_logged<-log2(arr1)