interaction01.r

require(MASS)
# Generage fake data for male
data_male <- data.frame(mvrnorm(n=1000,mu=c(2,0),Sigma=rbind(c(1,.8),c(.8,1)),empirical=TRUE ) )
colnames(data_male)<-c('Income','Age')
data_male$Gender = 'Male'
# Generate fake data for female
data_female <- data.frame(mvrnorm(n=1000,mu=c(3,0),Sigma=rbind(c(1,.3),c(.3,1)),empirical=TRUE ))
colnames(data_female) <- c('Income','Age')
data_female$Gender = 'Female'
# Combine data
data <-rbind(data_female,data_male)
data$Gender<-as.factor(data$Gender)

# Check data has correlation and average that was specified
cat('Correlation between Income & Age for Male:',cor(data_male$Income, data_male$Age))
cat('Correlation between Income & Age for Female:',cor(data_female$Income, data_female$Age))
cat('Mean Income for Male:',mean(data_male$Income))
cat('Mean Income for Female:',mean(data_female$Income))