salaries <-c(55, 70, 88, 92, 64, 79, 85, 68, 72, 60, 90, 91, 100, 83, 77)
#central tendency 
mean_salary<-mean(salaries)
median_salary<-median(salaries)
get_mode <-function(v){
    uniq_vals <- unique(v)
    uniq_vals[which.max(tabulate(match(v, uniq_vals)))]
} 
mode_salary<-get_mode(salaries)
vr_salary<-var(salaries)
sd_salary<-sd(salaries)
range_salary<- diff(range(salaries))
iqr_slary<-IQR(salaries)
hist(salaries, main="histogram of employee salaries", xlab="salary(in thousands)", col="lightblue")
boxplot(salaries, main="boxplot of employee salaries", ylab="salary(in thousands)", col="lightgreen")
class_a <-c(78, 82, 88, 95, 80, 72, 68, 85, 90, 91)
class_b <-c(65, 70, 68, 72, 75, 78, 80, 85, 77, 82)
mean_a <-mean(class_a)
median_a <-median(class_a)
sd_a<- sd(class_a)
var_a <- var(class_a)
mean_b <-mean(class_b)
median_b <-median(class_b)
sd_b <-sd(class_b)
var_b <-var(class_b)
hist(class_a, main="histogramof class a scores", xlab="scores",col="orange", 
     xlim=c(60,100))
hist(class_b, main="histogram of class b scores", ylab="scores",col="blue",
     xlim=c(60,100))
product_X<-c(3, 4, 4, 5, 2, 4, 5, 5, 4, 3, 5, 5)
product_Y<-c(2, 3, 3, 4, 2, 3, 4, 3, 2, 3, 4, 4)
mean_X <-mean(product_X)
median_X <-median(product_X)
mode_X <-get_mode(product_X)
sd_X <-sd(product_X)
IQR_X<-IQR(product_X)
mean_Y <-mean(product_Y)
median_Y<-median(product_Y)
mode_Y<-get_mode(product_Y)
sd_Y <-sd(product_Y)
IQR_Y <-IQR(product_Y)
boxplot(product_X, product_Y, names=c("product X", "product Y"),
        col=c("red", "purple"), main="boxplot of customer satisfaction scores")