#Employee salaries in thousands
salaries <- c(120,300,70,95,110,67)

#Central Tendency
mean_salary <- mean(salaries)
median_salary <- median(salaries)
mode <- function(v) {
    uniq_vals <- unique(v)
    uniq_vals [which.max(tabulate(match(v,uniq_vals)))]
}
mode_salary <-mode (salaries)

#Dispersion
var_salary <- var(salaries)
sd_salary <- sd(salaries)
range_salary <- diff(range(salaries))
iqr_salary <- IQR(salaries)

#Visualization
hist(salaries, main="Histogram of Employee Salaries", xlab="Salary (in thousands)", col="lightgreen")
boxplot(salaries, main="Boxplot of Employee Salary", ylab="Salary(in thousands)", col="pink")

#Scores for Class A and B 
class_a <- c(20,30,11,25,37,52,21,67)
class_b <- c(67,44,55,33,21,56,86,39)

#Class A Statistics
mean_a <- mean(class_a)
median_a <- median(class_a)
sd_a <- sd(class_a)
var_a <- var(class_a)

#Class B Statistics
mean_b <- mean(class_b)
median_b <- median(class_b)
sd_b <- sd(class_b)
var_b <- var(class_b)

#Visualization
hist(class_a, main="Histogram of Class A Scores", xlab="Scores", col="pink", xlim=c(60,100))
hist(class_b, main="Histogram of Class B Scores", xlab="Scores", col="orange",xlim=c(60,100))