Use a function

linkedin <- c(16, 9, 13, 5, 2, 17, 14)
facebook <- c(17, 7, 5, 16, 8, 13, 14)

# Calculate average number of views and assign the result to avg_li and avg_fb, respectively. 

avg_li <- mean(linkedin)
avg_fb <- mean(facebook)

print(avg_li)

## [1] 10.85714

print(avg_fb)

## [1] 11.42857

linkedin <- c(16, 9, 13, 5, 2, 17, 14)
facebook <- c(17, 7, 5, 16, 8, 13, 14)

# Calculate the mean of the element-wise sum of linkedin and facebook and store the result in a variable avg_sum

sum <- linkedin + facebook
avg_sum <- mean(sum)
print(avg_sum)

## [1] 22.28571

trim_avg <- mean(avg_sum, trim = 0.2)
print(trim_avg)

## [1] 22.28571

sd function

?sd()

## starting httpd help server ... done

Functions inside functions

linkedin <- c(16, 9, 13, 5, NA, 17, 14)
facebook <- c(17, NA, 5, 16, 8, 13, 14)

# Use abs() on linkedin - facebook to get the absolute differences between the daily Linkedin and Facebook profile views. 

abs_li <- abs(linkedin - facebook)
abs_li

## [1]  1 NA  8 11 NA  4  0

# calculate the mean of the absolute difference. Treat the missing data in mean function
abs_li.1 <- mean(abs(linkedin - facebook), na.rm = TRUE)
abs_li.1

## [1] 4.8