mean() {base}

mean() function that computes the arithmetic mean.

mean(x, trim = 0, na.rm = FALSE, ...)

The arguments are:

• x: numeric vector
• trim: fraction of observations (0 to 0.5) to be trimmed from each end of x before the mean is computed.
• na.rm: logical value indicating whether NA values should be removed before the computation proceeds.

x = 1:10; x

##  [1]  1  2  3  4  5  6  7  8  9 10

mean(x)  #sum(x)/length(x)

## [1] 5.5

trim: 

It trims a fraction (0 to 0.5) of observations from each end of x before the mean is computed.

y = c(7,8,9,3,4,55,3,4,5,6,2,23,4,5,3,65,5,78,9,9)
mean(y)

## [1] 15.35

sort(y)

##  [1]  2  3  3  3  4  4  4  5  5  5  6  7  8  9  9  9 23 55 65 78

mean(y, trim = 0.1) ; e = sort(y)[-c(1,2,19,20)] ; sum(e)/length(e)

## [1] 9.9375

## [1] 9.9375

mean(y, trim = 0.3) ; f = sort(y)[-c(1:6,15:20)] ; sum(f)/length(f)

## [1] 6.125

## [1] 6.125

# if trim >= to 0.5 it returns the median
mean(y, trim = 0.5) ; d = sort(y)[-c(1:10,10:20)] ; sum(d)/length(d) 

## [1] 5.5

## [1] NaN

mean(y, trim = 0.9)

## [1] 5.5

na.rm:

 na.rm = TRUE removes NA values before computing the mean.

z = c(1,2,3,4,5,NA,NA,23,34,67)
mean(z)

## [1] NA

mean(z, na.rm = TRUE)

## [1] 17.375

plot(sort(y), main = 'mean() function')
abline(v = mean(y), col = 'deeppink')
abline(v = mean(y, trim = 0.1), col = 'orange')
abline(v = mean(y, trim = 0.6), col = 'darkmagenta') #median
text(16.5, 60, "mean(y)", col = 'deeppink') 
text(11.2, 60, "mean(y,\n trim = 0.1)", col = 'orange') 
text(6.9, 60, "mean(y,\n trim = 0.6) \n (median)", col = 'darkmagenta')