Statistical Summaries

Weighted Mean

Unequal Importance

weighted.mean averages values while giving some positions more influence than others.

Program

Play the script to change the final value's weight and watch the average move.

weight_last
weighted_mean.R
Replay: real traced execution (multi-file project)
values <- c(10, 20, 30)
weight_last <- 2
weights <- c(1, 1, weight_last)
average <- weighted.mean(values, weights)
cat(average, "\n", sep = "")

values <- c(10, 20, 30)
weight_last <- 3
weights <- c(1, 1, weight_last)
average <- weighted.mean(values, weights)
cat(average, "\n", sep = "")

values <- c(10, 20, 30)
weight_last <- 4
weights <- c(1, 1, weight_last)
average <- weighted.mean(values, weights)
cat(average, "\n", sep = "")

  1. values ← 10, 20, 30

    1values <- c(10, 20, 30)2weight_last <- 2
    values this step10, 20, 30values

  2. weight_last ← 2

    1values <- c(10, 20, 30)2weight_last <- 23weights <- c(1, 1, weight_last)
    values this step2weight_last

  3. weights ← 1, 1, 2

    2weight_last <- 23weights <- c(1, 1, weight_last)4average <- weighted.mean(values, weights)
    values this step1, 1, 2weights2weight_last

  4. average ← 22.5

    3weights <- c(1, 1, weight_last)4average <- weighted.mean(values, weights)5cat(average, "\n", sep = "")
    values this step22.5average10, 20, 30values1, 1, 2weights

  5. cat(average, " ", sep = "")

    4average <- weighted.mean(values, weights)5cat(average, "\n", sep = "")
    output22.5
    values this step22.5average

  1. values ← 10, 20, 30

    1values <- c(10, 20, 30)2weight_last <- 3
    values this step10, 20, 30values

  2. weight_last ← 3

    1values <- c(10, 20, 30)2weight_last <- 33weights <- c(1, 1, weight_last)
    values this step3weight_last

  3. weights ← 1, 1, 3

    2weight_last <- 33weights <- c(1, 1, weight_last)4average <- weighted.mean(values, weights)
    values this step1, 1, 3weights3weight_last

  4. average ← 24

    3weights <- c(1, 1, weight_last)4average <- weighted.mean(values, weights)5cat(average, "\n", sep = "")
    values this step24average10, 20, 30values1, 1, 3weights

  5. cat(average, " ", sep = "")

    4average <- weighted.mean(values, weights)5cat(average, "\n", sep = "")
    output24
    values this step24average

  1. values ← 10, 20, 30

    1values <- c(10, 20, 30)2weight_last <- 4
    values this step10, 20, 30values

  2. weight_last ← 4

    1values <- c(10, 20, 30)2weight_last <- 43weights <- c(1, 1, weight_last)
    values this step4weight_last

  3. weights ← 1, 1, 4

    2weight_last <- 43weights <- c(1, 1, weight_last)4average <- weighted.mean(values, weights)
    values this step1, 1, 4weights4weight_last

  4. average ← 25

    3weights <- c(1, 1, weight_last)4average <- weighted.mean(values, weights)5cat(average, "\n", sep = "")
    values this step25average10, 20, 30values1, 1, 4weights

  5. cat(average, " ", sep = "")

    4average <- weighted.mean(values, weights)5cat(average, "\n", sep = "")
    output25
    values this step25average
weighted.mean `weighted.mean(values, weights)` scales each value by its weight.
weights A larger weight gives one value more pull on the average.
numeric output `cat` writes the numeric result without R's vector label.