Chapter 5 Standardizing

5.1 Intro

Standardizing a variable means subtracting its mean from every data point in the data series, and dividing the resulting numbers by the variable’s standard deviation. The result is a variable with a mean of 0 and a standard deviation of 1.

5.1.1 Example dataset

This example uses the Rosetta Stats example dataset “pp15” (see Chapter 1 for information about the datasets and Chapter 3 for an explanation of how to load datasets).

5.1.2 Variable(s)

From this dataset, this example uses variable xtcUsePillHigh.

5.2 Input: jamovi

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Figure 5.1: A screenshot placeholder

5.3 Input: R

This stores the standardized values in a variable called xtcUsePillHigh_standardized:

dat$xtcUsePillHigh_standardized <-
  scale(dat$xtcUsePillHigh);

In R is also easy to center a variable around its mean (i.e. omit the division by the standard deviation from the standardization procedure). The following command stores the centered values in a variable called xtcUsePillHigh_centered:

dat$xtcUsePillHigh_centered <-
  scale(dat$xtcUsePillHigh, scale = FALSE);

5.4 Input: SPSS

This command orders descriptives, but the /SAVE subcommand also saves the standardized values. These are then given the original variable name prepended by Z, so in this case, ZxtcUsePillHigh:

DESCRIPTIVES VARIABLES = xtcUsePillHigh
 /SAVE.