Chapter 7 Standardizing
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.
7.1.1 Example dataset
From this dataset, this example uses variable
7.2 Input: jamovi
7.3 Input: R
This stores the standardized values in a variable called
$xtcUsePillHigh_standardized <- datscale(dat$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
$xtcUsePillHigh_centered <- datscale(dat$xtcUsePillHigh, scale = FALSE);
7.4 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,
DESCRIPTIVES VARIABLES = xtcUsePillHigh /SAVE.
Recoding a variable is not an analysis, and as such, does not produce output. You can inspect the newly created variable to ensure it has been created properly.