The z-score is a descriptive statistic used to determine the distance from the mean in units of standard deviation.
Z-scores are calculated by subtracting the mean from the values of the variable, then dividing by its standard deviation.
This allows researchers to compare scores on scales with different units (for example, weight in Pounds versus height in Inches).
Although SPSS does not easily provide z-scores in descriptive statistics tables, it is easy to produce and analyze z-scores by converting variables to standardized values.
Z score in SPSS with example
A table of data below contains 15 observations of human heights and weights.
In this tutorial we are going to demonstrate how to create a z-score for the two variables: height and weight.
Step 1: Import data from SPSS
The first step to do is to import our data to SPSS. In this case the data above is saved in an excel file.
Under the "File" menu, select "Open" and then "Data".
In the window that appears we choose the location and the type of file:
We choose “Excel” as file type:
In our case the file is in the "Downloads" folder:
Click on “Open” and the data file will be loaded:
Step 2: Calculate the z-score
Once the data are loaded, we can now calculate the z-score for the two variables.
Click on the "Analyze", select "Descriptive Statistics", and then "Descriptives".
In the "Descriptive" window that appears, move your variables of interest to the "Variable(s)" column. You can select and analyze several variables at once, and these can be moved to the "Variable(s)" column by clicking and dragging or by highlighting the variables of interest and clicking the arrow button.
Select “Save standardized values as variables” and then we click “OK”
On the “Data View”, the two new variables will be recorded as: ZHeightInches and Z WeightPounds.
This dataset is a derivative of “SOCR Data Dinov 020108 HeightsWeights” dataset which can be found online at :
Was this Helpful?