Comparing Column Means

This example uses the data file survey_sample.sav. See the topic Sample Files for more information.

The column means tests are used to determine whether there is a relationship between a categorical variable in the Columns and a continuous variable in the Rows. Moreover, you can use the test results to determine the relative ordering of categories of the categorical variable in terms of the mean value of the continuous variable. For example, you may want to determine whether Hours per day watching TV is related to Get news from newspapers.

1. From the menus, choose:

   Analyze > Tables > Custom Tables...

2. Click Reset to restore the default settings to all tabs.
3. In the table builder, drag and drop Hours per day watching TV from the variable list into the Rows area of the canvas pane.
4. Drag and drop Get news from newspapers from the variable list into the Columns area.
5. Select Hours per day watching TV and click Summary Statistics in the Define group.
6. Select nnnn as the format.
7. Select 2 as the number of decimals to display. Notice that this causes the format to now read nnnn.nn.
8. Click Apply to Selection.
9. In the Custom Tables dialog box, click the Test Statistics tab.
10. Select Compare column means (t-tests).
11. Click OK to create the table and obtain the column means tests.

This table shows the mean Hours per day watching TV for people who do and do not get their news from newspapers. The observed difference in these means suggests that people who do not get their news from newspapers spend approximately 0.18 more hours watching TV than people who do get their news from newspapers. To see whether this difference is due to chance variation, check the column means tests.

The column means test table assigns a letter key to each category of the column variable. For Get news from newspapers, the category No is assigned the letter A, and Yes is assigned the letter B. For each pair of columns, the column means are compared using a t test. Since there are only two columns, only one test is performed. For each significant pair, the key of the category with the smaller mean is placed under the category with larger mean. Since no keys are reported in the cells of the table, this means that the column means are not statistically different.

Significance Results in APA-style Notation

If you do not want the significance results in a separate table, you can choose to display them in the main table. Significance results are identified using an APA-style notation with subscript letters. Complete the previous steps for comparing column means, but make the following change on the Test Statistics tab:

1. In the Identify Significant Differences area, select In the main table using APA-style subscripts.
2. Click OK to create the table and obtain the column means tests using APA-style notation.

The column means test table assigns a subscript letter to the categories of the column variable. For each pair of columns, the column means are compared using a t test. If a pair of values is significantly different, the values have different subscript letters assigned to them. Since there are only two columns, only one test is performed. Because the column means in this example share the same subscript letter, the column means are not statistically different.