Show significances (group comparisons) in tables and bar/column charts

You can display significances in tables, column charts and bar charts.

For a chart, select the test you want under Settings → Significances.

The following tests are currently available

• Chi-square (complement comparisons):
  Compares expected vs. observed frequencies between each individual cell and its complement (all other categories).

• Chi-square (pairwise comparisons):
  Compares expected vs. observed frequencies between cells in a pairwise manner.

• Z-test (proportion comparisons):
  Compares the percentages between cells pairwise for significance

• t-test (independent samples; pairwise):
  Compares means pairwise between two independent groups (e.g. gender) with respect to a dependent variable.

• t-test (repeated measures):
  Compares means pairwise between two measurement points (or conditions) for the same individuals with respect to a dependent variable.

• Chi-square (independence)
  Tests two variables for statistical independence.

• In progress: t-test (dependent samples)
  Compares means pairwise between two ratings (e.g. products) for the same individuals with respect to a dependent variable.

Recommended metrics

• Chi-square tests: absolute values

• Z-test: percent

• t-test: mean

Notes:

• For the t-tests, the dependent variable must be defined as numeric in the codebook!

• For the chi-square tests, the Yates correction can be enabled/disabled in the chart settings.

How significances are displayed (significance levels can be found in the legend):

• Complement comparisons: asterisks indicate whether one group differs from the others. The number of asterisks represents the significance level.

• A letter after a value indicates which comparison group the value is significant against. Each comparison group is assigned a letter (either in the columns or in the labels for the categories). The way the letter is displayed represents the significance level.