Group comparison

Group comparison capabilities let you check whether the average of a numeric feature differs between groups, telling you how large the difference is and how confident you can be that it's real. Choose the method that matches your comparison:

• T-test: two groups.
• ANOVA: three or more groups.
• Control comparisons: several groups, each against one shared control.

T-test

The two-sample t-test determines whether the mean of a feature differs between two groups. For three or more groups, use ANOVA instead.

1. Open a table.
2. Run Top Menu > ML > Analyze > Group Comparison > T-test.... A dialog opens.
3. In the dialog, specify:
   • the column defining the two groups (in the Category field)
   • the column with feature values (in the Feature field)
   • the significance level (in the Alpha field)
   • the analysis method (in the Method field): Welch or Student
   • whether to add the results table (the Full report checkbox, on by default)
4. Click Run. You get:
   • a box plot showing the distribution of values by category
   • a results table (when Full report is on) reporting the t-statistic, degrees of freedom, p-value, mean difference with its confidence interval, and effect size (Cohen's d and Hedges' g)

ANOVA

Analysis of variance (ANOVA) determines whether the examined factor has a significant impact on the studied feature.

1. Open a table.
2. Run Top Menu > ML > Analyze > Group Comparison > ANOVA.... A dialog opens.
3. In the dialog, specify:
   • the column with factor values (in the Category field)
   • the column with feature values (in the Feature field)
   • the analysis method (in the Method field): Welch or Fisher
   • the significance level (in the Alpha field)
   • whether to add the results table (the Full report checkbox, on by default)
4. Click Run. You get:
   • a box plot showing the distribution of values by category
   • a results table (when Full report is on) with the ANOVA computations

Control comparisons

Control comparisons test each group against a single control, correcting for the multiple comparisons. Use them in dose-response or toxicology studies, where every treatment is compared with one reference group.

1. Open a table.
2. Run Top Menu > ML > Analyze > Group Comparison > Control Comparisons.... A dialog opens.
3. In the dialog, specify:
   • the column defining the groups (in the Category field)
   • the reference group every other group is compared against (in the Control field)
   • the column with feature values (in the Feature field)
   • the significance level (in the Alpha field)
   • the analysis method (in the Method field): Dunnett or Holm-Welch
   • whether to add the results table (the Full report checkbox, on by default)
4. Click Run. You get:
   • a box plot showing the distribution of values by category
   • a results table (when Full report is on) with one row per group compared against the control

See also:

• Box plot