Purpose: The purpose of the Group Comparison (ANOVA) is to compare the performance of groups using a numeric variable.


Information on ANOVA:


Inputs: 

  1. Data table
  2. Group column - The group column should be a categorical variable, such as Operator
  3. Value column - The value column should be a continuous variable, such as EUR
  4. Checkbox to include or exclude pairwise comparisons.  If the box is not checked, the 'Pairwise comparisons between each group' output table will not be generated


Limitations: 

  • Can only run one group and one value column at a time


Prep:


Steps to Run:

  1. Go to the Tools menu
  2. Select the Data Science option
  3. Select the Group Comparison (ANOVA) option
  4. Enter the data table, the Group column, the Value column and check whether or not to include pairwise comparisons.


Outputs: 

  • If pairwise comparisons are included, there are four outputs
  • Pairwise Comparisons between each Group table
  • ANOVA and Kruskal-Wallis Test for Groups table
  • Group Results table, including normality checks on each group name
  • Box plot visualization


Interpretation: 

  • See video for explanation of how to interpret the values