Guide 14 · Group Comparisons

    How to Conduct a MANOVA

    Use a MANOVA when you want to measure the difference in more than two outcomes between more than two groups.

    Step 1: Access the MANOVA Tool

    • Click ANOVA / MANOVA in the sidebar menu.

    Step 2: Configure Your Analysis

    • Choose two or more outcome variables (e.g., Revenue, Performance).
    • Choose the group variable (e.g., Location: urban, suburban, rural).
    • Click Apply variables.
    • Ensure there are no missing or erroneous values in these columns.

    Step 3: Run the MANOVA

    • Click Stat mode to run the MANOVA.
    • See the values of the dependent variables for each group.

    Step 4: Interpret the Results

    • Scroll down to Averisys AI and click Results to review key outputs:
      • Review Wilks’ lambda, F-value, degrees of freedom, and p-value.
    • p-value < 0.05 — statistically significant difference between group means.
    • p-value ≥ 0.05 — no significant difference detected.

    Step 5: Report Your Findings

    • Develop action plans based on insights (e.g., target customers at risk of revenue loss, optimize pricing).
    • Click Reports to see the executive summary.
    • Click Publish this page to share results with stakeholders via a published page.
    • Click Invite Users to invite stakeholders to share results via dashboards.

    Example

    • DV: Revenue, Performance.
    • IV: Location (urban, suburban, rural).
    • Run MANOVA to test if Revenue and Performance differ by location.
    • If F = 822.45, p < 0.001 — Revenue and Performance are significantly different between urban, suburban, and rural locations.

    If something does not work as described

    Screens are updated as the platform changes, so a button may sit in a slightly different place than the wording above suggests. When that happens, the AI assistant inside the platform is the fastest way forward: it can see the page being worked on and answer in context, at any hour. Ask it what a message means, why a file was rejected, or which step comes next.

    Most problems in this part of the workflow come from the data rather than the platform. Column headers that repeat, numbers stored as text, blank rows at the bottom of a file, and inconsistent category labels are the usual causes. Checking those four things resolves the majority of failed uploads and unexpected results before any further troubleshooting is needed.

    For anything that still does not resolve, email support@averisysanalytics.com with the guide title, the step reached, and what appeared instead of the expected result. Including the file name and a screenshot usually means the issue is answered in the first reply. Related instructions are listed in the full platform guide, and common questions are collected in the support FAQ.