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Performing a 2-way or higher factorial analysis of variance (ANOVA)

Test if there is a difference between population means when a response variable is classified by two or more categorical variables (factors).

  1. Select a cell in the dataset.
  2. On the Analyse-it ribbon tab, in the Statistical Analyses group, click Fit Model, and then click ANOVA.
    The analysis task pane opens.
  3. In the Y drop-down list, select the response variable.
  4. In the Available variables list, select the factor variables:
    • To select a single variable, click the variable.
    • To select multiple variables, click the first variable then hold down the CTRL key and click each additional variable.
    • To select a range of variables, click the first variable then hold down the SHIFT key and click the last variable in the range.
  5. Click Factorial, and then click Full for a full factorial model, or click the highest order of interaction terms to include in the model.
  6. Optional: To sort the terms by order (that is, all simple terms, all two-way interactions, then all three-way interactions...) rather than in the order the variables were added, click Sort.
  7. Click Calculate.
Related concepts
Effect of model hypothesis test
Effect of terms hypothesis test
Effect means
Related tasks
Performing ANOVA
Plotting main effects and interactions
Comparing effect means
Related reference
Dataset layout
Available in Analyse-it Editions
Standard edition
Method Validation edition
Quality Control & Improvement edition
Ultimate edition

  •  What is Analyse-it?
  •  What's new?
  •  Administrator's Guide
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  •  Statistical Reference Guide
  •  Distribution
  •  Compare groups
  •  Compare pairs
  •  Contingency tables
  •  Correlation and association
  •  Principal component analysis (PCA)
  •  Factor analysis (FA)
  •  Item reliability
  •  Fit model
  •  Linear fit
  •  Simple regression models
  •  Fitting a simple linear regression
  •  Advanced models
  •  Fitting a multiple linear regression
  •  Performing ANOVA
  •  Performing 2-way or higher factorial ANOVA
  •  Performing ANCOVA
  •  Fitting an advanced linear model
  •  Scatter plot
  •  Summary of fit
  •  Parameter estimates
  •  Effect of model hypothesis test
  •  ANOVA table
  •  Predicted against actual Y plot
  •  Lack of Fit
  •  Effect of terms hypothesis test
  •  Effect leverage plot
  •  Effect means
  •  Plotting main effects and interactions
  •  Multiple comparisons
  •  Multiple comparison procedures
  •  Comparing effect means
  •  Residual plot
  •  Residuals - normality
  •  Residuals - independence
  •  Plotting residuals
  •  Outlier and influence plot
  •  Identifying outliers and other influential points
  •  Prediction
  •  Making predictions
  •  Making inverse predictions
  •  Saving variables
  •  Logistic / Probit fit
  •  Study design
  •  Method comparison / Agreement
  •  Measurement systems analysis (MSA)
  •  Reference interval
  •  Diagnostic performance
  •  Survival/Reliability
  •  Control charts
  •  Process capability
  •  Pareto analysis
  •  Study Designs
  •  Bibliography



Version 6.15
Published 18-Apr-2023
statistics software, statistical software for Excel
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