![]() The Summary table in the top portion displays mean incomes for our six groups. Males have a higher average income, and that effect is consistent (plus or minus random error) across majors. For example, gender’s main effect on average income does not change from one major to another. The main effects are the portion of the relationship between an independent variable and the dependent variable that does not change based on the values of the other variables in the model. Because the interaction effect is not significant, we can focus on only the main effects. On the other hand, the interaction effect is not significant because its p-value (0.151) is greater than our significance level. Note that these p-values are so low that Excel uses scientific notation to represent them. Because the p-values for both Gender and Major are less than our significance level, these factors are statistically significant. Interpreting Excel’s Two-Way ANOVA Resultsįirst, look in the P-value column in the ANOVA Source of Variation table at the bottom of the output. ![]() Change this value only when you have a specific reason for doing so.įor this example, the popup should look like this: Excel uses a default Alpha value of 0.05, which is usually a good value.This represents the number of observations per group. Under Input, select the ranges for all columns of data.From the Data Analysis popup, choose Anova: Two-Factor With Replication. ![]() ![]() Two-way ANOVA determines whether the observed differences between means provide strong enough evidence to conclude that the population means are different. The dollar amount indicates the average income for each group.
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