Analysis of Variance (ANOVA)

Jay Arthur
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Analysis of variance (ANOVA) can help you determine if two or more samples have the same "mean" or average. This is a form of "hypothesis testing."

The null hypothesis is that the means are equal:

• H₀: Mean1 = Mean2

The alternate hypothesis is that the means are not equal:

• H_a: Mean1 <> Mean2

The goal is to accept or reject the null hypothesis (i.e., the samples have different means) at a certain confidence level (95% or 99%).

Excel and the QI Macros can perform:

• One-Way ANOVA Example - Single factor ANOVA analysis
• Two-Way ANOVA Example - Two-factor ANOVA analysis without replication
• Two-Way ANOVA Example - Two-factor ANOVA analysis with replication

ANOVA Assumptions

ANOVA assumes three things:

• The data is randomly selected.
• The data is normally distributed.
• The populations have equal variances.

Other Statistical Tests in the QI Macros

• data normality test
• test of proportion
• t test in Excel
• f test in Excel

Analysis of Variance is just one of the tools included in the QI Macros for Excel SPC Software for Excel.

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