This guide contains all of the ASC's statistics resources. If you do not see a topic, suggest it through the suggestion box on the Statistics home page.

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- Learn about the different input parameters needed to determine the minimum sample size for One-Way, Two-Way/Factorial, and Repeated-Measures ANOVA tests using G*Power. Practice conducting each type of a priori (before data collection) analysis.

The ANOVA test family is similar to the T-test family in that we use it to compare groups to determine if any significant differences exist between those groups. The ANOVA is appropriate when you're comparing more than two groups. Here are some examples of what types of research questions and/or hypotheses may indicate an ANOVA is appropriate:

**One-Way ANOVA:**

- RQ: What effect, if any, does grade level have on problem-solving efficiency?
- H0: There is no effect of grade level on problem-solving efficiency.
- Ha: At least two grades have significantly different levels of problem-solving efficiency.

**Two-Way ANOVA:**

- RQ1: What differences in BMI, if any, exist based on alcohol consumption (drinkers vs. non-drinkers)?
- H0: There are no differences in BMI based on alcohol consumption.
- Ha: There are significant differences in BMI based on alcohol consumption.

- RQ2: What differences in BMI, if any, exist based on tobacco consumption (smokers vs. non-smokers)?
- H0: There are no differences in BMI based on tobacco consumption.
- Ha: There are significant differences in BMI based on tobacco consumption.

- RQ3: What interaction, if any, occurs between alcohol consumption (drinkers vs. non-drinkers) and tobacco consumption (smokers vs. non-smokers) in affecting BMI?
- H0: No interaction occurs between alcohol consumption and tobacco consumption in affecting BMI.
- Ha: There is an interaction that occurs between alcohol consumption (drinkers vs. non-drinkers) and tobacco consumption (smokers vs. non-smokers) that significantly affects BMI.

**Repeated Measures ANOVA:**

- RQ: What effect, if any, does the type of chocolate consumed (milk chocolate, dark chocolate, white chocolate) have on test performance?
- H0: Test performance is not affected by the type of chocolate consumed.
- Ha: Test performance is significantly affected by the type of chocolate consumed.

*NOTE: each participant experiences each type of chocolate and provides a test performance score for each.*

See the ANOVA page for additional information.

- Last Updated: Mar 12, 2023 6:02 PM
- URL: https://resources.nu.edu/statsresources
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