31. ANOVA

Question 1

What is the purpose of One-Way ANOVA?

Answer 1

To test differences between group means

One-Way ANOVA is used to test hypotheses about differences between three or more means.

Question 2

What is the need for post-hoc analyses following ANOVA?

Answer 2

To identify specific group differences

Post-hoc analyses are necessary because ANOVA does not reveal which population means differ from others.

Question 3

Name two multiple comparison procedures used in post-hoc analyses.

Answer 3

• Tukey’s HSD
• Bonferroni

These procedures help adjust for multiple tests and identify specific differences between group means.

Question 4

What does Two-Way ANOVA analyze?

Answer 4

The effects of two independent variables and their interaction on a dependent variable

Two-Way ANOVA allows for the examination of main effects and interactions.

Question 5

In a One-Way ANOVA, what is the null hypothesis (H0)?

Answer 5

H0: μ1 = μ2 = … = μa

This null hypothesis states that all population means are equal.

Question 6

True or false: One-Way ANOVA reveals which population means differ from each other.

Answer 6

FALSE

One-Way ANOVA only indicates that at least one population mean is different, but does not specify which.

Question 7

What are the two types of variables in ANOVA?

Answer 7

• Between-subject
• Within-subject (repeated measures)

These variables are essential for understanding the structure of the ANOVA analysis.

Question 8

What is an example of a research question suitable for Two-Way ANOVA?

Answer 8

Do diet type and exercise level influence weight loss?

This question examines the main effects and interactions between two independent variables.

Question 9

What are the two factors in the Two-Way ANOVA example regarding weight loss?

Answer 9

• Diet type (low-carb, Mediterranean)
• Exercise level (none, moderate, high)

These factors are combined to analyze their effects on weight loss.

Question 10

What is the alternative hypothesis (Ha) in the Two-Way ANOVA example?

Answer 10

There is a significant main effect of one or both factors, or a significant interaction

This hypothesis suggests that at least one of the factors has an effect on weight loss.