Chapter 13—Introduction to ANOVA

1. Explain why you should use ANOVA instead of several t tests to evaluate mean differences when an experiment consists of three or more treatment conditions.

1. The following data represent the results from an independent-measures experiment comparing three treatment conditions. Use an analysis of variance with α = .05 to determine whether these data are sufficient to conclude that there are significant difference between the treatments.

Formulas & Answers:

1. The following data were obtained in a study using three separate samples to compare three different treatments.

1. Use an analysis of variance with alpha = .05 to determine whether there are any significant differences among the treatments.
2. Compute the value for η ² for these data.

Formulas & Answers:

1. A researcher reports an F-ratio with df=2, 24 for an independent –measures research study.

1. How many treatment conditions were compared in the study?
2. How many subjects participated in the entire study?

1. A developmental psychologist is examining the development of language skills from age 2 to age 5. Four different groups of children are obtained, one for each age, with n = 15 in each group. Each child is given a language skills assessment test. The resulting data were analyzed with an ANOVA to test the mean differences between age groups. The results of the ANOVA are presented in the following table. Fill in all missing values.

Chapter 14—Repeated Measures ANOVA

1. A researcher conducts a repeated measures experiment using a sample of n = 10 subjects to evaluate the differences among three treatment conditions. If the results are examined with an ANOVA, what are the df values for the F ratio?

1. The following data were obtained in a repeated measures study comparing two treatment conditions. Use a repeated-measures ANOVA with α = .05 to determine whether there are any significant mean differences between the two treatments.

1. The following data were obtained from a repeated-measures study comparing three treatment conditions.

Use a repeated-measures ANOVA with α = .05 to determine whether these data are sufficient to demonstrate significant differences between the treatments.

16. A researcher is evaluating the effectiveness of a speed-reading course. A standardized reading test, measuring both speed and comprehension, was given to a sample of n = 15 students before the course started and again at the end of the course. The following table presents the results from the repeated-measures ANOVA. Fill in the missing values in the table. (Hint: Start with the df values.)

1. The following summary table presents the results from a repeated-measures ANOVA comparing three treatment conditions, each with a sample of n = 12 participants. Fill in the missing values in the table. (Hint: Start with the df values).

   Source			SS		df		MS		F
   Between treatments			30		2				F =
   Within treatments					33
   		Between subjects			11
   	Error		55		22		2.50
   Total			155		35

   
   Chapter 15—Two Factor ANOVA (Independent Measures)
2. The structure of a two-factor study can be presented as a matrix, with one factor determining the rows and the second factor determining the columns. With this structure in mind, describe the mean differences that are evaluated by each factor of the three hypothesis tests that make up a two-factor ANOVA.

1. For the following graph:
   1. Is there a main effect for the treatment factor? Explain your answer.
   2. Is there a main effect for the age factor? Explain your answer.
   3. Is there an interaction between age and treatment? Explain your answer.

1. The following results are from an independent-measures, two factor study with n = 10 participants in each treatment condition.

1. Use a two-factor ANOVA with α = .05 to evaluate the main effects and the interaction.
2. Compute η ² to measure the effect size for each of the main effects and the interaction.

1. The following table summarizes the results from a two-factor study with 2 levels of factor A and 3 levels of factor B using a separate sample of n = 8 participants in each treatment condition. Fill in the missing values. ( Hint : Start with the df values.)

This question is #22 from the 7 ^th edition of this book.

Hyperactivity in children usually is treated by counseling, by drugs or by both. The following data are from an experiment designed to evaluate the effectiveness of these different treatments. The dependent variable is a measure of attention span (how long each child was able to concentrate on a specific task.)

1. Use ANOVA with α = .05 to evaluate these data.
2. Do the data indicate that the drug has a significant effect? Does the counseling have an effect? Describe these results in terms of the effectiveness of the drug and counseling and their interaction.

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