Psyc 354 Homework 6 Effect Size Assignment Answer Each Quest

Psyc 354homework 6effect Size Assignmentanswer Each Question About Eff

Answer each question about effect size. Remember to show your work. Submit your assignment to Blackboard as a Word document. The questions involve calculating effect sizes based on given means, standard deviations, and projected changes, using Cohen’s effect size conventions for interpretation.

Paper For Above instruction

Effect size is a quantitative measure that describes the magnitude of the difference or relationship in a statistical analysis. It offers a standardized way to interpret the clinical or practical significance of research findings, independent of sample size. The most common measure of effect size in psychology is Cohen’s d, which assesses the difference between two means relative to the pooled standard deviation. Calculating effect sizes allows researchers to contextualize their findings, compare results across studies, and make informed decisions about the impact of interventions.

Question 1: Effect size of the new sales program

The company reports that the mean sales for participants in the program was 29, while the population mean is 25 with a standard deviation of 4. The effect size (Cohen’s d) is calculated as the difference between the two means divided by the population standard deviation:

> d = (M1 - M2) / SD

Substituting values: > d = (29 - 25) / 4 = 4 / 4 = 1.0

This indicates a large effect size, suggesting that the sales program had a substantial impact on sales performance.

Question 2: Effect size of the relaxation program on anxiety levels

The population mean score is 12 with a standard deviation of 2.3. Post-program mean score is 10.2. The effect size is:

> d = (M_post - M_population) / SD = (10.2 - 12) / 2.3 = (-1.8) / 2.3 ≈ -0.78

The negative sign indicates a reduction in anxiety, and the magnitude suggests a medium-to-large effect size, consistent with Cohen’s conventions.

Question 3: Predicted effect size for GRE score increase

The GRE population mean is 462, with a standard deviation of 119. The program aims to increase scores by 25 points. The effect size is based on the projected change:

> d = (Projected increase) / SD = 25 / 119 ≈ 0.21

This effect size is considered small, indicating a modest improvement in GRE scores due to the program.

Question 4: Effect size of reducing aggressive behaviors

The current mean is 14 behaviors/week, with a standard deviation of 3.2. The goal is to reduce this number to 7. The effect size is calculated as:

> d = (M_post - M_current) / SD = (7 - 14) / 3.2 = (-7) / 3.2 ≈ -2.19

This represents a very large effect size, demonstrating a significant anticipated reduction in aggressive behaviors.

Question 5: Effect size of the group therapy on self-destructive behaviors

The pre-treatment mean is 35, with a standard deviation of 4.7. Post-treatment mean is 27. The effect size is:

> d = (M_post - M_pre) / SD = (27 - 35) / 4.7 = (-8) / 4.7 ≈ -1.70

This indicates a large effect, suggesting substantial improvement following the therapy.

Question 6: Cohen’s effect size conventions

• a. 0.15: Small
• b. -0.81: Large
• c. -0.59: Medium to large
• d. 0.32: Small to medium
• e. Not specified, but assuming a value to interpret accordingly.

Regarding the effect size d = -0.67 reported by the counselor, based on Cohen’s conventions:

• Effect size of -0.67 is considered a medium to large effect, leaning towards large.

This suggests the treatment had a considerable impact on reducing depression symptoms.

References

• Cohen, J. (1988). Statistical power analysis for the behavioral sciences (2nd ed.). Routledge.
• Gravetter, F. J., & Wallnau, L. B. (2017). Statistics for the Behavioral Sciences (10th ed.). Cengage Learning.
• Keppel, G., & Wickens, T. D. (2004). Design and analysis: A researcher's handbook (4th ed.). Pearson.
• Hays, W. L. (2016). Statistics (9th ed.). Cengage Learning.
• Field, A. (2013). Discovering statistics using IBM SPSS statistics (4th ed.). Sage Publications.
• Tabachnick, B. G., & Fidell, L. S. (2013). Using Multivariate Statistics (6th ed.). Pearson.
• Ellis, P. D. (2010). The essential guide to effect sizes: Statistical power, meta-analysis, and the interpretation of research results. Cambridge University Press.
• Sullivan, G. M., & Feinn, R. (2012). Using Effect Size—or Why the P Value Is Not Enough. Journal of Graduate Medical Education, 4(3), 279–282.
• Rosenthal, R. (1994). Intervention Studies in the Post-Cohen Age: Effect Sizes and Their Judicious Use. The American Psychologist, 49(5), 359–367.
• Lakens, D. (2013). Calculating and reporting effect sizes to facilitate cumulative science: a practical primer for t-tests and ANOVAs. Frontiers in Psychology, 4, 863.