# Hypothesis Testing & Cohen's d

Problem Set 1: Chapter 9, problems 4, 12, 14, 22

4. Explain why t distribution tend to be flatter and more spread out than the normal distribution.

12. Last fall, a sample of n = 36 freshmen was selected to participate in a new 4-hour training program: µ = 74; M = 79.4, s = 18.

a. On the basis of these data, can the college conclude that the students in the new program performed significantly better than the rest of the freshman class? Use a one tailed test with ? = .05

b. Can the college conclude that the students in the new program are significantly different from the rest of the freshman class? Use a two-tailed test with ? = .05

14. In the Preview for this chapter, we discussed a study that examined the effect of eye spot patterns on the behaviour of moth eating birds: µ = 30; M = 37, SS = 288, n = 9.

a. Is this sample sufficient to conclude that the eye-spots have a significant influence on the birds' behaviour? Use a two-tailed test with ? = .05.

b. Compute the estimated Cohen's d to measure the size of the treatment effect.

22. A researcher would like to examine the effects of humidity on eating behaviours. It is known that laboratory rats normally eat an average of µ = 21 grams of food each day. The researcher selects a random sample of n = 16 rats and places them in a controlled atmosphere room in which the relative humidity is maintained to 90%. The daily food consumption scores for the rats are as follows:

14, 18, 21, 15, 18, 18, 21, 18

16, 20, 17, 19, 20, 17, 17, 19

a. Can the researcher conclude that humidity has a significant effect on eating behaviour? Use a two tailed test with a alpha value = .05

b. Compute the estimated d and r2 to measure the size of the treatment effect.

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#### Solution Summary

The solution provides step by step method for the calculation of testing of hypothesis and Cohen's d. Formula for the calculation and Interpretations of the results are also included. Interactive excel sheet is included. The user can edit the inputs and obtain the complete results for a new set of data.