Question

1. A sample is selected from a population with µ= 50. After a treatment is administered to the individuals in the sample, the mean is found to be M= 55 and the variance is s²= 64.

          a. For a sample of n = 4 scores, conduct a single sample t-test to evaluate the

              significance of the treatment effect and calculate Cohen’s d to measure the size of the

              treatment effect. Use a two-tailed test with α = .05.Show the sampling distribution.(2pts)

          b. For a sample of n = 16 scores, conduct a single sample t-test to evaluate the significance

            of the treatment effect and calculate Cohen’s d to measure the size of the treatment effect.

Use a two-tailed test with α = .05. Show the sampling distribution. (2 pts)

          c. Using symbols, write up your results. Describe how increasing the size of the sample

affects the likelihood of rejecting the null hypothesis and the measure of effect size. (1 pt)

Answer 1

c) a) Result - Fail to reject null hypothesis.

b) Result - Reject null hypothesis.

Size of the sample affect the likelihood of rejecting the null hypothesis . As the sample size increases result changes from " failed to reject null hypothesis " to " reject null hypothesis."

Effect size doesn't affected by sample size it remains same for both the sample sizes. PL??