B. Given your confidence interval in part A, is there evidence that the mean wee

Question

B. Given your confidence interval in part A, is there evidence that the mean weekly study hours of males and females are different in the population of all Pennsylvania College of Technology students? Explain your reasoning.

C. Compute Cohen’s d as a measure of effect size.

D. Interpret the effect size that you computed in part C.

E. Is there a practically significant difference between the mean weekly study hours of males and females? Explain your reasoning.

F. Is it likely that a Type I error was committed? Why or why not?

Bootstrap Histogram for Study Time by Gender 95% Confidence Interval 5.18293 9.44928 1.62806 120 100 80 > 60 40 20 10 12 Difference in Means

Explanation / Answer

B. The confidence interval does not contain 0, therefore, reject null hypothesis [H0:mufemales-mumale=0 (there is no difference in mean weekly study hours of females and males of Pennsylvania college of Technology students)] and conclude that there is significant difference in mean weekly study hours of males and females of Pennsylvania college of Technology students.

C. Effect size, Cohen's d=xbarfemale-xbarmale)/sqrt s^2p, where, xbar is sample mean, and s^2p is pooled sample standard deviation.

s^2p=(s1^2+s2^2)/2=(225.058+74.6815)/2=149.86975

d=5.27821/sqrt (149.86975/69+149.86975/107)

=2.79

D. According to rule, d>0.8 is considered to have large effect. Thus, the effect size is large.

E. There is statistically significant difference in mean weekly study hours of males and females.

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