Chat with us, powered by LiveChat The battle of the sexes lives on still today. Since admission standards do not address gender whatsoever, there should be an equally diverse group of men and women in school, but do they perfo | EssayAbode

The battle of the sexes lives on still today. Since admission standards do not address gender whatsoever, there should be an equally diverse group of men and women in school, but do they perfo

 

1.The battle of the sexes lives on still today. Since admission standards do not address gender whatsoever, there should be an equally diverse group of men and women in school, but do they perform equally well. Using the sample of 200 students, conduct a hypothesis test for two independent samples to determine if the mean GPA differs for men and women. Use a .05 significance level.

2.Can a student keep up their grade performance at the next level? Is a strong GPA at the Bachelors level a good predictor of a strong GPA at the Masters level, or are GPAs naturally going to decline since graduate school is tougher, or will GPAs automatically be higher in graduate school because of the 3.00 requirement to graduate and the treatment of a C as subpar instead of average? Using the sample of 200 students (in the data file), conduct a hypothesis test for paired samples and test if there is a difference in the mean GPA from the Bachelors to the Masters programs. Use a .05 significance level.

3.Given the reasons why people get their Masters, you surmise that men are more likely to declare a major than women. Using the sample of 200 students (in the data file), conduct a hypothesis test of proportions to determine if the proportion of women with "no major" is greater than the proportion of men with "no major". Use a .05 significance level.

4.You have probably heard that if you want something done, give it to a busy person. So is one's employment status a factor in their academic performance? Using the sample of 200 students (in the data file), conduct a hypothesis test using Analysis of Variance to determine if there is a difference in the mean GPA for those who are unemployed vs. work part-time vs. work full-time.

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ID Gender Major Employ Age MBA_GPA BS GPA Hrs_Studying Works FT
1 1 No Major Unemployed 39 2.82 3.05 3 0 Variable descriptions
2 1 No Major Full Time 55 3.49 3.45 7 1 Gender = 0 (male), 1 (female)
3 1 No Major Part Time 43 3.28 3.5 7 0 Major = student's major
4 1 No Major Full Time 56 3.25 3.55 7 1 Age = age of student in years
5 1 No Major Full Time 38 3.26 3.3 6 1 MBA_GPA = overall GPA in the MBA program
6 1 No Major Unemployed 54 2.87 3.05 4 0 BS_GPA = overall GPA in the BS program
7 1 No Major Full Time 30 3.16 3.35 6 1 Hrs_Studying = average hours studied per week
8 1 No Major Full Time 37 3.4 3.35 6 1 Works FT = 0 (No), 1 (Yes)
9 1 No Major Part Time 38 2.84 3.05 3 0
10 1 No Major Full Time 42 3.72 3.7 7 1
11 1 No Major Part Time 52 3.22 3.5 7 0
12 1 No Major Full Time 35 3.44 3.55 7 1
13 1 No Major Full Time 37 3.65 3.9 8 1
14 1 No Major Full Time 53 3.02 3.3 6 1
15 1 No Major Part Time 51 3.03 3.25 6 0
16 1 No Major Full Time 40 3.8 3.8 8 1
17 1 No Major Full Time 33 3.23 3.5 7 1
18 1 No Major Part Time 53 3.26 3.5 7 0
19 1 No Major Full Time 43 3.53 3.75 8 1
20 1 No Major Unemployed 35 3.75 3.9 8 0
21 1 No Major Full Time 57 3.15 3.2 6 1
22 1 No Major Part Time 32 3.66 3.75 8 0
23 1 No Major Full Time 59 3.36 3.45 7 1
24 1 No Major Full Time 48 3.79 3.85 8 1
25 1 No Major Part Time 34 2.85 3.05 3 0
26 1 No Major Full Time 53 3.74 3.9 8 1
27 1 No Major Part Time 35 3.23 3.25 6 0
28 1 No Major Unemployed 38 3.52 3.7 7 0
29 1 No Major Part Time 37 3.32 3.45 7 0
30 1 No Major Full Time 46 2.89 3.1 4 1
31 1 No Major Full Time 44 2.83 3.05 3 1
32 1 No Major Unemployed 31 2.93 3.1 5 0
33 1 No Major Full Time 51 3.71 3.8 8 1
34 1 No Major Full Time 47 3.47 3.75 8 1
35 1 No Major Part Time 56 3.52 3.65 7 0
36 1 Finance Part Time 42 2.83 3.05 3 0
37 1 Finance Full Time 44 3.64 3.55 7 1
38 1 Finance Unemployed 54 2.96 3.1 4 0
39 1 Finance Full Time 51 3.59 3.8 8 1
40 1 Finance Part Time 42 3.33 3.55 7 0
41 1 Finance Full Time 45 3.38 3.6 7 1
42 1 Finance Full Time 55 3.44 3.35 6 1
43 1 Finance Full Time 47 3.31 3.45 7 1
44 1 Finance Unemployed 43 3.03 3.25 6 0
45 1 Finance Full Time 57 3.26 3.4 7 1
46 1 Finance Full Time 36 3.04 3.25 6 1
47 1 Finance Part Time 58 2.98 3.1 5 0
48 1 Finance Full Time 46 2.8 3.05 2 1
49 1 Finance Full Time 53 3.75 3.75 8 1
50 1 Finance Full Time 59 3.64 3.65 7 1
51 1 Finance Full Time 49 3.65 3.8 8 1
52 1 Finance Full Time 34 3.18 3.3 6 1
53 1 Finance Full Time 46 3.44 3.4 7 1
54 1 Finance Unemployed 46 3.06 3.15 6 0
55 1 Finance Full Time 33 3.51 3.75 8 1
56 1 Finance Part Time 56 3.33 3.4 7 0
57 1 Finance Full Time 39 2.81 3.05 2 1
58 1 Finance Full Time 51 3.64 3.8 8 1
59 1 Finance Part Time 55 3.05 3.4 7 0
60 1 Finance Full Time 38 2.85 3.05 3 1
61 1 Marketing Full Time 33 3.56 3.6 7 1
62 1 Marketing Full Time 34 2.92 3.1 5 1
63 1 Marketing Full Time 31 3.35 3.5 7 1
64 1 Marketing Full Time 37 3.46 3.35 6 1
65 1 Marketing Full Time 46 3.59 3.75 8 1
66 1 Marketing Unemployed 31 3.11 3.2 6 0
67 1 Marketing Full Time 47 3.65 3.7 8 1
68 1 Marketing Part Time 54 3.17 3.5 7 0
69 1 Marketing Full Time 52 2.97 3.1 5 1
70 1 Marketing Part Time 43 3.77 3.9 8 0
71 1 Leadership Full Time 44 3.21 3.2 6 1
72 1 Leadership Part Time 34 3.17 3.15 6 0
73 1 Leadership Full Time 59 3.65 3.65 7 1
74 1 Leadership Full Time 45 2.94 3.1 5 1
75 1 Leadership Full Time 30 3.53 3.7 8 1
76 1 Leadership Full Time 32 3.65 3.6 7 1
77 1 Leadership Full Time 32 3.61 3.7 8 1
78 1 Leadership Full Time 40 3.7 3.9 8 1
79 1 Leadership Full Time 48 2.91 3.1 5