1. Create a pivot table of Gender and Major. Then complete the Joint Probability table so you can answer the following: a) What is the probability of randomly choosing a Female?  b) What is the probability of randomly choosing a Male AND Finance major?  c) What is the probability of randomly choosing a Female OR Leadership major?  ID Gender Major Employ Age MBA_GPA BS GPA Hrs_Studying Works FT 1 1 No Major Unemployed 39

MATLAB: An Introduction with Applications
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Author:Amos Gilat
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Use the Student_Data which consists of 200 MBA students at Whatsamattu U. It includes variables regarding their age, gender, major, GPA, Bachelors GPA, course load, English speaking status, family, and weekly hours spent studying.

1. Create a pivot table of Gender and Major. Then complete the Joint Probability table so you can answer the following:


a) What is the probability of randomly choosing a Female? 
b) What is the probability of randomly choosing a Male AND Finance major? 
c) What is the probability of randomly choosing a Female OR Leadership major? 

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
2 1 No Major Full Time 55 3.49 3.45 7 1
3 1 No Major Part Time 43 3.28 3.5 7 0
4 1 No Major Full Time 56 3.25 3.55 7 1
5 1 No Major Full Time 38 3.26 3.3 6 1
6 1 No Major Unemployed 54 2.87 3.05 4 0
7 1 No Major Full Time 30 3.16 3.35 6 1
8 1 No Major Full Time 37 3.4 3.35 6 1
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 1
80 1 Leadership Unemployed 51 3.09 3.25 6 0
81 1 Leadership Full Time 30 3.77 3.95 9 1
82 1 Leadership Full Time 31 3.79 3.8 8 1
83 1 Leadership Full Time 35 3.59 3.6 7 1
84 1 Leadership Full Time 33 3.38 3.5 7 1
85 1 Leadership Full Time 35 3.57 3.5 7 1
86 1 Leadership Full Time 31 2.97 3.1 5 1
87 1 Leadership Full Time 38 3.44 3.65 7 1
88 1 Leadership Part Time 46 3.64 3.55 7 0
89 1 Leadership Full Time 45 3.48 3.4 7 1
90 1 Leadership Full Time 59 2.99 3.1 5 1
91 1 Leadership Full Time 58 3.73 3.8 8 1
92 1 Leadership Full Time 46 2.91 3.05 4 1
93 1 Leadership Full Time 35 3.78 3.95 9 1
94 1 Leadership Part Time 53 3.4 3.4 7 0
95 1 Leadership Full Time 31 3.13 3.15 6 1
96 1 Leadership Full Time 50 3.14 3.25 6 1
97 1 Leadership Full Time 38 3.24 3.3 6 1
98 1 Leadership Full Time 50 3.56 3.5 7 1
99 1 Leadership Full Time 48 3.16 3.25 6 1
100 1 Leadership Full Time 53 3.53 3.55 7

1

Variable descriptions
Gender = 0 (male), 1 (female)
Major = student's major
Age = age of student in years
MBA_GPA = overall GPA in the MBA program
BS_GPA = overall GPA in the BS program
Hrs_Studying = average hours studied per week
Works FT = 0 (No), 1 (Yes)
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