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: d) Given that the student you selected is a Male, what is the probability he has no major? e) Given that the student you selected has no major, what is the probability the student is male?
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: d) Given that the student you selected is a Male, what is the probability he has no major? e) Given that the student you selected has no major, what is the probability the student is male?
MATLAB: An Introduction with Applications
6th Edition
ISBN:9781119256830
Author:Amos Gilat
Publisher:Amos Gilat
Chapter1: Starting With Matlab
Section: Chapter Questions
Problem 1P
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Question
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:
d) Given that the student you selected is a Male, what is the probability he has no major?
e) Given that the student you selected has no major, what is the probability the student is male?
e) Given that the student you selected has no major, what is the probability the student is male?
| ID | Gender | Major | Employ | Age | MBA_GPA | BS GPA | Hrs_Studying | Works FT |
| 101 | 0 | No Major | Unemployed | 53 | 3.01 | 3.15 | 6 | 0 |
| 102 | 0 | Leadership | Full Time | 30 | 3.3 | 3.35 | 6 | 1 |
| 103 | 0 | No Major | Part Time | 32 | 3.62 | 3.6 | 7 | 0 |
| 104 | 0 | Leadership | Full Time | 42 | 3.21 | 3.4 | 7 | 1 |
| 105 | 0 | Leadership | Full Time | 56 | 3.39 | 3.4 | 7 | 1 |
| 106 | 0 | No Major | Full Time | 46 | 3.65 | 3.8 | 8 | 1 |
| 107 | 0 | Leadership | Full Time | 49 | 3.47 | 3.7 | 8 | 1 |
| 108 | 0 | No Major | Part Time | 32 | 3.44 | 3.6 | 7 | 0 |
| 109 | 0 | No Major | Full Time | 36 | 3.88 | 3.95 | 9 | 1 |
| 110 | 0 | Leadership | Full Time | 42 | 3.83 | 3.95 | 9 | 1 |
| 111 | 0 | No Major | Part Time | 37 | 3.53 | 3.6 | 7 | 0 |
| 112 | 0 | No Major | Full Time | 31 | 3.22 | 3.3 | 6 | 1 |
| 113 | 0 | No Major | Full Time | 31 | 3.56 | 3.8 | 8 | 1 |
| 114 | 0 | No Major | Unemployed | 42 | 3.2 | 3.25 | 6 | 0 |
| 115 | 0 | No Major | Full Time | 39 | 3.17 | 3.3 | 6 | 1 |
| 116 | 0 | No Major | Full Time | 47 | 3.41 | 3.6 | 7 | 1 |
| 117 | 0 | No Major | Part Time | 28 | 3.56 | 3.7 | 8 | 0 |
| 118 | 0 | No Major | Unemployed | 28 | 3.34 | 3.6 | 7 | 0 |
| 119 | 0 | No Major | Full Time | 52 | 3.44 | 3.6 | 7 | 1 |
| 120 | 0 | No Major | Part Time | 35 | 3.76 | 3.8 | 8 | 0 |
| 121 | 0 | Finance | Full Time | 38 | 3.55 | 3.45 | 7 | 1 |
| 122 | 0 | Finance | Full Time | 44 | 3.88 | 3.9 | 8 | 1 |
| 123 | 0 | Finance | Part Time | 38 | 3.31 | 3.45 | 7 | 0 |
| 124 | 0 | Finance | Full Time | 52 | 3.09 | 3.15 | 6 | 1 |
| 125 | 0 | Finance | Unemployed | 53 | 3.82 | 4 | 9 | 0 |
| 126 | 0 | Finance | Part Time | 53 | 3.01 | 3.2 | 6 | 0 |
| 127 | 0 | Finance | Full Time | 31 | 3.66 | 3.85 | 8 | 1 |
| 128 | 0 | Finance | Part Time | 47 | 3.64 | 3.7 | 8 | 0 |
| 129 | 0 | Finance | Full Time | 51 | 3.59 | 3.65 | 7 | 1 |
| 130 | 0 | Finance | Unemployed | 37 | 3.49 | 3.55 | 7 | 0 |
| 131 | 0 | Finance | Part Time | 46 | 3.13 | 3.2 | 6 | 0 |
| 132 | 0 | Finance | Full Time | 48 | 3.83 | 3.9 | 8 | 1 |
| 133 | 0 | Finance | Full Time | 54 | 3.04 | 3.15 | 6 | 1 |
| 134 | 0 | Finance | Full Time | 48 | 3.91 | 4 | 10 | 1 |
| 135 | 0 | Finance | Full Time | 36 | 3.56 | 3.7 | 8 | 1 |
| 136 | 0 | Finance | Unemployed | 39 | 3.96 | 4 | 9 | 0 |
| 137 | 0 | Finance | Full Time | 28 | 3.46 | 3.4 | 7 | 1 |
| 138 | 0 | Finance | Part Time | 45 | 3.22 | 3.15 | 6 | 0 |
| 139 | 0 | Finance | Full Time | 31 | 3.27 | 3.2 | 6 | 1 |
| 140 | 0 | Finance | Full Time | 47 | 3.43 | 3.45 | 7 | 1 |
| 141 | 0 | Finance | Part Time | 35 | 3.85 | 3.95 | 9 | 0 |
| 142 | 0 | Finance | Full Time | 52 | 3.89 | 3.9 | 8 | 1 |
| 143 | 0 | Finance | Part Time | 52 | 3.37 | 3.45 | 7 | 0 |
| 144 | 0 | Finance | Unemployed | 55 | 3.32 | 3.3 | 6 | 0 |
| 145 | 0 | Finance | Full Time | 52 | 3.54 | 3.55 | 7 | 1 |
| 146 | 0 | Finance | Part Time | 46 | 3.8 | 3.9 | 8 | 0 |
| 147 | 0 | Finance | Full Time | 31 | 3.74 | 3.85 | 8 | 1 |
| 148 | 0 | Finance | Full Time | 33 | 3.17 | 3.45 | 7 | 1 |
| 149 | 0 | Finance | Part Time | 45 | 3.27 | 3.55 | 7 | 0 |
| 150 | 0 | Finance | Full Time | 50 | 3.32 | 3.3 | 6 | 1 |
| 151 | 0 | Marketing | Part Time | 33 | 3.56 | 3.45 | 7 | 0 |
| 152 | 0 | Marketing | Full Time | 37 | 3.95 | 4 | 9 | 1 |
| 153 | 0 | Marketing | Unemployed | 33 | 3.56 | 3.75 | 8 | 0 |
| 154 | 0 | Marketing | Full Time | 46 | 3.79 | 3.75 | 8 | 1 |
| 155 | 0 | Marketing | Part Time | 55 | 3.93 | 4 | 9 | 0 |
| 156 | 0 | Marketing | Full Time | 30 | 3.79 | 3.85 | 8 | 1 |
| 157 | 0 | Marketing | Full Time | 51 | 3.71 | 3.85 | 8 | 1 |
| 158 | 0 | Marketing | Part Time | 35 | 3.05 | 3.35 | 6 | 0 |
| 159 | 0 | Marketing | Unemployed | 40 | 3.22 | 3.2 | 6 | 0 |
| 160 | 0 | Marketing | Part Time | 29 | 3.85 | 3.95 | 9 | 0 |
| 161 | 0 | Marketing | Full Time | 52 | 3.82 | 3.95 | 9 | 1 |
| 162 | 0 | Marketing | Full Time | 27 | 3.23 | 3.95 | 9 | 1 |
| 163 | 0 | Marketing | Full Time | 51 | 3.56 | 3.65 | 7 | 1 |
| 164 | 0 | Marketing | Part Time | 56 | 3.53 | 3.65 | 7 | 0 |
| 165 | 0 | Marketing | Full Time | 35 | 3.62 | 4 | 9 | 1 |
| 166 | 0 | Leadership | Full Time | 46 | 3.8 | 3.95 | 9 | 1 |
| 167 | 0 | Leadership | Part Time | 39 | 3.47 | 3.35 | 6 | 0 |
| 168 | 0 | Leadership | Full Time | 31 | 3.64 | 3.65 | 7 | 1 |
| 169 | 0 | Leadership | Full Time | 52 | 3.03 | 3.15 | 5 | 1 |
| 170 | 0 | Leadership | Unemployed | 32 | 3.17 | 3.25 | 6 | 0 |
| 171 | 0 | Leadership | Part Time | 32 | 3.22 | 3.2 | 6 | 0 |
| 172 | 0 | Leadership | Full Time | 44 | 3.92 | 4 | 10 | 1 |
| 173 | 0 | Leadership | Full Time | 43 | 3.82 | 3.95 | 9 | 1 |
| 174 | 0 | Leadership | Part Time | 38 | 3.26 | 3.55 | 7 | 0 |
| 175 | 0 | Leadership | Full Time | 54 | 3.8 | 3.85 | 8 | 1 |
| 176 | 0 | Leadership | Full Time | 27 | 3.2 | 3.2 | 6 | 1 |
| 177 | 0 | Leadership | Part Time | 38 | 3.46 | 3.35 | 6 | 0 |
| 178 | 0 | Leadership | Full Time | 45 | 3.67 | 3.75 | 8 | 1 |
| 179 | 0 | Leadership | Unemployed | 48 | 3.06 | 3.4 | 7 | 0 |
| 180 | 0 | Leadership | Full Time | 43 | 3.66 | 3.85 | 8 | 1 |
| 181 | 0 | Leadership | Full Time | 34 | 3.96 | 4 | 10 | 1 |
| 182 | 0 | Leadership | Full Time | 54 | 3.75 | 3.85 | 8 | 1 |
| 183 | 0 | Leadership | Full Time | 36 | 3.83 | 3.85 | 8 | 1 |
| 184 | 0 | Leadership | Full Time | 45 | 3.22 | 3.2 | 6 | 1 |
| 185 | 0 | Leadership | Unemployed | 28 | 3.36 | 3.35 | 6 | 0 |
| 186 | 0 | Leadership | Full Time | 37 | 3.21 | 3.25 | 6 | 1 |
| 187 | 0 | Leadership | Full Time | 27 | 3.02 | 3.15 | 5 | 1 |
| 188 | 0 | Leadership | Full Time | 31 | 3.99 | 4 | 10 | 1 |
| 189 | 0 | Leadership | Unemployed | 45 | 3.07 | 3.15 | 6 | 0 |
| 190 | 0 | Leadership | Full Time | 48 | 3.65 | 3.65 | 7 | 1 |
| 191 | 0 | Leadership | Full Time | 50 | 3.67 | 3.85 | 8 | 1 |
| 192 | 0 | Leadership | Full Time | 32 | 3.06 | 3.35 | 6 | 1 |
| 193 | 0 | Leadership | Unemployed | 33 | 3.98 | 3.7 | 8 | 0 |
| 194 | 0 | Leadership | Full Time | 49 | 3.93 | 4 | 10 | 1 |
| 195 | 0 | Leadership | Unemployed | 27 | 3.41 | 3.3 | 6 | 0 |
| 196 | 0 | Leadership | Part Time | 28 | 3.43 | 3.5 | 7 | 0 |
| 197 | 0 | Leadership | Full Time | 36 | 3.7 | 3.65 | 7 | 1 |
| 198 | 0 | Leadership | Full Time | 35 | 3.76 | 3.75 | 8 | 1 |
| 199 | 0 | Leadership | Part Time | 47 | 3.9 | 3.9 | 8 | 0 |
| 200 | 0 | Leadership | Full Time | 33 | 3.23 | 3.3 | 6 | 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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