t_Data.xls file was the entire population. We know the mean and standard deviation of student ages to be 42.3 and 8.9, respectively. Using the Normal_ Probability.xls file, compute the percentage of students that are older than 50, younger than 40, between 41 and 46, and oldest 10% are at what age? Then compare to the truth as found in the actual file. ID Gender Major Employ Age MBA_GPA BS GP
t_Data.xls file was the entire population. We know the mean and standard deviation of student ages to be 42.3 and 8.9, respectively. Using the Normal_ Probability.xls file, compute the percentage of students that are older than 50, younger than 40, between 41 and 46, and oldest 10% are at what age? Then compare to the truth as found in the actual file. ID Gender Major Employ Age MBA_GPA BS GP
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.
Let's assume that the Student_Data.xls file was the entire population. We know the mean and standard deviation of student ages to be 42.3 and 8.9, respectively. Using the Normal_ Probability.xls file, compute the percentage of students that are older than 50, younger than 40, between 41 and 46, and oldest 10% are at what age? Then compare to the truth as found in the actual file.
| 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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