1. Using the Excel Analysis Tool Pak function descriptive statistics, generate and show the descriptive statistics for each appropriate variable in the sample data set.
a. For which variables in the data set does this function not work correctly for? Why?
descriptive analysis is shown in the next sheet.
Gender, Degree, Gender 1 are measures on nominal cale and thus are descriptive stats for these variables does not function properly.
2 Sort the data by Gen or Gen 1 (into males and females) and find the mean and standard deviation for each gender for the following variables:
sal, compa, age, sr and raise.
| |
|
average |
standard deviation |
| sal |
female |
38 |
18.2939 |
| |
male |
52 |
17.77639 |
| compa |
female |
1.06872 |
0.070345 |
| |
male |
1.05624 |
0.083789 |
| age |
female |
32.52 |
6.880649 |
| |
male |
38.92 |
8.3861 |
| sr |
female |
7.92 |
4.906798 |
| |
male |
10 |
6.35741 |
| raise |
female |
4.88 |
0.919239 |
| |
male |
4.996 |
0.82688 |
3 What is the probability for a:
a. Randomly selected person being a male in grade E?
b. Randomly selected male being in grade E?
c. Why are the results different?
part a includes the sample space of all persons while part b includes sample space of males. This differentiates the denominator and hence the answer
4 Find:
a. The z score for each male salary, based on only the male salaries.
b. The z score for each female salary, based on only the female salaries.
c. The z score for each female compa, based on only the female compa values.
d. The z score for each male compa, based on only the male compa values.
e. What do the distributions and spread suggest about male and female salaries?
Why might we want to use compa to measure salaries between males and females?
5 Based on this sample, what conclusions can you make about the issue of male and female pay equality?
Are all of the results consistent with your conclusion? If not, why not?
Attachment:- data.xlsm