bus 308 week 3 and 4 problem set
1.Is the average salary the same for each of the grade levels? (Assume equal variance, and use the Analysis ToolPak function ANOVA.) Set up the data input table/range to use as follows: Put all of the salary values for each grade under the appropriate grade label.
A | B | C | D | E | F |
2.The factorial ANOVA with only two variables can be done with the Analysis ToolPak function two-way ANOVA with replication. Set up a data input table like the following:
Grade | Grade | Grade | Grade | Grade | Grade | |
Gender | A | B | C | D | E | F |
M | ||||||
F | ||||||
For each empty cell, randomly pick a male or female salary from each grade. Interpret the results. Are the average salaries for each gender (listed as sample) equal? Are the average salaries for each grade (listed as column) equal?
3.Repeat question 2 for the compa values.
Grade | Grade | Grade | Grade | Grade | Grade | |
Gender | A | B | C | D | E | F |
M | ||||||
F | ||||||
4.Pick any other variable you are interested in and do a simple 2-way ANOVA without replication. Why did you pick this variable and what do the results show?
5.What are your conclusions about salary equity now?
Week 4 problem setLet’s look at some other factors that might influence pay. Complete the problems below and submit your work in an Excel document. Be sure to show all of your work and clearly label all calculations. All statistical calculations will use theEmployee Salary Data Set.
- Is the probability of having a graduate degree independent of the grade the employee is in?
- Construct a 95% confidence interval on the mean service for each gender. Do they intersect?
- Are males and females distributed across grades in a similar pattern?
- Do 95% confidence intervals on the mean length of service for each gender intersect?
- How do you interpret these results in light of our equity question?
-
Rating:
5/
Solution: bus 308 week 3 and 4 problem set