Employee Salary Data Set

Week 2

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 the Employee Salary Data Set.

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Included in the Week Two tab of the Employee Salary Data Set are 2 one-sample t-tests comparing male and female average salaries to the overall sample mean.

1. Based on our sample, how do you interpret the results and what do these results suggest about the population means for male and female salaries?
2. Based on our sample results, perform a 2-sample t-test to see if the population male and female salaries could be equal to each other.
3. Based on our sample results, can the male and female compas in the population be equal to each other? (Another 2-sample t-test.)
4. What other information would you like to know to answer the question about salary equity between the genders? Why?
5. If the salary and compa mean tests in questions 3 and 4 provide different results about male and female salary equality, which would be more appropriate to use in answering the question about salary equity? Why? What are your conclusions about equal pay at this point?

Attachments:
Week3

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 the Employee Salary Data Set.

1. Based on the sample data, can the average(mean) salary in the population be the same for each of the grade levels? (Assume equal variance, and use the analysis toolpak function ANOVA.) Set up the input table/range to use as follows: Put all of the salary values for each grade under the appropriate grade label.Be sure to include the null and alternate hypothesis along with the statistical test and result.
2. The table and analysis below demonstrate a 2-way ANOVA with replication. Please interpret the results.
3. Using our sample results, can we say that the compa values in the population are equal by grade and/or gender, and are independent of each factor?
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. Using the results for this week, What are your conclusions about gender equal pay for equal work at this point?

week4

Let’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 the Employee Salary Data Set.

1. One question we might have is if the distribution of graduate and undergraduate degrees independent of the grade the employee? (Note: this is the same as asking if the degrees are distributed the same way.) Based on the analysis of our sample data (shown below), what is your answer?
2. Using our sample data, we can construct a 95% confidence interval for the population’s mean salary for each gender. Interpret the results. How do they compare with the findings in the week 2 one sample t-test outcomes (Question 1)?
3. Based on our sample data, can we conclude that males and females are distributed across grades in a similar pattern within the population?
4. Using our sample data, construct a 95% confidence interval for the population’s mean salary difference for each gender. Do they intersect or overlap? How do these results compare to the findings in week 2, question 2?
5. How do you interpret these results in light of our question about equal pay for equal work?