Week 2 – Problem Set

Submit your work in an Excel document. See Where Is Help Button in Microsoft Excel 2007, 2010, 2013 and 2016 (Links to an external site.)Load the Analysis ToolPak (Links to an external site.), and Use the Analysis ToolPak to Perform Complex Data Analysis (Links to an external site.) for more information on how to use the required technologies for the course. Be sure to show all of your work and clearly label all calculations.

All statistical calculations will use the data found in the Data tab

Data

IDSalaryCompaMidpointAgePerformance RatingServiceGenderRaiseDegreeGender1GradeDo not manipuilate Data set on this page, copy to another page to make changes
156.50.992573485805.70METhe ongoing question that the weekly assignments will focus on is: Are males and females paid the same for equal work (under the Equal Pay Act)?
226.50.854315280703.90MBNote: to simplfy the analysis, we will assume that jobs within each grade comprise equal work.
334.21.103313075513.61FB
461.31.07657421001605.51METhe column labels in the table mean:
549.41.0304836901605.71MDID – Employee sample numberSalary – Salary in thousands
672.31.0796736701204.51MFAge – Age in yearsPerformance Rating – Appraisal rating (employee evaluation score)
741.51.0374032100815.71FCService – Years of service (rounded)Gender – 0 = male, 1 = female
822.40.976233290915.81FAMidpoint – salary grade midpointRaise – percent of last raise
973.31.094674910010041MFGrade – job/pay gradeDegree (0= BS\BA 1 = MS)
1023.61.024233080714.71FAGender1 (Male or Female)Compa-ratio – salary divided by midpoint
1123.11.00323411001914.81FA
1261.71.0825752952204.50ME
1341.91.0484030100214.70FC
1423.41.01623329012161FA
1522.90.994233280814.91FA
1641.31.032404490405.70MC
1765.71.1535727553131FE
1835.61.1483131801115.60FB
1923.51.023233285104.61MA
2035.41.1413144701614.80FB
2177.31.1536743951306.31MF
2258.31.215484865613.81FD
2322.30.970233665613.30FA
2447.20.984483075913.80FD
2523.91.0412341704040MA
2624.41.059232295216.20FA
2744.21.105403580703.91MC
2876.21.138674495914.40FF
2977.31.154675295505.40MF
3048.91.0184845901804.30MD
3124.41.062232960413.91FA
3227.40.883312595405.60MB
33581.018573590905.51ME
3427.60.890312680204.91MB
3522.40.975232390415.30FA
3622.70.985232775314.30FA
3723.91.037232295216.20FA
3859.51.0435745951104.50ME
3935.11.132312790615.50FB
40251.087232490206.30MA
4140.91.022402580504.30MC
4222.70.9872332100815.71FA
4373.91.1036742952015.50FF
44651.1405745901605.21ME
4552.41.092483695815.21FD
4660.61.0635739752003.91ME
4761.11.072573795505.51ME
4868.71.2065734901115.31FE
49601.0525741952106.60ME
5059.51.0435738801204.60ME

Week2

Week 2: Identifying Significant Differences – part 1
To Ensure full credit for each question, you need to show how you got your results. This involves either showing where the data you used is located
or showing the excel formula in each cell.Be sure to copy the appropriate data columns from the data tab to the right for your use this week.
As with our examination of compa-ratio in the lecture, the first question we have about salary between the genders involves equality – are they the same or different?
What we do, depends upon our findings.
1As with the compa-ratio lecture example, we want to examine salary variation within the groups – are they equal?Use Cell K10 for the Excel test outcome location.
aWhat is the data input ranged used for this question:
bWhich is needed for this question: a one- or two-tail hypothesis statement and test ?
Answer:
Why:
c. Step 1:Ho:
Ha:
Step 2:Significance (Alpha):
Step 3:Test Statistic and test:
Why this test?
Step 4:Decision rule:
Step 5:Conduct the test – place test function in cell k10
Step 6:Conclusion and Interpretation
What is the p-value:
What is your decision: REJ or NOT reject the null?
Why?
What is your conclusion about the variance in the population for male and female salaries?
2Once we know about variance quality, we can move on to means: Are male and female average salaries equal?Use Cell K35 for the Excel test outcome location.
(Regardless of the outcome of the above F-test, assume equal variances for this test.)
aWhat is the data input ranged used for this question:
bDoes this question need a one or two-tail hypothesis statement and test?
Why:
c. Step 1:Ho:
Ha:
Step 2:Significance (Alpha):
Step 3:Test Statistic and test:
Why this test?
Step 4:Decision rule:
Step 5:Conduct the test – place test function in cell K35
Step 6:Conclusion and Interpretation
What is the p-value:
What is your decision: REJ or NOT reject the null?
Why?
What is your conclusion about the means in the population for male and female salaries?
3Education is often a factor in pay differences.
Do employees with an advanced degree (degree = 1) have higher average salaries?Use Cell K60 for the Excel test outcome location.
Note: assume equal variance for the salaries in each degree for this question.
aWhat is the data input ranged used for this question:
bDoes this question need a one or two-tail hypothesis statement and test?
Why:
c. Step 1:Ho:
Ha:
Step 2:Significance (Alpha):
Step 3:Test Statistic and test:
Why this test?
Step 4:Decision rule:
Step 5:Conduct the test – place test function in cell K60
Step 6:Conclusion and Interpretation
What is the p-value:
Is the t value in the t-distribution tail indicated by the arrow in the Ha claim?
What is your decision: REJ or NOT reject the null?
Why?
What is your conclusion about the impact of education on average salaries?
4Considering both the compa-ratio information from the lectures and your salary information, what conclusions can you reach about equal pay for equal work?
Your findings:
The lecture’s related findings:
Overall conclusion:
Why – what statistical results support this conclusion?