Attachments: BUS 308 lst Week 3 Problem Set.xlsx [ Preview Here ]
During this week, we will look at ways of testing multiple (more than two) data samples at the same time.
We will continue to use the data and assignment file that we opened in Week 2, we just move on to the Week 3 tab.
The first question asks us to determine if the average compa-ratio is equal across 10K salary groups (20 – 29K. 30 – 39K, etc.). The second question asks us to identify which of the salary groups have different averages. The final question asks us to interpret the new information presented in the lecture and assignment; how does the new information we analyzed help us answer our equal pay for equal work question.
The data and assignment file can be found in the Course Materials link, at the bottom in the Multi-Media section. If you save the files from last week, you do not need to open them again.
Week 3 ANOVA Three Questions
Remember to show how you got your results in the appropriate cells. For questions using functions, show the input range when asked.
1 One interesting question is are the average compa-ratios equal across salary ranges of 10K each. While compa-ratios remove the impact of grade on salaries, are they different for different pay levels, that is are people at different levels paid differently relative to the midpoint? (Put data values at right.)
What is the data input ranged used for this question:
Step 2: Decision Rule:
Step 3: Statistical test:
Step 4: Conduct the test - place cell b16 in the output location box.
Step 5: Conclusions and Interpretation
What is the p-value?
Is P-value < 0.05?
What is your decision: REJ or NOT reject the null?
If the null hypothesis was rejected, what is the effect size value (eta squared)?
If calculated, what does the effect size value tell us about why the null hypothesis was rejected?
What does that decision mean in terms of our equal pay question?
2 If the null hypothesis in question 1 was rejected, which pairs of means differ? Why?
Groups Compared Diff T +/- Term Low to High Difference Significant? Why?
3 Since compa is already a measure of pay for equal work, do these results impact your conclusion on equal pay for equal work? Why or why not?