Week 3: Identifying Significant Differences – part 2
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.
1 A good pay program will have different average salaries by grade. Is this the case for our company?
a What is the data input ranged used for this question: Use Cell K08 for the Excel test outcome location.
Note: assume equal variances for each grade, even though this may not be accurate, for purposes of this question.
b. Step 1: Ho:
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 K08
Step 6: Conclusion and Interpretation
What is the p-value:
What is your decision: REJ or NOT reject the null?
What is your conclusion about the means in the population for grade salaries?
2 If the null hypothesis in question 1 was rejected, which pairs of means differ?
(Use the values from the ANOVA table to complete the follow table.)
Groups Compared Mean Diff. T value used +/- Term Low to High Difference Significant? Why?
3 One issue in salary is the grade an employee is in – higher grades have higher salaries.
This suggests that one question to ask is if males and females are distributed in a similar pattern across the salary grades?
a What is the data input ranged used for this question: Use Cell K54 for the Excel test outcome location.
b. Step 1: Ho:
Step 2: Significance (Alpha):
Step 3: Test Statistic and test: Place the actual distribution in the table below.
Why this test? A B C
Step 4: Decision rule: Male
Step 5: Conduct the test – place test function in cell K54 Female
Step 6: Conclusion and Interpretation Place the expected distribution in the table below.
What is the p-value: A B C
What is your decision: REJ or NOT reject the null? Male
What is your conclusion about the means in the population for male and female salaries?
4 What implications do this week’s analysis have for our equal pay question?
Why – what statistical results support this conclusion?
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