Question

For each case study, you will be provided a brief overview, the actual problem, and the steps to follow on Minitab. Each case study will require you to follow the five step hypothesis testing process in addition to providing the computer output AND templated results.

Case Study 1: Applying a Completely Randomized Design (Detecting Changes in Salaries)

That the starting salaries of new accounting graduates would differ according to geographic regions of the United States seems logical. A random selection of accounting firms is taken from three geographic regions, and each is asked to state the starting salary for a new accounting graduate who is going to work in auditing. The data obtained follow. Use a one-way ANOVA to analyze these data. Note that the data can be restated to make the computations more reasonable (example: $42,500 = 4.25). Use a 1% level of significance. Discuss the business implications of your findings. Please provide the 5 steps for both the main effect and the post-hoc test (if required), the Minitab output for each hypothesis test, and state the business implication based upon your analysis. You must use Minitab and the 5 step hypothesis testing process.

South                Northeast                      West

40,500              51,000                          45,500

41,500              49,500                          43,500

40,000              49,000                          45,000

41,000              48,000                          46,500

41,500              49,500                          46,000

APA style:

An one way analysis of variance showed that the effect of noise was significant, F(3,27) = 5.94, p = .007. Post hoc analyses using the Tukey post hoc criterion for significance indicated that the average number of errors was significantly lower in the white noise condition (M = 12.4, SD = 2.26) than in the other two noise conditions (traffic and industrial) combined (M = 13.62, SD = 5.56), F(3, 27) = 7.77, p = .042.

Answer 1

The Minitab output is:

The hypothesis being tested is:

H0: µ1 = µ2 = µ3

Ha: Not all means are not equal

The p-value from the output is 0.000.

Since the p-value (0.000) is less than the significance level (0.01), we can reject the null hypothesis.

Therefore, we can conclude that there is a difference between the group means.

There is a significant difference between all the groups from the post hoc results.

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