Bus 308 Week 3 Anova and Paired T-Test

BUS 308 Week 3 ANOVA and Paired T-test

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1Week 3 ANOVA and Paired T-test

At this point we know the following about male and female salaries.
a. Male and female overall average salaries are not equal in the population.
b. Male and female overall average compas are equal in the population, but males are a bit more spread out.
c. The male and female salary range are almost the same, as is their age and service.
d. Average performance ratings per gender are equal.
Let's look at some other factors that might influence pay - education(degree) and performance ratings.

1 Last week, we found that average performance ratings do not differ between males and females in the population.
Now we need to see if they differ among the grades. Is the average performace rating the same for all grades?
(Assume variances are equal across the grades for this ANOVA.) You can use these columns to place grade Perf Ratings if desired.
A B C D E F
Null Hypothesis:
Alt. Hypothesis:
Place B17 in Outcome range box.

Interpretation:
What is the p-value:
Is P-value < 0.05?
Do we REJ or Not reject the null?
If the null hypothesis was rejected, what is the effect size value (eta squared):
Meaning of effect size measure:

What does that decision mean in terms of our equal pay question:


2 While it appears that average salaries per each grade differ, we need to test this assumption.
Is the average salary the same for each of the grade levels? (Assume equal variance, and use the analysis toolpak function ANOVA.)
Use the input table to the right to list salaries under each grade level.

Null Hypothesis: If desired, place salaries per grade in these columns
Alt. Hypothesis: A B C D E F


Place B55 in Outcome range box.


What is the p-value:
Is P-value < 0.05?
Do you reject or not reject the null hypothesis:
If the null hypothesis was...