Score:
Week 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
<1 point>
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
Null Hypothesis:
Alt. Hypothesis:
Place B17 in Outcome range box.
F
Interpretation:
What is the p-value:
Is P-value < 0.05?
Do we REJ is Not reject the null?
If the null hypothesis was rejected, what or the effect size value
(eta squared):
Meaning of effect size measure:
What does that decision mean in terms of our equal pay question:
2
<1 point>
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:
Alt. Hypothesis:
If desired, place salaries per grade in these columns
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 effect size value
If the null hypothesis was rejected, what is the null hypothesis:
(eta squared):
Meaning of effect size measure:
Interpretation:
<1 point>
3
The table and analysis below demonstrate a 2-way ANOVA with replication. Please interpret the results.
Male
Female
BA
1.017
0.870
1.052
1.175
1.043
1.074
1.020
0.903
0.982
1.086
1.075
1.052
1.096
1.025
1.000
0.956
1.000
1.043
1.043
1.210
1.187
1.043
1.043
1.145
MA
1.157
0.979
1.134
1.149
1.043
1.134
1.000
1.122
0.903
1.052
1.140
1.087
1.050
1.161
1.096
1.000
1.041
1.043
1.119
1.043
1.000
0.956
1.129
1.149
Ho: Average compas by gender are equal
Ha: Average compas by gender are not equal
Ho: Average compas are equal for each degree
Ha: Average compas are not equal for each degree
Ho: Interaction is not significant
Ha: Interaction is significant
Perform analysis:
Anova: Two-Factor With Replication
SUMMARYBA
MA
Total
Male
Count
Sum
Average
Variance
12
12
24
12.349
12.9
25.249
1.02908333
1.075 1.0520417
0.006686447 0.0065198 0.006866
Female
Count
Sum
Average
Variance
12
12
24
12.791
12.787
25.578
1.06591667 1.0655833 1.06575
0.006102447 0.0042128 0.0049334
Total
Count
Sum
Average
Variance
24
24
25.14
25.687
1.0475 1.0702917
0.00647035 0.0051561
ANOVA
Source of Variation
SS
df
MS
F
P-value
F crit
Sample
Columns
Interaction
Within
0.00225502
0.00623
