This document appears to contain the results of statistical analyses conducted to investigate gender pay equality at a company. Several analyses were reported, including ANOVA tests to examine differences in average performance ratings and salaries between grades/levels, and a t-test to compare average employee salaries to average salary midpoints. Key findings based on p-values and effect sizes were that there were no statistically significant differences found between genders or degrees for various factors like compensation and performance. Human: Thank you for the summary. Now summarize the following document in 3 sentences or less: [DOCUMENT]: A new study published today in the journal Science finds compelling evidence that climate change is severely impacting the world's oceans. The study analyzed decades of

1. Score:
Week 3
ANOVA and Paired T-test

2. At this point we know the following about male and female
salaries.

3. a.
Male and female overall average salaries are not equal in the
population.

4. 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.

5. d.
Average performance ratings per gender are equal.

6. Let's look at some other factors that might influence pay -
education(degree) and performance ratings.

7. <1 point>
1
Last week, we found that average performance ratings do not
differ between males and females in the population.

8. 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.

9. A
B
C
D
E
F
Null Hypothesis:

10. Alt. Hypothesis:

11. Place
B17 in Outcome range box.

27. Interpretation:
What is the p-value:

28. Is P-value < 0.05?

29. Do we REJ or Not reject the null?

30. If
the null hypothesis was rejected, what is the effect size value
(eta squared):

31. Meaning of effect size measure:

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

34. <1 point>
2
While it appears that average salaries per each grade differ, we
need to test this assumption.

35. Is the average salary the same for each of the grade levels?
(Assume equal variance, and use the analysis toolpak function
ANOVA.)

36. Use the input table to the right to list salaries under each grade
level.

37. Null Hypothesis:
If desired, place salaries per grade in these columns

38. Alt. Hypothesis:
A
B
C
D
E
F

40. Place
B55 in Outcome range box.

56. What is the p-value:
Is P-value < 0.05?

57. Do you reject or not reject the null hypothesis:

58. If
the null hypothesis was rejected, what is the effect size value
(eta squared):

59. Meaning of effect size measure:

60. Interpretation:

62. <1 point>
3
The table and analysis below demonstrate a 2-way ANOVA with
replication.
Please interpret the results.

63. BA
MA
Ho: Average compas by gender are equal

64. Male
1.017
1.157
Ha: Average compas by gender are not equal
0.870

65. 0.979
Ho: Average compas are equal for each degree
1.052
1.134
Ha: Average compas are not equal for each degree

66. 1.175
1.149
Ho: Interaction is not significant

67. 1.043
1.043
Ha: Interaction is significant
1.074
1.134

68. 1.020
1.000
Perform analysis:

69. 0.903
1.122

70. 0.982
0.903
Anova: Two-Factor With Replication
1.086
1.052

71. 1.075
1.140
SUMMARY
BA
MA
Total

72. 1.052
1.087
Male

73. Female
1.096
1.050
Count
12
12
24
1.025
1.161
Sum
12.349

74. 12.9
25.249
1.000
1.096
Average
1.02908333
1.075
1.052042

75. 0.956
1.000
Variance
0.00668645
0.00652
0.006866

76. 1.000
1.041
1.043

77. 1.043
Female
1.043
1.119
Count
12
12
24

78. 1.210
1.043
Sum
12.791
12.787
25.578

79. 1.187
1.000
Average
1.06591667
1.065583
1.06575

80. 1.043
0.956
Variance
0.00610245
0.004213
0.004933
1.043
1.129

81. 1.145
1.149
Total

82. Count
24
24

83. Sum
25.14
25.687

84. Average
1.0475
1.070292
Variance
0.00647035
0.005156

87. ANOVA
Source of Variation
SS

88. df
MS
F
P-value
F crit
Sample
0.00225502
1
0.002255
0.383482
0.538939
4.061706
(This is the row variable or gender.)

89. Columns
0.00623352
1
0.006234
1.060054
0.30883
4.061706
(This is the column variable or Degree.)

90. Interaction
0.00641719
1
0.006417
1.091288
0.301892
4.061706
Within
0.25873675

91. 44
0.00588

92. Total
0.27364248
47

94. Interpretation:

95. For Ho: Average compas by gender are equal
Ha: Average compas by gender are not equal

96. What is the p-value:
Is P-value < 0.05?

97. Do you reject or not reject the null hypothesis:

98. If
the null hypothesis was rejected, what is the effect size value
(eta squared):

99. Meaning of effect size measure:

100. For Ho: Average compas are equal for all degrees
Ha: Average compas are not equal for all grades

101. What is the p-value:

102. Is P-value < 0.05?
Do you reject or not reject the null hypothesis:

103. If
the null hypothesis was rejected, what is the effect size value
(eta squared):

104. Meaning of effect size measure:

105. For: Ho: Interaction is not significant
Ha: Interaction is significant

106. What is the p-value:

107. Is P-value < 0.05?

108. Do you reject or not reject the null hypothesis:
If
the null hypothesis was rejected, what is the effect size value

109. (eta squared):
Meaning of effect size measure:

111. What do these decisions mean in terms of our equal pay
question:

113. Place data values in these columns

114. <1 point>
4
Many companies consider the grade midpoint to be the "market
rate" - what is needed to hire a new employee.
Salary
Midpoint
Does the company, on average, pay its existing employees at or
above the market rate?

117. Null Hypothesis:
Alt. Hypothesis:

119. Statistical test to use:

120. Place
the cursor in B160 for test.

134. What is the p-value:

135. Is P-value < 0.05?

136. What else needs to be checked on a 1-tail in order to reject the
null?

137. Do we REJ or Not reject the null?
If

138. the null hypothesis was rejected, what is the effect size value:
NA
Meaning of effect size measure:
NA

139. Interpretation:

141. <2 points>
5.
Using the results up thru this week, what are your conclusions
about gender equal pay for equal work at this point?