Score: Week 2 Testing means - T-tests Q3 In questions 2 and 3, be sure to include the null and alternate hypotheses you will be testing.   Ho Female Male Female In the first 3 questions use alpha = 0.05 in making your decisions on rejecting or not rejecting the null hypothesis. 45 34 1.017 1.096 45 41 0.870 1.025 <1 point> 1 Below are 2 one-sample t-tests comparing male and female average salaries to the overall sample mean.   45 23 1.157 1.000 (Note: a one-sample t-test in Excel can be performed by selecting the 2-sample unequal variance t-test and making the second variable = Ho value -- see column S) 45 22 0.979 0.956 Based on our sample, how do you interpret the results and what do these results suggest about the population means for male and female average salaries? 45 23 1.134 1.000 Males Females 45 42 1.149 1.050 Ho: Mean salary = 45 Ho: Mean salary = 45 45 24 1.052 1.043 Ha: Mean salary =/= 45 Ha: Mean salary =/= 45 45 24 1.175 1.043 45 69 1.043 1.210 Note: While the results both below are actually from Excel's t-Test: Two-Sample Assuming Unequal Variances,  45 36 1.134 1.161 having no variance in the Ho variable makes the calculations default to the one-sample t-test outcome - we are tricking Excel into doing a one sample test for us. 45 34 1.043 1.096 Male Ho Female Ho 45 57 1.000 1.187 Mean 52 45 Mean 38 45 45 23 1.074 1.000 Variance 316 0 Variance 334.6666667 0 45 50 1.020 1.041 Observations 25 25 Observations 25 25 45 24 0.903 1.043 Hypothesized Mean Difference 0 Hypothesized Mean Difference 0 45 75 1.122 1.119 df 24 df 24 45 24 0.903 1.043 t Stat 1.968903827 t Stat -1.913206357 45 24 0.982 1.043 P(T<=t) one-tail 0.03030785 P(T<=t) one-tail 0.033862118 45 23 1.086 1.000 t Critical one-tail 1.71088208 t Critical one-tail 1.71088208 45 22 1.075 0.956 P(T<=t) two-tail 0.060615701 P(T<=t) two-tail 0.067724237 45 35 1.052 1.129 t Critical two-tail 2.063898562 t Critical two-tail 2.063898562 45 24 1.140 1.043 Conclusion: Do not reject Ho; mean equals 45 Conclusion: Do not reject Ho; mean equals 45 45 77 1.087 1.149 Is this a 1 or 2 tail test? Is this a 1 or 2 tail test? - why? - why? P-value is: P-value is: 45 55 1.052 1.145 Is P-value > 0.05? Is P-value > 0.05? 45 65 1.157 1.140 Why do we not reject Ho? Why do we not reject Ho? Interpretation: <1 point> 2 Based on our sample data set, perform a 2-sample t-test to see if the pop.

1. Score:
Week 2
Testing means - T-tests

2. Q3
In questions 2 and 3, be sure to include the null and alternate
hypotheses you will be testing.
Ho
Female
Male
Female
In the first 3 questions use alpha = 0.05 in making your
decisions on rejecting or not rejecting the null hypothesis.

3. 45
34
1.017
1.096
45
41
0.870
1.025
<1 point>
1
Below are 2 one-sample t-tests comparing male and female
average salaries to the overall sample mean.

4. 45
23
1.157
1.000
(Note: a one-sample t-test in Excel can be performed by
selecting the 2-sample unequal variance t-test and making the
second variable = Ho value -- see column S)
45
22
0.979
0.956
Based on our sample, how do you interpret the results and what
do these results suggest about the population means for male
and female average salaries?

5. 45
23
1.134
1.000
Males
Females
45
42
1.149
1.050

6. Ho: Mean salary = 45
Ho: Mean salary = 45
45
24
1.052
1.043
Ha: Mean salary =/= 45
Ha: Mean salary =/= 45

7. 45
24
1.175
1.043
45
69
1.043
1.210

8. Note: While the results both below are actually from Excel's t-
Test: Two-Sample Assuming Unequal Variances,
45
36
1.134
1.161
having no variance in the Ho variable makes the calculations
default to the one-sample t-test outcome - we are tricking Excel
into doing a one sample test for us.
45
34
1.043
1.096

9. Male
Ho
Female
Ho
45
57
1.000
1.187
Mean
52
45
Mean
38
45

10. 45
23
1.074
1.000
Variance
316
0
Variance
334.6666667
0
45
50
1.020
1.041

11. Observations
25
25
Observations
25
25
45
24
0.903
1.043
Hypothesized Mean Difference
0
Hypothesized Mean Difference
0

12. 45
75
1.122
1.119
df
24
df
24
45
24

13. 0.903
1.043
t Stat
1.968903827
t Stat
-1.913206357
45
24
0.982
1.043
P(T<=t) one-tail
0.03030785
P(T<=t) one-tail

14. 0.033862118
45
23
1.086
1.000
t Critical one-tail
1.71088208
t Critical one-tail
1.71088208

15. 45
22
1.075
0.956
P(T<=t) two-tail
0.060615701
P(T<=t) two-tail
0.067724237
45
35
1.052
1.129
t Critical two-tail
2.063898562

16. t Critical two-tail
2.063898562
45
24
1.140
1.043
Conclusion: Do not reject Ho; mean equals 45
Conclusion: Do not reject Ho; mean equals 45
45
77

17. 1.087
1.149
Is this a 1 or 2 tail test?
Is this a 1 or 2 tail test?
- why?
- why?

18. P-value is:
P-value is:

19. 45
55
1.052
1.145
Is P-value > 0.05?
Is P-value > 0.05?
45
65
1.157
1.140
Why do we not reject Ho?

20. Why do we not reject Ho?
Interpretation:

24. <1 point>
2
Based on our sample data set, perform a 2-sample t-test to see if
the population male and female average salaries could be equal
to each other.
(Since we have not yet covered testing for variance equality,
assume the data sets have statistically equal variances.)

25. Ho:

26. Ha:

27. Test to use:
Place B43 in Outcome range box.

38. P-value is:

39. Is P-value < 0.05?

40. Reject or do not reject Ho:

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

43. Interpretation:

44. b.
Since the one and two sample t-test results provided different
outcomes, which is the proper/correct apporach to comparing
salary equality? Why?

46. <1 point>
3
Based on our sample data set, can the male and female compas
in the population be equal to each other? (Another 2-sample t-
test.)

47. Ho:

48. Ha:
Statistical test to use:

49. Place B75 in Outcome range box.

60. What is the p-value:

61. Is P-value < 0.05?

62. Reject or do not reject Ho:
If the null hypothesis was rejected, what is the effect size
value:

63. Meaning of effect size measure:

64. Interpretation:

66. <1 point>
4
Since performance is often a factor in pay levels, is the average
Performance Rating the same for both genders?

67. Ho:

68. Ha:

69. Test to use:

70. Place B106 in Outcome range box.

82. What is the p-value:

83. Is P-value < 0.05?

84. Do we REJ or Not reject the null?
If the null hypothesis was rejected, what is the effect size
value:

85. Meaning of effect size measure:

86. Interpretation:

89. <2 points>
5
If the salary and compa mean tests in questions 2 and 3 provide
different results about male and female salary equality,

90. which would be more appropriate to use in answering the
question about salary equity? Why?
What are your conclusions about equal pay at this point?