Unformatted Attachment Preview
Complete the problems below and submit your work in an Excel document. Be sure to show all
of your work and clearly label all calculations. All statistical calculations will use the Additional
excel attachment
Included in the Additional excel attachment Data Set are 2 one-sample t-tests comparing male
and female average salaries to the overall sample mean.
Below are 2 one-sample t-test comparing male and female average salaries to the overall sample
mean. Based on our sample, how do you interpret the results and what do these results suggest
about the population means for male and female salaries?
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.)
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.)
Since performance is often a factor in pay levels, is the average Performance Rating the same for
both genders?
If the salary and compa mean tests in questions 2 and 3 provide different results about male and
female salary equality, 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??
Complete the problems below and submit your work in an Excel document. Be sure to show all
of your work and clearly label all calculations. All statistical calculations will use the Additional
excel attachment
Included in the Additional excel attachment Data Set are 2 one-sample t-tests comparing male
and female average salaries to the overall sample mean.
Below are 2 one-sample t-test comparing male and female average salaries to the overall sample
mean. Based on our sample, how do you interpret the results and what do these results suggest
about the population means for male and female salaries?
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.)
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.)
Since performance is often a factor in pay levels, is the average Performance Rating the same for
both genders?
If the salary and compa mean tests in questions 2 and 3 provide different results about male and
female salary equality, 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??
Complete the problems below and submit your work in an Excel document. Be sure to show all
of your work and clearly label all calculations. All statistical calculations will use the Additional
excel attachment
Included in the Additional excel attachment Data Set are 2 one-sample t-tests comparing male
and female average salaries to the overall sample mean.
Below are 2 one-sample t-test comparing male and female average salaries to the overall sample
mean. Based on our sample, how do you interpret the results and what do these results suggest
about the population means for male and female salaries?
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.)
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.)
Since performance is often a factor in pay levels, is the average Performance Rating the same for
both genders?
If the salary and compa mean tests in questions 2 and 3 provide different results about male and
female salary equality, 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??
See comments at the right of the data set.
ID Salary Compa Midpoint Age
8
10
11
14
15
23
26
31
35
36
37
42
3
18
20
39
7
13
22
24
45
17
48
28
43
19
25
40
2
32
34
16
27
41
5
30
1
4
12
23
22
23
24
24
23
24
24
24
23
22
24
34
36
34
35
41
42
57
50
55
69
65
75
77
24
24
25
27
28
28
47
40
43
47
49
58
66
60
1.000
0.956
1.000
1.043
1.043
1.000
1.043
1.043
1.043
1.000
0.956
1.043
1.096
1.161
1.096
1.129
1.025
1.050
1.187
1.041
1.145
1.210
1.140
1.119
1.149
1.043
1.043
1.086
0.870
0.903
0.903
1.175
1.000
1.075
0.979
1.020
1.017
1.157
1.052
23
23
23
23
23
23
23
23
23
23
23
23
31
31
31
31
40
40
48
48
48
57
57
67
67
23
23
23
31
31
31
40
40
40
48
48
57
57
57
32
30
41
32
32
36
22
29
23
27
22
32
30
31
44
27
32
30
48
30
36
27
34
44
42
32
41
24
52
25
26
44
35
25
36
45
34
42
52
Performanc Service Gender Raise Degree Gender1
e Rating
90
9
1
5.8
0
F
80
7
1
4.7
0
F
100
19
1
4.8
0
F
90
12
1
6
0
F
80
8
1
4.9
0
F
65
6
1
3.3
1
F
95
2
1
6.2
1
F
60
4
1
3.9
0
F
90
4
1
5.3
1
F
75
3
1
4.3
1
F
95
2
1
6.2
1
F
100
8
1
5.7
0
F
75
5
1
3.6
0
F
80
11
1
5.6
1
F
70
16
1
4.8
1
F
90
6
1
5.5
1
F
100
8
1
5.7
0
F
100
2
1
4.7
1
F
65
6
1
3.8
0
F
75
9
1
3.8
1
F
95
8
1
5.2
0
F
55
3
1
3
0
F
90
11
1
5.3
1
F
95
9
1
4.4
1
F
95
20
1
5.5
1
F
85
1
0
4.6
1
M
70
4
0
4
0
M
90
2
0
6.3
0
M
80
7
0
3.9
0
M
95
4
0
5.6
0
M
80
2
0
4.9
1
M
90
4
0
5.7
0
M
80
7
0
3.9
1
M
80
5
0
4.3
0
M
90
16
0
5.7
1
M
90
18
0
4.3
0
M
85
8
0
5.7
0
M
100
16
0
5.5
1
M
95
22
0
4.5
0
M
33
38
44
46
47
49
50
6
9
21
29
64
56
60
65
62
60
66
76
77
76
72
1.122
0.982
1.052
1.140
1.087
1.052
1.157
1.134
1.149
1.134
1.074
57
57
57
57
57
57
57
67
67
67
67
35
45
45
39
37
41
38
36
49
43
52
90
95
90
75
95
95
80
70
100
95
95
9
11
16
20
5
21
12
12
10
13
5
0
0
0
0
0
0
0
0
0
0
0
5.5
4.5
5.2
3.9
5.5
6.6
4.6
4.5
4
6.3
5.4
1
0
1
1
1
0
0
1
1
1
0
M
M
M
M
M
M
M
M
M
M
M
Grade
A
A
A
A
A
A
A
A
A
A
A
A
B
B
B
B
C
C
D
D
D
E
E
F
F
A
A
A
B
B
B
C
C
C
D
D
E
E
E
The ongoing question that the weekly assignments will focus on is: Are males and females paid the same
Note: to simplfy the analysis, we will assume that jobs within each grade comprise equal work.
The column labels in the table mean:
ID – Employee sample number
Age – Age in years
Service – Years of service (rounded)
Midpoint – salary grade midpoint
Grade – job/pay grade
Gender1 (Male or Female)
Salary – Salary in thousands
Performance Rating – Appraisal rating (Employee evalua
Gender: 0 = male, 1 = female
Raise – percent of last raise
Degree (0= BS\BA 1 = MS)
Compa - salary divided by midpoint
E
E
E
E
E
E
E
F
F
F
F
es and females paid the same for equal work (under the Equal Pay Act)?
Week 1. Measurement and Description - chapters 1 and 2
1
Measurement issues. Data, even numerically coded variables, can be one of 4 levels nominal, ordinal, interval, or ratio. It is important to identify which level a variable is, as
this impact the kind of analysis we can do with the data. For example, descriptive statistics
such as means can only be done on interval or ratio level data.
Please list under each label, the variables in our data set that belong in each group.
Nominal Ordinal Interval Ratio
b. For each variable that you did not call ratio, why did you make that decision?
2
The first step in analyzing data sets is to find some summary descriptive statistics for key variables.
For salary, compa, age, performance rating, and service; find the mean, standard deviation, and range for 3
You can use either the Data Analysis Descriptive Statistics tool or the Fx =average and =stdev functions.
(the range must be found using the difference between the =max and =min functions with Fx) functions.
Note: Place data to the right, if you use Descriptive statistics, place that to the right as well.
Salary
Compa
Age
Perf. Rat. Service
Overall
Mean
Standard Deviation
Range
Female
Mean
Standard Deviation
Range
Male
Mean
Standard Deviation
Range
3
What is the probability for a:
Probability
a.
Randomly selected person being a male in grade E?
b.
Randomly selected male being in grade E?
Note part b is the same as given a male, what is probabilty of being in grade E?
c. Why are the results different?
4
a.
b.
c.
d.
e.
f.
g.
h.
i.
5.
For each group (overall, females, and males) find:
The value that cuts off the top 1/3 salary in each group.
The z score for each value:
The normal curve probability of exceeding this score:
What is the empirical probability of being at or exceeding this salary value?
The value that cuts off the top 1/3 compa in each group.
The z score for each value:
The normal curve probability of exceeding this score:
What is the empirical probability of being at or exceeding this compa value?
How do you interpret the relationship between the data sets? What do they mean about our equal pay for e
What conclusions can you make about the issue of male and female pay equality? Are all of the results co
What is the difference between the sal and compa measures of pay?
Conclusions from looking at salary results:
Conclusions from looking at compa results:
Do both salary measures show the same results?
Can we make any conclusions about equal pay for equal work yet?
Overall
Female
Male
ey mean about our equal pay for equal work question?
equality? Are all of the results consistent?
Week 2
1
Testing means
In questions 2 and 3, be sure to include the null and alternate hypotheses you will be testing.
In the first 3 questions use alpha = 0.05 in making your decisions on rejecting or not rejecting the nul
Below are 2 one-sample t-tests comparing male and female average salaries to the overall sample me
(Note: a one-sample t-test in Excel can be performed by selecting the 2-sample unequal variance t-tes
Based on our sample, how do you interpret the results and what do these results suggest about the pop
Males
Females
Ho: Mean salary = 45
Ho: Mean salary = 45
Ha: Mean salary =/= 45
Ha: Mean salary =/= 45
Note: While the results both below are actually from Excel's t-Test: Two-Sample Assuming Unequal
having no variance in the Ho variable makes the calculations default to the one-sample t-test outcome
Male
Ho
Mean
52
45
Variance
316
0
Observations
25
25
Hypothesized Mean Difference 0
df
24
t Stat
1.96890383
P(T