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bus308_week_1_data_questions.xlsx
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week 1

Score: Week 1. Measurement and Description - chapters 1 and 2
<1 point> 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?
<1 point> 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 groups: overall sample, Females, and Males.
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
<1 point> 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?
<1 point> 4 For each group (overall, females, and males) find: Overall Female Male
a. The value that cuts off the top 1/3 salary in each group. Hint: can use these Fx functions
b. The z score for each value: Excel's standize function
c. The normal curve probability of exceeding this score: 1-normsdist function
d. What is the empirical probability of being at or exceeding this salary value?
e. The value that cuts off the top 1/3 compa in each group.
f. The z score for each value:
g. The normal curve probability of exceeding this score:
h. What is the empirical probability of being at or exceeding this compa value?
i. How do you interpret the relationship between the data sets? What do they mean about our equal pay for equal work question?
<2 points> 5.      What conclusions can you make about the issue of male and female pay equality? Are all of the results consistent?
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?

data

ID Salary Compa Midpoint Age Performance Rating Service Gender Raise Degree Gender1 Gr
1 64.4 1.13 57 34 85 8 0 5.7 0 M E The ongoing question that the weekly assignments will focus on is: Are males and females paid the same for equal work (under the Equal Pay Act)?
2 27.4 0.884 31 52 80 7 0 3.9 0 M B Note: to simplfy the analysis, we will assume that jobs within each grade comprise equal work.
3 35.6 1.148 31 30 75 5 1 3.6 1 F B
4 62.3 1.093 57 42 100 16 0 5.5 1 M E The column labels in the table mean:
5 48.7 1.014 48 36 90 16 0 5.7 1 M D ID – Employee sample number Salary – Salary in thousands
6 75 1.12 67 36 70 12 0 4.5 1 M F Age – Age in years Performance Rating - Appraisal rating (employee evaluation score)
7 41.8 1.046 40 32 100 8 1 5.7 1 F C Service – Years of service (rounded) Gender – 0 = male, 1 = female
8 23.7 1.029 23 32 90 9 1 5.8 1 F A Midpoint – salary grade midpoint Raise – percent of last raise
9 76.8 1.147 67 49 100 10 0 4 1 M F Grade – job/pay grade Degree (0= BS\BA 1 = MS)
10 24 1.044 23 30 80 7 1 4.7 1 F A Gender1 (Male or Female) Compa - salary divided by midpoint
11 23.9 1.041 23 41 100 19 1 4.8 1 F A
12 62.5 1.096 57 52 95 22 0 4.5 0 M E
13 42.7 1.067 40 30 100 2 1 4.7 0 F C
14 23.4 1.016 23 32 90 12 1 6 1 F A
15 23.3 1.012 23 32 80 8 1 4.9 1 F A
16 48.7 1.217 40 44 90 4 0 5.7 0 M C
17 65.1 1.142 57 27 55 3 1 3 1 F E
18 34.6 1.116 31 31 80 11 1 5.6 0 F B
19 24.5 1.065 23 32 85 1 0 4.6 1 M A
20 34.9 1.125 31 44 70 16 1 4.8 0 F B
21 76.5 1.142 67 43 95 13 0 6.3 1 M F
22 57.8 1.204 48 48 65 6 1 3.8 1 F D
23 22.7 0.987 23 36 65 6 1 3.3 0 F A
24 56.5 1.177 48 30 75 9 1 3.8 0 F D
25 24.5 1.064 23 41 70 4 0 4 0 M A
26 23.2 1.01 23 22 95 2 1 6.2 0 F A
27 46.8 1.171 40 35 80 7 0 3.9 1 M C
28 76.6 1.144 67 44 95 9 1 4.4 0 F F
29 75.9 1.133 67 52 95 5 0 5.4 0 M F
30 47.4 0.987 48 45 90 18 0 4.3 0 M D
31 25.3 1.101 23 29 60 4 1 3.9 1 F A
32 27.2 0.878 31 25 95 4 0 5.6 0 M B
33 66 1.158 57 35 90 9 0 5.5 1 M E
34 28.1 0.907 31 26 80 2 0 4.9 1 M B
35 22.5 0.98 23 23 90 4 1 5.3 0 F A
36 22.7 0.985 23 27 75 3 1 4.3 0 F A
37 23.4 1.017 23 22 95 2 1 6.2 0 F A
38 58.5 1.026 57 45 95 11 0 4.5 0 M E
39 35.5 1.144 31 27 90 6 1 5.5 0 F B
40 24.8 1.078 23 24 90 2 0 6.3 0 M A
41 45.8 1.144 40 25 80 5 0 4.3 0 M C
42 22.2 0.965 23 32 100 8 1 5.7 1 F A
43 77.4 1.155 67 42 95 20 1 5.5 0 F F
44 58.8 1.032 57 45 90 16 0 5.2 1 M E
45 51.2 1.066 48 36 95 8 1 5.2 1 F D
46 61.3 1.076 57 39 75 20 0 3.9 1 M E
47 64.3 1.128 57 37 95 5 0 5.5 1 M E
48 67.6 1.186 57 34 90 11 1 5.3 1 F E
49 61.3 1.075 57 41 95 21 0 6.6 0 M E
50 66.1 1.159 57 38 80 12 0 4.6 0 M E

Sheet3

Sal Compa G Mid Age EES SR G Raise Deg SUMMARY OUTPUT SUMMARY OUTPUT
24 1.045 1 23 32 90 9 1 5.8 1
24.2 1.053 1 23 30 80 7 1 4.7 1 Regression Statistics Regression Statistics
23.4 1.018 1 23 41 100 19 1 4.8 1 Multiple R 0.7050179484 Multiple R 0.9931286935
23.4 1.017 1 23 32 90 12 1 6 1 R Square 0.4970503076 R Square 0.9863046018
22.6 0.983 1 23 32 80 8 1 4.9 1 Adjusted R Square 0.4132253589 Adjusted R Square 0.9840220355
22.9 0.995 1 23 36 65 6 1 3.3 0 Standard Error 0.0561252686 Standard Error 2.4352822665
23.1 1.003 1 23 22 95 2 1 6.2 0 Observations 50 Observations 50
23.3 1.011 1 23 29 60 4 1 3.9 1
22.7 0.985 1 23 23 90 4 1 5.3 0 ANOVA ANOVA
23.5 1.023 1 23 27 75 3 1 4.3 0 df SS MS F Significance F df SS MS F Significance F
23 1.002 1 23 22 95 2 1 6.2 0 Regression 7 0.1307500775 0.0186785825 5.9296225662 0.0000782906 Regression 7 17938.424611863 2562.632087409 432.1033638177 5.29906273684337E-37
24 1.042 1 23 32 100 8 1 5.7 1 Residual 42 0.1323019225 0.0031500458 Residual 42 249.085188137 5.9305997175
35.5 1.145 1 31 30 75 5 1 3.6 1 Total 49 0.263052 Total 49 18187.5098
34.7 1.119 1 31 31 80 11 1 5.6 0
35.5 1.146 1 31 44 70 16 1 4.8 0 Coefficients Standard Error t Stat P-value Lower 95% Upper 95% Lower 95.0% Upper 95.0% Coefficients Standard Error t Stat P-value Lower 95% Upper 95% Lower 95.0% Upper 95.0%
35.2 1.136 1 31 27 90 6 1 5.5 0 Intercept 0.9486238772 0.0817167716 11.6086803119 0 0.7837127557 1.1135349987 0.7837127557 1.1135349987 Intercept -4.8714544587 3.54570071 -1.3739045839 0.1767599037 -12.0269681853 2.2840592678 -12.0269681853 2.2840592678
40.4 1.01 1 40 32 100 8 1 5.7 1 Mid 0.0034995027 0.0006492568 5.3900133356 0.0000029767 0.0021892495 0.0048097559 0.0021892495 0.0048097559 Mid 1.2284155048 0.0281713308 43.6051641629 1.32019333894083E-36 1.1715634576 1.2852675521 1.1715634576 1.2852675521
42.7 1.068 1 40 30 100 2 1 4.7 0 Age 0.0005527738 0.0014459446 0.3822925256 0.7041721007 -0.0023652605 0.0034708081 -0.0023652605 0.0034708081 Age 0.0368279425 0.0627397124 0.5869957178 0.5603489282 -0.0897859231 0.1634418081 -0.0897859231 0.1634418081
53.4 1.112 1 48 48 65 6 1 3.8 1 EES -0.0018462553 0.0010252155 -1.8008461371 0.0789105539 -0.0039152239 0.0002227133 -0.0039152239 0.0002227133 EES -0.0821579785 0.0444842245 -1.8469014451 0.0718147225 -0.171930778 0.007614821 -0.171930778 0.007614821
51.5 1.072 1 48 30 75 9 1 3.8 0 SR -0.0004182288 0.0018278101 -0.2288141345 0.820123898 -0.004106899 0.0032704414 -0.004106899 0.0032704414 SR -0.0778484529 0.079308905 -0.9815852701 0.3319249969 -0.2379003029 0.0822033971 -0.2379003029 0.0822033971
49.8 1.037 1 48 36 95 8 1 5.2 1 G 0.0646649961 0.0183396697 3.5259629624 0.001034866 0.0276540443 0.101675948 0.0276540443 0.101675948 G 2.9145083112 0.7957605113 3.6625445343 0.000693549 1.3085985836 4.5204180389 1.3085985836 4.5204180389
68.3 1.198 1 57 27 55 3 1 3 1 Raise 0.0146549564 0.0139088976 1.0536389608 0.2980722322 -0.0134143354 0.0427242483 -0.0134143354 0.0427242483 Raise 0.6763294824 0.6035087689 1.1206622295 0.2687988764 -0.5416005215 1.8942594864 -0.5416005215 1.8942594864
65.4 1.148 1 57 34 90 11 1 5.3 1 Deg 0.0014675988 0.0161098249 0.0910996125 0.9278465471 -0.0310433441 0.0339785418 -0.0310433441 0.0339785418 Deg 0.0345044482 0.6990072742 0.0493620731 0.9608647532 -1.3761493419 1.4451582383 -1.3761493419 1.4451582383
78.4 1.17 1 67 44 95 9 1 4.4 0
75.9 1.133 1 67 42 95 20 1 5.5 0
24 1.044 0 23 32 85 1 0 4.6 1
23.3 1.012 0 23 41 70 4 0 4 0
24.1 1.049 0 23 24 90 2 0 6.3 0
27.5 0.887 0 31 52 80 7 0 3.9 0 t-Test: Two-Sample Assuming Equal Variances
27.1 0.875 0 31 25 95 4 0 5.6 0
27.7 0.895 0 31 26 80 2 0 4.9 1 Variable 1 Variable 2
40.8 1.019 0 40 44 90 4 0 5.7 0 Mean 1.06684 1.04836
43.9 1.097 0 40 35 80 7 0 3.9 1 Variance 0.00430164 0.00648099
41 1.025 0 40 25 80 5 0 4.3 0 Observations 25 25
48.7 1.014 0 48 36 90 16 0 5.7 1 Pooled Variance 0.005391315
49.4 1.029 0 48 45 90 18 0 4.3 0 Hypothesized Mean Difference 0
64.4 1.13 0 57 34 85 8 0 5.7 0 df 48
64.5 1.132 0 57 42 100 16 0 5.5 1 t Stat 0.8898352784
58.9 1.033 0 57 52 95 22 0 4.5 0 P(T<=t) one-tail 0.188996287
57.9 1.016 0 57 35 90 9 0 5.5 1 t Critical one-tail 1.6772241961
59 1.035 0 57 45 95 11 0 4.5 0 P(T<=t) two-tail 0.3779925741
63.3 1.111 0 57 45 90 16 0 5.2 1 t Critical two-tail 2.0106347576
56.8 0.996 0 57 39 75 20 0 3.9 1
58 1.017 0 57 37 95 5 0 5.5 1
62.4 1.094 0 57 41 95 21 0 6.6 0
63.8 1.12 0 57 38 80 12 0 4.6 0
79 1.179 0 67 36 70 12 0 4.5 1
77 1.149 0 67 49 100 10 0 4 1
74.8 1.116 0 67 43 95 13 0 6.3 1
76 1.135 0 67 52 95 5 0 5.4 0