The Equal Opportunity Commission is investigating questions around unequal pay rates and discriminatory remuneration in various industries. The Pay Equity tab in the excel workbook contains information on 100 employees from a particular industry. Information includes: Salary ($) Gender Years of Education Years of Experience Division of employment Age Run a multiple regression analysis looking at the relationship between salary and years of education and years of experience. What proportion of variation in salary can be explained by these two variables? Conduct a test of the overall significance of the model. Test both the Education and Experience variables separately. Do both contribute to explaining the variation in salaries? Write out the estimated equation and interpret all coefficients. Salary (in $) Education (years) Experience (years) 20860 11 4 30200 16 1 31240 12 1 36860 12 8 44760 14 4 46690 19 3 47400 15 1 47880 14 3 50620 13 6 50690 14 4 56590 15 4 57040 15 1 57100 14 5 57960 16 2 61260 16 6 62260 12 12 63330 12 8 64540 16 6 66380 15 10 67670 14 22 67920 16 10 68620 17 12 68670 14 9 68690 15 13 69640 15 5 70030 18 12 70160 18 15 74810 13 21 75490 15 10 76820 15 19 77030 12 10 77290 12 10 79100 16 10 79290 14 10 80090 15 7 80320 15 19 80520 16 8 81640 15 12 81760 15 32 82100 16 9 82430 17 12 83160 15 11 83430 14 16 84340 13 20 85470 15 6 86010 14 16 87320 16 12 87920 15 16 88350 17 2 89050 16 6 89150 13 9 90070 16 11 90990 15 18 91450 13 20 91560 16 10 91850 11 22 92630 15 12 92720 15 10 92840 14 19 93090 14 18 93390 17 10 93830 17 9 94470 14 20 97440 14 12 97480 17 14 97790 16 20 98050 16 13 98940 15 10 99090 16 25 99680 15 18 99710 14 18 100250 16 16 100930 16 8 101400 12 22 101750 17 6 105750 14 22 106830 20 18 107570 17 29 109360 17 28 109680 18 16 110660 15 21 113920 15 17 114970 17 10 115500 14 20 116930 17 16 119470 17 18 120580 15 31 122940 16 30 125360 15 21 126750 16 30 129790 17 21 131560 17 32 132010 17 20 134540 16 23 139260 15 21 142760 18 10 145110 13 19 158960 17 35 165400 16 30 175760 15 24

The Equal Opportunity Commission is investigating questions around unequal pay rates and discriminatory remuneration in various industries. The Pay Equity tab in the excel workbook contains information on 100 employees from a particular industry. Information includes: Salary ($) Gender Years of Education Years of Experience Division of employment Age Run a multiple regression analysis looking at the relationship between salary and years of education and years of experience. What proportion of variation in salary can be explained by these two variables? Conduct a test of the overall significance of the model. Test both the Education and Experience variables separately. Do both contribute to explaining the variation in salaries? Write out the estimated equation and interpret all coefficients. Salary (in $) Education (years) Experience (years) 20860 11 4 30200 16 1 31240 12 1 36860 12 8 44760 14 4 46690 19 3 47400 15 1 47880 14 3 50620 13 6 50690 14 4 56590 15 4 57040 15 1 57100 14 5 57960 16 2 61260 16 6 62260 12 12 63330 12 8 64540 16 6 66380 15 10 67670 14 22 67920 16 10 68620 17 12 68670 14 9 68690 15 13 69640 15 5 70030 18 12 70160 18 15 74810 13 21 75490 15 10 76820 15 19 77030 12 10 77290 12 10 79100 16 10 79290 14 10 80090 15 7 80320 15 19 80520 16 8 81640 15 12 81760 15 32 82100 16 9 82430 17 12 83160 15 11 83430 14 16 84340 13 20 85470 15 6 86010 14 16 87320 16 12 87920 15 16 88350 17 2 89050 16 6 89150 13 9 90070 16 11 90990 15 18 91450 13 20 91560 16 10 91850 11 22 92630 15 12 92720 15 10 92840 14 19 93090 14 18 93390 17 10 93830 17 9 94470 14 20 97440 14 12 97480 17 14 97790 16 20 98050 16 13 98940 15 10 99090 16 25 99680 15 18 99710 14 18 100250 16 16 100930 16 8 101400 12 22 101750 17 6 105750 14 22 106830 20 18 107570 17 29 109360 17 28 109680 18 16 110660 15 21 113920 15 17 114970 17 10 115500 14 20 116930 17 16 119470 17 18 120580 15 31 122940 16 30 125360 15 21 126750 16 30 129790 17 21 131560 17 32 132010 17 20 134540 16 23 139260 15 21 142760 18 10 145110 13 19 158960 17 35 165400 16 30 175760 15 24

Linear Algebra: A Modern Introduction

4th Edition

ISBN:9781285463247

Author:David Poole

Publisher:David Poole

Chapter7: Distance And Approximation

Section7.3: Least Squares Approximation

Problem 31EQ

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Question

100%

Salary ($)
Gender
Years of Education
Years of Experience
Division of employment
Age

Run a multiple regression analysis looking at the relationship between salary and years of education and years of experience. What proportion of variation in salary can be explained by these two variables? Conduct a test of the overall significance of the model. Test both the Education and Experience variables separately. Do both contribute to explaining the variation in salaries? Write out the estimated equation and interpret all coefficients.

Salary (in $)	Education (years)	Experience (years)
20860	11	4
30200	16	1
31240	12	1
36860	12	8
44760	14	4
46690	19	3
47400	15	1
47880	14	3
50620	13	6
50690	14	4
56590	15	4
57040	15	1
57100	14	5
57960	16	2
61260	16	6
62260	12	12
63330	12	8
64540	16	6
66380	15	10
67670	14	22
67920	16	10
68620	17	12
68670	14	9
68690	15	13
69640	15	5
70030	18	12
70160	18	15
74810	13	21
75490	15	10
76820	15	19
77030	12	10
77290	12	10
79100	16	10
79290	14	10
80090	15	7
80320	15	19
80520	16	8
81640	15	12
81760	15	32
82100	16	9
82430	17	12
83160	15	11
83430	14	16
84340	13	20
85470	15	6
86010	14	16
87320	16	12
87920	15	16
88350	17	2
89050	16	6
89150	13	9
90070	16	11
90990	15	18
91450	13	20
91560	16	10
91850	11	22
92630	15	12
92720	15	10
92840	14	19
93090	14	18
93390	17	10
93830	17	9
94470	14	20
97440	14	12
97480	17	14
97790	16	20
98050	16	13
98940	15	10
99090	16	25
99680	15	18
99710	14	18
100250	16	16
100930	16	8
101400	12	22
101750	17	6
105750	14	22
106830	20	18
107570	17	29
109360	17	28
109680	18	16
110660	15	21
113920	15	17
114970	17	10
115500	14	20
116930	17	16
119470	17	18
120580	15	31
122940	16	30
125360	15	21
126750	16	30
129790	17	21
131560	17	32
132010	17	20
134540	16	23
139260	15	21
142760	18	10
145110	13	19
158960	17	35
165400	16	30
175760	15	24

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