## Linear Regression Analysis; Women make less than men

Regression analysis is a statistical tool used to “estimate the value of variable based on the value of another” (University of Phoenix, 2004, p. 429). The goal of regression analysis is to determine the values of parameters for a function that cause the function to best fit a set of selected data observations. Team C will be using the data from our research to confirm the hypothesis. The team will be using the five-step hypothesis process to determine whether to reject or accept the null hypothesis. The analysis will assist by providing numerical data and facts. The analysis we will be using is the Linear Regression analysis. By the end of this research, Team C should be able to prove whether or not women make less money than men.

Women today take on many roles and responsibilities. Not only do they work, but they also have other responsibilities in addition to their wife and motherly duties. Even with those increased responsibilities, women today hold some of the most top positions in the world and they have come this far through continuous education. According to Krefting, although women tend to go to school longer than men; they get educated in fields that don’t pay that much. Most women find jobs in childcare; hospitality; nursing; teaching; and; counseling. Men on the other hand are construction workers; engineers; sociologists; and firemen. Though men might not go to school to practice construction it may be just a talent that they have and they are paid a lot for it; but women have to work harder to move up in salary and in job positions (Krefting, 2003).
Hypothesis Statement
Based on the data sets, the hypothesis for our research shows is that men make higher salary than women. The data provides a comparison on income earnings based on men versus women with the influence of education. The data confirms the disproportion in income between the genders and education. By viewing the data, men’s salaries are substantially more on an annual basis. Even with the men and women having the same education levels, men are paid substantially more than the women with the same level of education. The data confirms the hypothesis that males with similar education levels make more money than women.

The null hypothesis states that income depends on the gender and the mean salaries for women with a higher education still make less than a man with the same education level. The alternative hypothesis states that the income for women with a higher education is higher than the average income earnings of men with the same education level. The hypothesis is that women that have the same level of education as men and are given less pay for the same job position.
Five-Step Hypothesis Test

Regression Analysis

Conclusion
Team C has proven the hypothesis to be correct. The final decision is that women do make less money than men. This was proven through the data that we collected and analyzed through the numerical data shown. (Appendix I)
The results show that even though women are educated and they may have masters and doctrines degrees, their male counterparts still make more money than they do on an annual basis. Although our hypothesis has been tested and results confirmed, the following questions are still unanswered. When will women be able to be on the same field as men? When will they be able to feel that they are equal in the workplace, and there is no favoritism present at work?

Reference
Longley, R. (n.d.).Why women still make less than men: Death, taxes, and a glass ceiling. Retrieved on May 25, 2009, from http://usgovinfo.about.com/cs/censusstatistic/a/womenspay.htm
Dessler, G. (2004). A framework for human resource management (Third Edition). Upper Saddle River, NJ: Prentice-Hall.
Doan, D. & Seward, L. (2007). Applied Statistics in Business and Economics. Burr Ridge, IL: McGraw-Hill. Retrieved May 24, 2009, from https://mycampus.phoenix.eduFouts, C. (2008).
Krefting, L. (2003, March). Gender, work, and organization: Intertwined discourses of merit and gender: Evidence from academic employment in the USA. Retrieved May 31, 2009, from http://classroom.phoenix.edu/afm214/secure/viewattachment.jspa?ID=8414888&messageID=41100199&name=interwined discourses of merit and gender evidence.pdf&view=inline
StatPac Inc (1997-2009). The Statistics Calculator; Statistical Analysis Tests At Your Fingertips. Retrieved from the World Wide Web on June 8, 2009 at http://www.statpac.com/statistics-calculator/counts.htm
Zoppo, G. (April 28, 2009). Why Are Women Still Earning Less Than Men? Retrieved from the World Wide Web on June 1, 2009 at http://www.diversityinc.com/public/5809.cfm.

Appendix I
Female & Male Wage Comparison Data Table

Wage Industry Occupation Ed South Nonwhite Hispanic Fe Ex Marr Age Union
11186 0 0 12 0 0 0 0 0 0 18 0
20852 0 0 12 1 0 0 0 1 0 19 0
10997 0 4 14 0 1 0 0 0 0 20 0
14476 0 5 12 0 0 0 1 3 1 21 0
13787 0 4 11 0 0 0 0 4 1 21 0
19452 0 4 13 0 1 0 0 3 0 22 0
16667 0 3 12 1 0 0 0 4 0 22 0
15234 0 1 12 1 0 1 1 4 0 22 0
39888 0 3 12 1 0 0 0 5 0 23 0
13162 1 0 12 0 1 0 0 6 0 24 1
20793 0 0 12 1 0 0 1 6 0 24 0
19284 1 4 16 0 0 0 0 3 0 25 0
13481 0 4 12 1 0 1 0 7 0 25 0
16789 0 3 13 1 0 0 1 6 1 25 0
11702 0 2 14 1 0 0 1 6 1 26 0
11451 1 0 12 0 0 0 1 8 1 26 0
33351 0 5 16 1 0 0 1 4 1 26 0
37771 0 5 15 0 0 0 0 5 0 26 0
25670 0 3 13 0 0 0 1 8 0 27 1
13312 0 4 12 1 0 0 1 9 1 27 0
29191 0 0 12 0 0 0 0 9 0 27 0
41780 0 0 12 1 0 0 0 9 1 27 0
29977 0 4 16 0 1 0 1 6 1 28 0
25166 0 4 12 0 0 0 1 10 0 28 0
30308 0 4 12 0 0 0 0 10 1 28 0
83443 0 5 17 0 0 0 1 5 0 28 0
15957 0 2 12 1 0 0 1 10 0 28 0
21716 0 5 12 0 0 0 1 11 0 29 0
33461 0 1 16 0 0 1 0 7 1 29 1
28219 0 3 12 1 0 0 0 12 1 30 0
31691 1 0 12 0 0 0 0 13 0 31 0
60626 0 5 18 0 0 0 0 7 1 31 0
52762 0 5 18 0 0 0 0 7 1 31 0
22133 0 5 16 0 0 0 1 10 0 32 1
32094 0 3 12 1 0 0 1 14 1 32 0
16796 0 4 12 0 0 0 1 14 1 32 0
35185 1 3 14 0 0 0 1 12 1 32 0
17690 0 1 12 1 1 0 0 14 1 32 0
15193 1 0 12 0 0 0 1 15 0 33 0
75165 0 1 15 0 0 0 0 12 1 33 0
19227 0 3 12 0 0 0 1 15 1 33 0
50235 1 0 16 0 0 0 0 12 1 34 0
44543 0 2 18 0 0 0 0 10 1 34 0
24509 0 5 14 0 0 1 1 15 0 35 0
29407 0 4 10 1 0 0 0 19 0 35 0
34746 0 3 14 1 0 0 1 15 1 35 0
68573 0 5 16 1 0 0 0 14 1 36 1
28168 1 0 13 0 0 0 0 17 0 36 0
18121 1 3 12 0 0 0 1 18 1 36 0
33498 0 1 10 0 0 0 0 20 1 36 0
29390 0 0 13 0 0 0 0 18 1 37 0
26614 1 0 12 0 0 0 1 19 1 37 0
33411 1 2 12 1 0 0 0 20 1 38 0
22485 0 3 12 0 0 0 0 22 0 40 0
83601 0 5 17 0 0 1 0 18 1 41 0
55777 0 1 14 1 0 0 0 21 1 41 0
21994 0 1 12 0 0 0 1 24 1 42 0
32138 0 4 14 0 0 0 0 22 1 42 1
13318 1 0 11 1 0 0 1 25 1 42 1
33389 0 1 14 0 1 0 0 22 0 42 0
50187 0 3 12 0 0 0 1 24 1 42 0
28440 0 4 12 0 0 0 1 24 1 42 0
37664 0 5 18 0 0 0 0 19 1 43 0
15013 0 4 16 0 0 0 0 21 1 43 0
30133 2 0 10 0 0 0 0 27 1 43 0
31799 0 3 12 0 0 0 1 25 0 43 0
29809 0 4 8 0 1 0 1 29 0 43 0
16817 0 3 12 1 0 0 1 26 0 44 0
66738 0 0 9 1 0 0 0 29 1 44 0
9879 0 3 12 1 0 0 1 28 1 46 0
34484 0 3 13 1 0 0 1 28 0 47 0
49974 1 1 16 0 1 0 0 26 1 48 1
31304 0 1 16 0 0 0 1 26 1 48 0
33959 0 5 17 0 0 0 1 26 1 49 1
30006 1 3 16 0 0 0 1 27 1 49 0
19306 0 5 9 1 1 0 1 34 1 49 1
11780 0 2 11 0 0 0 1 33 1 50 0
49898 2 0 12 0 0 0 0 33 1 51 1
17694 0 4 8 0 0 0 1 38 1 52 0
57623 0 1 15 0 0 0 0 31 1 52 0
83569 0 1 18 0 0 0 0 29 1 53 0
23027 0 4 14 0 1 0 0 34 1 54 1
32786 1 0 11 1 0 0 0 37 1 54 1
46646 2 0 5 1 0 0 0 44 1 55 0
20852 1 0 12 0 0 0 1 38 1 56 0
32235 0 3 12 0 0 0 1 38 1 56 0
19388 1 0 6 1 0 0 0 45 1 57 0
26820 0 5 18 0 0 0 0 33 0 57 1
26795 0 0 7 1 0 0 0 44 1 57 0
50171 0 5 12 0 0 0 0 39 1 57 1
31702 0 3 12 1 0 0 1 39 1 57 0
36178 0 3 12 0 0 0 1 40 1 58 0
15160 0 4 8 1 0 0 1 45 0 59 0
12285 0 1 12 0 0 0 1 42 1 60 0
60152 0 5 16 1 0 0 0 38 1 60 0
29736 0 4 8 0 0 1 0 47 1 61 1
45976 0 2 12 0 0 0 0 43 1 61 1
18752 0 4 11 0 0 0 1 45 0 62 1
17626 0 3 12 0 0 0 1 45 1 63 0
19981 0 4 4 0 0 0 0 54 1 64 0