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Equations for a Regression Analysis

Our analysis reviews faculty salaries to see if there is in fact a substantial salary difference based upon gender. We have collected data from 1,446 random institutions across the United States. We have obtained salary information for both men and women faculty members, separately, within public, private and church-related institutions. The salary information that we have accumulated is further dissected by level of the institution and rank of the male/female faculty member at those institutions. The three levels that we are assessing are: Doctoral, Master's, and Baccalaureate Programs. The ranks that we are assessing are as follows: Full Professor, Associate Professor, Assistant Professor, and Instructor. Our hypothesis states that the salary gap between men and women is a result of women choosing fields that pay slightly less on overall average (i.e. social science versus engineering) rather than because of their gender alone. Does the data support or deny the hypothesis?

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Our analysis reviews faculty salaries to see if there is in fact a substantial salary difference based upon gender. We have collected data from 1,446 random institutions across the United States. We have obtained salary information for both men and women faculty members, separately, within public, private and church-related institutions. The salary information that we have accumulated is further dissected by level of the institution and rank of the male/female faculty member at those institutions. The three levels that we are assessing are: Doctoral, Master's, and Baccalaureate Programs. The ranks that we are assessing are as follows: Full Professor, Associate Professor, Assistant Professor, and Instructor. Our hypothesis states that the salary gap between men and women is a result of women choosing fields that pay slightly less on overall average (i.e. social science versus engineering) rather than because of their gender alone. Does the data support or deny the hypothesis?

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