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Topics > Business > Multiple Predictors of Salary


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Multiple Predictors of Salary

Multiple Predictors of Salary
Jacob Otto
MSC 1201 8am Section
Professor Zangenah
Monday, August 11, 2003































Introduction

In this report, our goal was to determine the significant predictor variables in determining an employee’s annual salary. ... It gives information on each employee’s annual salary, gender, age, experience level, and training level. This report examines each variable’s effect on annual salary, and the significance of its effect.

Analyses and Methods

As is exhibited in appendix 1, the multiple regression analysis was done in MiniTab on all k predictors of salary, and it shows this regression equation for the data set:

Salary = 6109 + 8425 (gender) + 326 (age) + 1168 (experience) + 7769 (training level)


The first question that we ask is that of co-linearity. As shown in appendix 1, the VIF values for all relevant predictors (C3-C6) are all less than five. ... This is done to eliminate insignificant predictors one at a time, to judge their significance to the model. ... Through the above tests, we have confirmed that all the variables included in the stated model equation are significant to determining salary. ...
Summary and Conclusion
In conclusion, the model that was produced was a significant, valid, and reliable way in which to predict a person’s annual salary.


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