- A The Table Below Shows The Output Of Regression Analysis Of Salary Increment On Sex Quality Of Work And Experience Fo 1 (64.02 KiB) Viewed 28 times
- A The Table Below Shows The Output Of Regression Analysis Of Salary Increment On Sex Quality Of Work And Experience Fo 2 (8.38 KiB) Viewed 28 times
- A The Table Below Shows The Output Of Regression Analysis Of Salary Increment On Sex Quality Of Work And Experience Fo 3 (4.92 KiB) Viewed 28 times
a) The table below shows the output of regression analysis of salary increment on Sex, quality of work and experience for 24 respondents. There are also two categorical variables represented by D2 and D3 used to represent sex (Male and Female) and area of work (production, research and Sales). These categorical variables are shown below. Sex 1 Female = 0 otherwise D2=1 production = 0 Otherwise D3= 1 research = 0 Otherwise Coefficients Standardized Coefficients B Std. Error Beta Sig. (Constant) 74.269 99.589 SEX -158.308 60.132 -.485 3.589 Quality of .625 1.013 Work 12.495 Experience .203 11.606 D2 -71.501 64.269 -.213 D3 -28.657 58.362 -.081 a. Dependent Variable: Salary Increment i) Using the regression model, compute the salaries of male and female (4marks) ii) Interpret the coefficient of Sex (2marks) iii) Interpret the coefficient of Experience (2marks) iv) Test the significance of the variables (4marks) Model 1 Unstandardized Coefficients
c) Show how the model below Yi =B₁ + B₂Xi + ui, where Vare,=o7, can be transformed so that the Ordinary least squares methodology can be applied to it. (4marks)
d)State and explain the assumptions made in least squares methodology.