Statistics - Multiple Regression Projects

Select variables for a multiple regression. You need to have at le ast four independent variables, Your

  1. Select variables for a multiple regression. You need to have at le ast four independent variables, Your model must make sense; each of the independent variables must logically have a possible impact on the dependent variable. Finally, your model cannot be identical to the model another group/individual is using for this assignment or the model used in the handouts. ( other document has variables in it)
  2. Test for violations of the assumptions of linearity, normality, homoskedasticity, and collinearity (in this order). Conduct both the graphic and statistical tests for linearity, normality, and homoskedasticity and the statistical test for collinearity.
  3. Correct (or attempt to correct) any violations to the assumptions of linearity, normality, and collinearity, and alter your model as appropriate.
  4. Fully interpret the final model.
  1. Describe the variables in your initial model and explain why you believe each independent variable would impact the dependent variable.
  2. Describe whether or not your initial model violated any of the assumptions and your attempts to address them. (Please note that you do not need to address violations of homoskedasticity.)
  3. Describe and interpret the final model.
Price: $19.04
Solution: The downloadable solution consists of 14 pages, 504 words and 12 charts.
Deliverable: Word Document



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