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Part of a CFO's job is to determine the direction of the company and which divisions/projects should be expanded. This CFO selects a sample of 30 projects and wants to find out about the relationship between Profit (Y measured in 1000's) per project and number of Employee Hours (EmployHrs) involved in each project (measured in 100's), length of time to complete the project (Months) measured in months, whether the project was completed on time (Ontime=1 if on time and 0 otherwise), and then the type of construction project (Retail, Manufacturing, or Government). Retail =1 if it was a retail project, 0 otherwise. Manufacturing =1 if it was a manufacturing project and 0 otherwise, Government is omitted.
See the attached file for the regression and questions.
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The following problem provides an overview of regression analysis from how to interpret coefficients to writing out the regression equation and interpreting R2.
The independent variables are called predictors. You are trying to find the statistical relation of "profit" with these predictors taken all at once in a grouped manner, as if they all have something to do with the behavior of your dependent variable called "profit". The tables in the question file attachment provide the information needed in order to answer the questions as follows:
In the column identified as "coef" are the numeric values for the coefficients for a regression formula which has the general expression such as:
(profit) = (constant) + (coef1)(EmployHrs)+(coef2)(Months) +(coef3)(Ontime)+(coef4)(Retail)+(coef5)(Manufact)
As you can see these ...
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