1. Multiple Regression
   1. Collect data ( \(n\ge 30\) ) on a quantitative dependent variable and three explanatory variables. At least one may be qualitative.
   2. Estimate a first order, multiple regression model and include the following in the Report Pad of the Minitab Project file,
      1. all relevant data sources,
      2. results of the overall F test (remember that the P value for the overall F test should be less t han .05) ,
      3. results of the individual t tests, and
      4. an explanation of each statistically significant coefficient.
   3. Determine the best model to fit your dependent variable,
      1. a first-order multiple regression model, or
      2. a second-order (quadratic) multiple regression model,
         by using an appropriate statistical test.
   4. In addition to the results from "B" (above), include the following in the Report Pad,
      1. the name and results of the test used to determine "C," and
      2. the conclusion regarding your choice of either model C1 or C2 (above).

III . Logistic Regression

A. Collect data ( \(n\ge 30\) ) on a binary dependent variable and at least three explanatory variables. At least one of the explanatory variables has to be qualitative.

B. Do a logistic regression in Minitab ( remember the null hypothesis that all slopes are zero should be rejected at .05 level and there should be no convergence issues/errors in the program) .

C. Include the following in the Report Pad of the Minitab Project file,

1. the data with all relevant sources,
2. the output of the logistic regression,
3. a discussion about the statistical significance of each explanatory

variable and an explanation of the meaning of each relevant odds ratio (in the Report Pad).

D. Email the above in a Minitab Project file to Lonnie.K.Stevans@hofstra.edu .

Price: $25.96

Solution: The downloadable solution consists of 10 pages, 1596 words and 7 charts.
Deliverable: Word Document