Layoffs at G&P

A large firm located in the northeast portion of the U.S. is planning to announce a significant layoff plan. The specific sector of the company where the layoffs will occur spans all levels of employment which includes employees in R&D, sales and manufacturing. The employees targeted have various levels of education with various levels of tenure with the company.

In anticipation of the layoffs, company officials want to provide as much information to those targeted as possible with respect to future employment in the area. Officials want to provide the employees with realistic expectations on what they are facing as they search for subsequent employment. Thus, they have obtained data from the local unemployment office. The data contains 55 people that were recently employed after going through a similar situation. The variables are:

1. The number of w eeks the person was unemployed. (# of weeks)
2. The age of the person that was unemployed. (# of years)
3. The amount of educ ation that the person possesses. (# of years of education: 12-high school, 14-associates degree, etc.)
4. Whether the person was married or not. (1-married/ 0 not married)
5. Whether the person was the head of the household. (1 head / 0 not head)
6. The tenure with the person’s previous employer. (Years)
7. The person’s weekly pay rate at the last position. ($/week)
8. Whether the person was in management . (1-yes / 0-no)
9. Whether the person was in sales . (1-yes / 0-no)
10. The gender of the person. (1-female / 0-male)

Case Deliverables:

Please submit an Executive Summary of the findings from your data analysis. Also, in the executive summary, provide the company any advice that you can based on the data that you analyzed. Again, don’t base your advice on your feelings, but purely on the suggestions and conclusions drawn from the data. This section should be somewhat concise and to the point.

Following the executive summary, I want you to discuss your findings in terms of multiple regression model development. Obviously, the number of weeks of unemployment is the most important thing to the ones that will be affected. Thus, I would like for you to first determine if any of this data has any predictive value for estimating the number of weeks the person should expect to be unemployed. Follow the 5-step process that I use in my lecture for model building and model adequacy.

Use any of the descriptive statistics tools that we used in the first portion of the class, such as bar charts, histograms, scatter plots, etc., to make your case. Provide accurate interpretations of your findings and try to explain them in simple terms.

In addition to your case write-up, I would like for you to submit your MINITAB work as well. Please perform and submit all of your data analysis work in one project file. Cut and paste the appropriate test results in the write-up. Your write-up should include all the information, so I shouldn’t have to look at your project file unless I have a question about your methods.

Price: $19.36

Solution: The downloadable solution consists of 9 pages, 1036 words and 5 charts.
Deliverable: Word Document