2. It is claimed that it's better to hire a manager from outside a firm than promote one from within. An analyst at a firm justifies this claim by showing that average performance evaluations tend to be significantly higher for managers hired from outside the firm compared with those promoted from within. Look at the below graph of salary versus performance evaluation (on a scale where 200 is the highest possible performance evaluation score) for managers at the same level at the firm. Is it true that average performance evaluation is higher for managers hired from outside the firm compared with those promoted from within? What other stories does this graph tell?

11. A manager would like to know which of the following factors has the strongest link to the salary an employee earns: age, gender, experience, time at the firm, or education. Looking at the file cmployees.xls, what do you conclude?

14. For each of the fifty states if you look at the state average income and the percentage of people in that state who are foreign-born immigrants, you will see a positive correlation. Does this mean immigrants tend to earn more than other people? Or does it mean immigrants improve a state's economy? If not, what could explain the correlation?

6. Production costs for a large number of previous orders of varying size for a product are in the file production.xls. An analyst computes the production cost per unit in each order, and averages these to get $50. Using this he gives a cost estimate of $5,000 for a new order for 500 units. Is this a reasonable cost estimate? Explain why or why not. Looking at the data in the file, can you give a better cost estimate?

7. A manager would like to know the relationship between the billable hours spent on a job and the total cost of the job including materials. The file jobs.xls contains the data. Summarize the relationship.

Case Study: The case involves the decision to locate a new store at one of two possible sites. The decision will be based on estimates of sales potential, and for this purpose, you will need to develop a multiple regression model to predict sales. Specific case questions are given in the textbook and the necessary data is in the file named pamsue.xls .

Content of the report consists of your answers to the case questions, plus computer output(s) to support your answers. Please keep the entire report - including computer outputs - under 8 printed pages. Thus, you write up should be concise, and you need to be selective in deciding which computer outputs to include. You can use your discretion in formatting your write up, but use good writing practices and try to make it look professional.

The data file pamsue.xls has 33 columns and 250 rows. The first row consists of column labels, which are self-explanatory, but sometimes their units are not. For example, annual sales are given in column AE in thousands of dollars, and selling areas are given in column AD in thousands of square feet.

Competitive types of store locations appear in column AG with the label comtype . This is a qualitative (categorical) variable with 7 categories. As explained in Section 9 of Chapter 11, you can use PivotTable or the IF function in Excel to create dummy variables to represent a qualitative variable.

To reduce the model building time and effort, you can use the Excel add-in for stepwise regression. This also has the added benefit of not requiring the data for X variables to be next to one another in a contiguous range.

When you feel that you found a reasonable model, do not forget to check model assumptions. Then, write up your report to answer the case questions, and attach the most relevant computer outputs you choose as exhibits (copying and pasting from Excel to Word should work fine for this purpose).

Price: $27.78

Solution: The downloadable solution consists of 14 pages, 1378 words and 18 charts.
Deliverable: Word Document