**Question 1**: [15 points] Does choice of an undergraduate major affect level of satisfaction among MBA graduates? That was the question investigated by a business school accreditation association. A random sample was selected from the population of recent MBA graduates. Each subject classified into one of four groups (LibArts, Engineering, Business, Other) based on their undergraduate major. Your objective is to determine whether the average satisfaction level across the four undergraduate major populations differs. The data from this problem are contained in the file named **UgradMajor.xlsx**.

**Question 2**: [25 points] On January 28, 1986, the space shuttle Challenger exploded and seven astronauts were killed. Prior to the launch, when predicted atmospheric temperature was for freezing weather at the launch site, engineers for Morton Thiokol (the manufacturer of the rocket motor) prepared charts to make the case that the launch should not take place due to the cold weather. These arguments were rejected and the launch tragically took place. Upon investigation after the tragedy, experts agreed that the disaster occurred because of leaky rubber O-rings that did not seal properly due to the cold temperature. Data indicating the atmospheric temperature at the time of 23 previous launches and the O-ring damage index are given in the file **Challenger.xlsx**.

**I. **Identify your independent and dependent variables.

**II. **Use a linear regression model to find the regression equation. Report the equation.

**III. **Is your model significant?

**IV. **Interpret the meanings of and (coefficients) in the context of the problem.

**V. **Do you think that the engineers claim at Morton Thiokol was reasonable? Why or why not? State your null/alternative hypothesis for = 0.05 (both verbally and symbolically). Also briefly interpret the testing results.

** **

**Question 3**: [30 points] A person holding two or more jobs, one primary and one or more secondary, is known as a *moonlighter*. You are interested in finding out what factors determine the wages of moonlighters (the dependent variable). The file named **Moonlight.xlsx **provides the following data from a random sample of 318 moonlighters: Moonlighting wage (cents/hour), Primary wage (cents/hour), Age (in years), Urban (“U”=urban, “N”=nonurban) and High school graduate (“Y”=high school graduate, “N”=not a high school graduate). Primary wage and age are assumed to be continuous variables; the other two are assumed to be discrete. Based on these data:

**I. **What is our best estimate of the regression equation (including the specific estimates of all beta parameters) underlying these data?

**II. **Based on the regression equation, what is the expected moonlighting wage associated with a 43-year-old high school non-completer whose primary wage is $30/hour and lives in an urban area?

**III. **Can we be reasonably certain that there exists a relationship between (linear) primary wage and moonlighting wage (after controlling for all the other variables in the model) in the population?

**IV. **Can we be reasonably sure that the best-fitting straight line characterizing the relationship between moonlighting wage and primary wage differs by whether or not the person is a high school graduate? (In answering this question, the independent variables that you need to include in your analysis are primary wage and whether or not the person is a high school graduate).

Subject | Mathematics |

Due By (Pacific Time) | 08/07/2014 10:00 pm |

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