Reference no: EM132738025
Hypothesis Testing-Regression (Partly from Keller and Warrack, 5th Ed.)
When setting up their rates policy, Automobile Insurance companies usually take in consideration several factors like age, marital status, vehicle type, profession, and distance driven yearly. To this end one of these companies conducted a survey on a sample of 200 people (100 male and 100 female) to investigate the effect of gender on driving habits. The number of miles driven by each person last year was recorded, as well as the distances of their homes to the Capital. The resulting dataset is stored in the third sheet "Data" of this Group Work Excel file (MTH203-STA201_Group Work-Fall 2020.xlsx). The variables used are defined as follows:
Column 1: Miles Driven (in miles).
Column 2: Distance to Capital (in miles).
Column 3: Gender Code (1 = male, 2 = female).
"a. Use appropriate Excel Descriptive Statistics tools to summarize this data (describe "Miles Driven" and "Distance to Capital" overall and for each gender separately).
b. The company believes that on the average, most people drive more than 10,000 miles per year. On the basis of the entire sample, discuss this issue based on a hypothesis test for the population mean number of miles driven per year at the 5% level of significance.
c. On the other hand, the company believes that on the average, the yearly number of miles driven by males is more than that for females. Repeat the test of hypothesis of part (b.), but for each gender separately. Based on the outcomes of these two tests approve or disapprove the company's belief.
d. Use a test of hypothesis to check whether there is a significant linear relationship between "Miles Driven" and "Distance to Capital" at the 5% then the 1% level of significance. Based on the value of R-Squared (Coefficient of Determination), is the regression of "Miles Driven" on "Distance to Capital" a good model? Explain."
Attachment:- Hypothesis Testing-Regression.rar