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Regression model for age of a car and its selling price.

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The owner of Maumee Ford-Mercury wants to study the relationship between the age of a car and its selling price. Listed below is a random sample of 12 used cars sold at Maumee Motors during the last year.

a. If we want to estimate selling price based on the age of the car, which variable is the dependent variable and which is the independent variable?
b. Draw a scatter diagram. [First, enter age and selling price data in Excel. Use Megastat Excel, correlation/regression, scatterplot function or Excel, Tools, Data Analysis, Regression function].
c. Determine the coefficient of correlation. Interpret the result. [use Megastat Excel, correlation/regression, correlation matrix].
d. Determine the coefficient of determination. Interpret the result.
e. Using regression coefficients table, write the simple linear regression equation that represents the relationship between age of car and its selling price.
f. Based on the regression equation, what will be the values of cars owned for the next 10 years

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The solution provides step by step method for the calculation of regression model for age of a car and its selling price. . Formula for the calculation and Interpretations of the results are also included. Interactive excel sheet is included. The user can edit the inputs and obtain the complete results for a new set of data.

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We want to determine the factors that affect selling prices of Ford Mustangs. The statistical analysis of the data involves hypothesis testing and multiple-regression analysis. The data is attached.

Analyses that you'll want to do are:
1. Test the hypothesis that mean price does not depend on whether the car is a convertible. (Interpret your answer in nontechnical terms) Then, perform the same hypothesis for transmission type, presence or absence of air conditioning, GT model or not, and private versus dealer ownership.
2. Perform a hypothesis test that mean selling price does not vary with color.
3. Find a reasonable multiple regression model of PRICE on the other variables available in the data set. (Which variables are significant, which are not? How do the significant variables affect the PRICE?)

You will want to prepare a report of your findings. Show how the findings could use your information to set prices on other cars in the near future.

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