Create a scatterplot of 4-year resale value

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  1. Create a correlation matrix for the following variables, paste it into your document, and list out the 3 strongest statistically significant correlations between different variables (give the variables and the correlation value)
    • 4-year resale value
    • Price in thousands
    • Engine size
    • Length
    • fuel efficiency
  2. Create a scatterplot of 4-year resale value on the y-axis and price in thousands on the x-axis. Paste it into your document. How would you describe the relationship shown?
  3. Run a regression with Price in thousands as the dependent variable and Length and Fuel efficiency as the independent variables. Give the regression model equation and R-square and explain which estimated coefficients appear to be statistically significant and how you know. How much faith would you have in these regression estimates and why?
  4. Run a regression with Price in thousands as the dependent variable and Horsepower, Length and Fuel efficiency as the independent variables. Give the regression model equation and R-square and explain which estimated coefficients appear to be statistically significant. Describe any changes in R-square or estimated coefficients from the regression in #3.
  5. Run a regression with 4-year resale value as the dependent variable and Horsepower, Length and Fuel efficiency as the independent variables. Give the regression model equation and R-square. Explain whether horsepower appears to have a bigger impact on the price of new cars or used cars and how you know. Refer to the regression results.

Reference no: EM133388709

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