Quantitative Business Analysis Case Study

Quantitative Business Analysis Case Study

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Quantitative Business Analysis Case Study

There are numerous variables that are believed to be predictors of combined (city and highway) fuel efficiency – number of cylinders, engine displacement, transmission type, number of gears, carline class.  The information in the Case Study No. 2 Fuel Efficiency Data .xlsx file pertains to a random sample of 2018 vehicle data.

  1. Develop a multiple linear regression model to predict a vehicle’s combined fuel efficiency-based engine displacement, transmission type, and number of gears as the predictor variables.
  1. Write the regression equation.
  2. Discuss the statistical significance of the model using the appropriate regression statistic at a 95% level of confidence.
  3. Discuss the statistical significance of the coefficient for each independent variable using the appropriate regression statistics at a 95% level of confidence.
  4. Discuss the statistical significance of the coefficient for each independent variable using the appropriate regression statistics at a 90% level of confidence.

Quantitative Business Analysis Case Study

  1. Develop a multiple linear regression model to predict a vehicle’s combined fuel efficiency-based number of cylinders, transmission type, and number of gears as the predictor variables.
  2. Write the regression equation.
  3. Discuss the statistical significance of the model as a whole using the appropriate regression statistic at a 95% level of confidence.
  4. Discuss the statistical significance of the coefficient for each independent variable using the appropriate regression statistics at a 95% level of confidence.
  5. Interpret the coefficient for each independent variable.
  6. What percentage of the observed variation in combined highway fuel efficiency is explained by the model?
  7. Predict the combined fuel efficiency for a vehicle that has 4 cyclinders, 6 gears, automatic transmission and is carline class 6

Compare the regression statistics for the multiple regression models from questions 1 and 2 above. Which model is the preferred model at a 95% level of confidence?  Use the Significance F values, p-values for the independent variables, R-squared or Adjusted R-squared values (as appropriate), and standard errors to explain your selection.

Prepare a single Microsoft Excel file to document your regression analyses.  Prepare a single Microsoft Word document that outlines your responses for each portion of the case study.  Upload BOTH your Excel and Word files for grading via the Canvas submission link. Quantitative Business Analysis Case Study

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