MIS 403 - Business Analytics Linear Regression Toyota Corolla Dataset. In this dataset, we are interested in the following variables: Variable Description Price Offer price in euros Age Age in months...

MIS 403 - Business Analytics Linear Regression Toyota Corolla Dataset. In this dataset, we are interested in the following variables: Variable Description Price Offer price in euros Age Age in months as of August 2004 Kilometers Accumulated kilometers on odometer Fuel Type Fuel Type (Petrol, Diesel, CNG) HP Horsepower Metallic Metallic Color (yes = 1, no = 0) Automatic Automatic (yes = 1, no = 0) CC Cylinder volume in cubic centimeters Doors Number of Doors QuartTax Quarterly road tax in Euros Weight Weight in Kilograms The objective of this analysis is to determine which variables can predict the price of Toyota Corolla cars. To do this, a predictive model is developed. The model used for this analysis is a multiple linear regression model. The model is suitable since: 1. The response variable is a continuous variable. 2. It is assumed that the predictor variables share a linear relationship with the response variable. 3. The variables are normally distributed. In this dataset, the following alternate hypotheses are made, assuming that the response variable is price and the other variables are predictor variables: H1 Age is negatively related to Price H2 Kilometers are negatively related to Price H3 Fuel types will have an impact on the Price H4 Horsepower will have a positive relationship with Price H5 Metallic color will have a increase the Price H6 Automatic cars will increase the Price H7 CC will have a positive relationship with Price H8 Doors will have a positive relationship with Price H9 QuartTax will have a positive relationship with Price H10 Weight will have a positive relationship with Price