Linear Regression Analysis for Predicting Used Sedan Prices

a. What is the sample regression equation that allows us to predict the price of a sedan based on its age and mileage?

Determine the sample regression equation that enables us to predict the price of a sedan on the basis of its age and mileage.

a. Sample Regression Equation for Sedan Price Prediction

The sample regression equation that allows us to predict the price of a sedan based on its age and mileage can be calculated by fitting a linear regression model to the given data. The regression equation is typically of the form:

Price = Intercept + (Coefficient of Age * Age) + (Coefficient of Miles * Miles)

Regression analysis is a statistical technique used to model the relationship between a dependent variable (selling price of a sedan in this case) and independent variables (age and mileage of the sedan). By calculating the coefficients of age and mileage through regression analysis, we can predict the selling price of a sedan based on these factors. To determine the sample regression equation, we need to follow these steps:

1. Calculate Coefficients

Using the given data, perform regression analysis to calculate the coefficients of age and mileage in the regression equation.

2. Formulate Regression Equation

Once the coefficients are obtained, formulate the regression equation by substituting the coefficients and variables into the equation.

3. Interpret the Equation

The regression equation represents the relationship between age, mileage, and selling price of sedans. It allows us to make predictions about the price of a sedan based on its age and mileage.