Multiple Choice
A student wants to create a multiple regression model to predict the height of a child with the variables age, length of foot, and shoe size. Using logic, are any of the variables irrelevant, and, if so, which one(s)?
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12. Regression
Multiple Regression - Excel
Multiple Choice
A student wants to create a multiple regression model to predict the price of a used car with the variables number of prior accidents, original sales price of car, and number of miles on the car. Using logic, are any of the variables irrelevant, and, if so, which one(s)?
A
All variables are relevant.
B
All variables are irrelevant.
C
Number of miles on the Car.
D
Original sales price of car.
Verified step by step guidance1
Step 1: Understand the purpose of multiple regression, which is to predict a dependent variable (here, the price of a used car) using several independent variables (number of prior accidents, original sales price, and number of miles on the car).
Step 2: Consider the logical relationship between each independent variable and the dependent variable. For example, the number of prior accidents likely affects the car's price because accidents can reduce value.
Step 3: Evaluate the original sales price of the car as a predictor. Since the starting price influences the resale value, it is logically relevant to predicting the used car price.
Step 4: Assess the number of miles on the car. Mileage typically impacts the car's wear and tear, which in turn affects its price, making it a relevant variable.
Step 5: Conclude that all three variables have a logical connection to the price of a used car, so none of them are irrelevant for the multiple regression model.
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