Question

Which of the following situations describes a multiple regression? a.) Using the average salary of a homeowner and the number of bedrooms to predict the listing price and square footage of a home. b.) Using the listing price of a home to predict the annual salary of a homeowner, the number of bedrooms, and the square footage. c.) Using the average salary of a homeowner, the number of bedrooms, and the square footage to predict the listing price of a home. d.) Using the square footage to predict the listing price of a home.

Answer 1

c.) Using the average salary of a homeowner, the number of bedrooms, and the square footage to predict the listing price of a home.

Step-by-step explanation:

Got it right on the test.

Answer 2

Answer:C. Using the average salary of a homeowner, the number of bedrooms, and the square footage to predict the listing price of a home.

Step-by-step explanation:

Multiple regression is simply a simple linear regression extension. Multiple regression is used when the researcher wants to forecast the value of a particular variable which is based on the value of other variables which are usually two or more.

With regards to the above question, the situation that describes the multiple regression is option C "Using the average salary of a homeowner, the number of bedrooms, and the square footage to predict the listing price of a home".

There are three variables that are involved which are the average salary of homeowner, the number of bed rooms and also the square feet to predict the listing price of the home.