Question

The main difference between simple linear regression and multiple regression is: Selected Answer: Multiple regression uses more than one explanatory variable, while simple linear regression only uses one. Answers: Multiple regression uses more than one response variable, while simple linear regression only uses one.

Simple linear regression uses more than one response variable, while multiple regression only uses one.

Multiple regression uses more than one explanatory variable, while simple linear regression only uses one.

Simple linear regression uses more than one explanatory variable, while multiple regression only uses one

. There is no obvious difference between these analyses. .

Answer 1

Simple Linear Regression:

Y = f(X)

Y -> Dependent/Response Variable

X -> Independent/Explanatory Variable

Multiple Linear Regression:

Y = f(X1, X2, X3,......)

Y -> Dependent/Response Variable

X1, X2, X3 ...... -> Independent/Explanatory Variables

In Simple Linear Regression, we have one explanatory variable and one response variable

In Multiple Regression, we have more than one explanatory variables and one response variable

So, answer is:

Multiple regression uses more than one explanatory variable, while simple linear regression only uses one

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