Asked by Arely Villalobos on Jul 12, 2024

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What is the major difference between a simple linear regression model and a multiple linear regression model?

A) In simple linear regression you can only have quantitative explanatory variables.In multiple linear regression you can have quantitative and categorical explanatory variables.
B) In simple linear regression you have many explanatory variables.In multiple linear regression you have only one explanatory variable.
C) In simple linear regression you have only one explanatory variable.In multiple linear regression you can have many explanatory variables.

Simple Linear Regression

A statistical technique that models the relationship between two variables by fitting a linear equation to observed data, with one independent variable explaining the variation in the dependent variable.

Multiple Linear Regression

An analytical approach in statistics that uses a linear equation to define how a dependent variable is related to two or more independent variables based on observed data.

  • Differentiate between simple and multiple linear regression models.
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Stephanie AbernathyJul 17, 2024
Final Answer :
C
Explanation :
The major difference between a simple linear regression model and a multiple linear regression model is that in a simple linear regression model you can have only one explanatory variable, while in a multiple linear regression model you can have many explanatory variables. Therefore, choice C is the correct answer.