In the context of regression, what does R-squared indicate?

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Question: In the context of regression, what does R-squared indicate?

Options:

Correct Answer: The proportion of variance explained by the model

Solution:

R-squared indicates the proportion of variance in the dependent variable that can be explained by the independent variables in the model.

In the context of regression, what does R-squared indicate?

In the context of regression, what does R-squared indicate?

Step 1: Understand that regression is a method used to predict a dependent variable based on one or more independent variables.
Step 2: Know that the dependent variable is what you are trying to predict, while independent variables are the factors that influence it.
Step 3: R-squared is a statistical measure that tells us how well the independent variables explain the variation in the dependent variable.
Step 4: R-squared values range from 0 to 1. A value of 0 means the independent variables do not explain any of the variation, while a value of 1 means they explain all the variation.
Step 5: If R-squared is, for example, 0.75, it means that 75% of the variation in the dependent variable can be explained by the independent variables.

R-squared – R-squared measures the proportion of variance in the dependent variable explained by the independent variables.