In statistics, a simple linear regression model uses a single variable to predict the result of the other variable.You may confuse it with linear regression but let us make it clear through this blog that they both are different. The other variable, meant B, is viewed as the response, outcome, or dependent variable. Simple linear regression is a statistical strategy that permits us to sum up and study connections between two continuous or quantitative variables: One variable, meant A, is viewed as the predictor, explanatory, or independent variable.
This blog talks about the concept of simple linear regression. You must be familiar with several terms of statistics and simple linear regression is one of them.
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