Linear correlation and simple linear regression

Linear correlation and simple linear regression

1. Linear connection and simple linear regression are statistical methods that study the linear relationship between two variables. Before delving into each of them.

2. It takes values between (-1, +1], where +1 is a perfect positive linear correlation and -1 is a perfect negative linear correlation.

   • It is a measure independent of the scales on which the variables are measured.
     • Doesn't change if transformations are applied to the variables
     • It doesn't take into account that the variables are dependent or independent

3. Linear connection and simple linear regression are statistical methods that study the linear relationship between two variables. Before delving into each of them.

   • Correlation quantifies how related two variables are, while linear regression consists of generating an equation (model) that, based on the relationship between both variables

4. Variable Types

   • Dependent variable/response variable
   • Covariates/Independent Variables/Regression Variables

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