What is linear regression and how does it work?

What is linear regression and how does it work?

Linear regression is a statistical method used to model the relationship between a dependent variable and one or more independent variables. It assumes a linear relationship, meaning that changes in the independent variable(s) will result in proportional changes in the dependent variable.

Can you explain the difference between simple and multiple linear regression?

Sure! Simple linear regression involves one independent variable predicting a dependent variable, while multiple linear regression uses two or more independent variables to predict the dependent variable.

What are some common applications of linear regression?

Linear regression is commonly used in fields like economics for predicting sales, in biology for growth modeling, and in social sciences for analyzing relationships between variables.

How do you interpret the coefficients in a linear regression model?

The coefficients represent the change in the dependent variable for a one-unit change in the independent variable, holding other variables constant. A positive coefficient indicates a direct relationship, while a negative coefficient indicates an inverse relationship.