Final answer:
Linear regression in statistics is used to study the relationship between variables and determine the line of best fit. In a machine learning framework, linear regression is used as a predictive modeling algorithm to make predictions on new data.
Step-by-step explanation:
Linear regression is a statistical technique used to model the relationship between a dependent variable and one or more independent variables. In statistics, linear regression is used to study the relationship between variables and determine the line of best fit that minimizes the sum of squared differences between the observed and predicted values.
In a machine learning framework, linear regression is used as a predictive modeling algorithm. It is trained on a dataset with input features and corresponding output values, and the goal is to learn the relationship between the input features and the output values to make predictions on new, unseen data.
Machine learning algorithms often include additional techniques like regularization and feature engineering to improve the performance of linear regression models.