Correlation evaluates the degree and direction of a linear relationship between two variables, with values ranging from -1 (perfect negative) to +1 (perfect positive). It is assessed using a correlation coefficient.
Regression, especially linear regression, is the process of modelling the connection between a dependent variable and one or more independent variables. It presents an equation (y = mx + b) that predicts the dependent variable based on the independent variables. Correlation suggests relationship, whereas regression implies causality and anticipates results.
Correlation assesses relationships, whereas regression allows for prediction and causal conclusions. visit Durga Online Trainer for free Demo Class.