Ans. Correlation and regression are both statistical techniques used to analyze the relationship between variables. However, they differ in their purpose and approach. Correlation measures the strength and direction of a linear relationship between two variables. It quantifies how closely the variables are related, ranging from -1 (perfect negative correlation) to +1 (perfect positive correlation). Regression, on the other hand, is used to model and predict the relationship between variables. It aims to find the best-fitting line (regression line) that minimizes the difference between the observed and predicted values. Regression also allows us to estimate the effect of one variable on another and make predictions based on the relationship.