Regression analysis is a statistical method used to examine the relationship between one dependent variable and one or more independent variables. The goal is to model and quantify the relationship, allowing for predictions or estimations of the dependent variable based on the values of the independent variables. In simple terms, regression analysis seeks to understand how changes in the independent variables are associated with changes in the dependent variable.

There are two main types of regression analysis:

1. Simple Linear Regression: Involves one independent variable and one dependent variable, and it fits a straight line (linear equation) to the data points.
2. Multiple Linear Regression: Involves more than one independent variable and one dependent variable. It extends the concept of simple linear regression to multiple dimensions, fitting a hyperplane to the data.

The regression equation expresses the relationship mathematically, and the coefficients in the equation provide information about the strength and direction of the relationships between variables. Regression analysis is widely used in various fields, including economics, finance, biology, and social sciences, for making predictions, understanding patterns, and identifying significant factors influencing the dependent variable.