Regression techniques are statistical methods used to understand the relationship between a dependent variable and one or more independent variables. These techniques help in predicting outcomes and identifying trends by fitting a mathematical model to the data. Common types include linear regression, logistic regression, and polynomial regression, each serving different types of data and relationships. In linear regression, the relationship is modeled as a straight line, while logistic regression is used for binary outcomes, predicting probabilities. Polynomial regression allows for more complex relationships by fitting curves. Overall, regression techniques are essential tools in data analysis and forecasting.