regressioen

Regressie is a statistical method used to model the relationship between a dependent variable and one or more independent variables. The goal of regression analysis is to understand how changes in the independent variables affect the dependent variable. This can be used for prediction, forecasting, or to understand the underlying relationships in data.

There are several types of regression analysis, with linear regression being the most common. In simple linear regression, a straight line is fitted to the data points, representing the best linear approximation of the relationship. Multiple linear regression extends this to include more than one independent variable, allowing for a more complex model.

Other forms of regression exist, such as logistic regression, which is used when the dependent variable is binary (e.g., yes/no, success/failure). Polynomial regression models can capture non-linear relationships by fitting a curve to the data. The choice of regression model depends on the nature of the data and the research question.

Regression analysis involves fitting a model to observed data and then evaluating its performance. This typically includes assessing the goodness of fit, such as R-squared, which indicates the proportion of variance in the dependent variable explained by the independent variables, and examining the statistical significance of the model's coefficients. The accuracy of the predictions made by a regression model is crucial for its practical application.