aðhvarfsgreiningu

Aðhvarfsgreiningu, or regression analysis in English, is a statistical method used to examine the relationship between a dependent variable and one or more independent variables. It aims to understand how changes in the independent variable(s) affect the dependent variable. The goal is to model this relationship and often to predict future values of the dependent variable based on known values of the independent variable(s).

There are various types of regression analysis, including linear regression, logistic regression, and polynomial regression, each suited for different types of data and relationships. Linear regression, for instance, assumes a linear relationship between variables and is often represented by a straight line. Logistic regression is used when the dependent variable is categorical, such as yes or no, true or false.

The process of regression analysis typically involves fitting a model to observed data. This is often done using techniques like the method of least squares, which minimizes the differences between the observed values and the values predicted by the model. Once a model is fitted, its performance is evaluated using statistical measures such as R-squared, which indicates the proportion of variance in the dependent variable that is predictable from the independent variable(s).

Regression analysis is a widely used tool in many fields, including economics, finance, social sciences, engineering, and medicine, for tasks such as forecasting, understanding causal relationships, and identifying key drivers of observed phenomena.