Lineaaranalüüsi

Lineaaranalüüsi, commonly known as linear analysis or linear regression in English, is a fundamental statistical technique used to model the relationship between a dependent variable and one or more independent variables. The core principle is to find a linear equation that best describes the observed data. This equation represents a line or hyperplane that minimizes the sum of squared differences between the observed values of the dependent variable and the values predicted by the linear model.

The simplest form is simple linear regression, which involves only one independent variable. The equation takes the form Y = a + bX, where Y is the dependent variable, X is the independent variable, 'a' is the intercept (the value of Y when X is zero), and 'b' is the slope (the change in Y for a one-unit change in X). Multiple linear regression extends this to include several independent variables, with the equation being Y = a + b1X1 + b2X2 + ... + bnXn.

Lineaaranalüüsi is widely applied across various fields, including economics, social sciences, engineering, and medicine, for tasks such as prediction, forecasting, and understanding causal relationships. Its simplicity and interpretability make it a powerful tool for data analysis and decision-making. However, it assumes a linear relationship between variables and can be sensitive to outliers.