Linear regression
Linear regression is the most commonly used method of predictive analysis. It uses linear relationships between a dependent variable (target) and one or more independent variables (predictors) to predict the future of the target. The prediction is based on the assumption that the relationship between the target and the predictors is dependent or causal.
You can use linear regression models, for example, to analyze how previously advertisements are related to an increase in sales to decide about future advertisements. In this example, the dependent variable is sales, and the independent variable is advertisement expenses.
You can also predict, for example, gold prices, the exchange rates of currencies, or the effect of exercise frequency and diet methods on body weight.