1. According to the existing data and the relationship between independent variables and dependent variables, the regression equation is initially established.

2. Find a reasonable regression coefficient.

3, correlation test, determine the correlation coefficient.

4. After meeting the requirements of correlation, the obtained regression equation can be combined with specific conditions to determine the future situation of things and calculate the confidence interval of predicted values.

Regression analysis method

Regression analysis refers to an analysis method that uses the principle of data statistics to mathematically process a large number of statistical data, determines the correlation between dependent variables and some independent variables, establishes a regression equation with good correlation, and extrapolates and predicts the future changes of dependent variables.

According to the number of dependent variables and independent variables, it is divided into: univariate regression analysis and multivariate regression analysis; According to the functional expressions of dependent variables and independent variables, it can be divided into linear regression analysis and nonlinear regression analysis.

Determine whether there is correlation between variables, and if so, find out the mathematical expression; According to the value of one or more variables, predict or control the value of another variable or variables, and estimate the accuracy of such control or prediction.