Collect the dependent variable and one or more independent variables
Clean the data and handle missing values or outliers
Choose the regression type
Define the regression equation
Estimate the coefficients using a fitting method
Compute predicted values from the fitted equation
Calculate residuals as actual values minus predicted values
Evaluate model fit using metrics such as R-squared, MSE, or RMSE
Test coefficient significance using t-tests or F-tests
Validate the model on separate data if available
Use the final model to make predictions