Limitations of Regression Analysis

1. Regression analysis can't tell you the cause-and-effect relationship between independent variables and dependent variables – it only shows that a relationship exists. 2. Regression analysis may suffer from omitted variable bias, which occurs when the regression analysis does not include all factors that affect the dependent variable which could lead to incorrect conclusions. 3. Regression analysis assumes a linear relationship between the dependent and independent variables, if this is not the case then the regression results will be inaccurate. 4. Regression analysis is sensitive to outliers, which can significantly alter the results of the regression, therefore it is important to identify all possible outliers prior to running the regression. 5. Regression analysis is limited by its scope – it only allows for the examination of the relationship between a few variables at one time. This means that complex relationships may not be accurately reflected in the results. 6. Finally, regression analysis requires that the data used is clean and free of errors. If errors are present in the data, this can affect the accuracy and reliability of the results.