Regression Analysis

 

Regression Analysis Regression analysis is the statistical method used to determine the structure of a relationship between two variables (single linear regression) or three or more variables (multiple regression). According to the Harvard Business School Online course Business Analytics,  regression is used for two primary purposes: 1.   To study the magnitude and structure of the relationship between variables 2.   To forecast a variable based on its relationship with another variable Both of these insights can inform strategic business decisions.  A regression is a statistical technique that relates a dependent variable to one or more independent (explanatory) variables. A regression model is able to show whether changes observed in the dependent variable are associated with changes in one or more of the explanatory variables. It does this by essentially fitting a best-fit line and seeing how the data is dispersed around this line. Regression helps economists and financial analysts in things ranging from asset valuation to making predictions. Once you’ve generated a regression equation for a set of variables, you effectively have a road-map for the relationship between your independent and dependent variables. If you input a specific X value into the equation, you can see the expected Y value. This can be critical for predicting the outcome of potential changes, allowing you to ask, “What would happen if this factor changed by a specific amount?”   For Example – Suppose a soft drink company wants to expand its manufacturing unit to a newer location. Before moving forward; the company wants to analyze its revenue generation model and the various factors that might impact it. Hence, the company conducts an online survey with a specific questionnaire.  After using regression analysis, it becomes easier for the company to analyze the survey results and understand the relationship between different variables like electricity and revenue – here revenue is the dependent variable. In addition to that, understanding the relationship between different independent variables like pricing, number of workers, and logistics with the revenue helps the company to estimate an impact of varied factors on sales and profits of the company.