Most of the things in this world are dependent on one or more factors. It can be reflected almost everywhere. Generally, we all know which thing is dependent on which all factors but where we lack is to try to find the level or strength of dependency or you can say correlation between the two. Regression Analysis is here for rescue which helps in defining the relationship between one or more independent variables with the dependent variable and the prediction of the dependent variable based on these independent variables. Factors can be dependent or independent depending upon the situation.
Regression Analysis helps in detecting which factor has the most impact, the least impact, or no significant impact on the dependent variable or simply detecting the strength or predictors.
It is widely used for predictions and forecasting. By defining the relationships between the dependent factor and one or more independent variables, regression analysis helps in the prediction of the dependent variable based on the values of the independent factors involved using the relationship defined. Also, forecasts can be made both ex- ante (using information of the past) and ex-post (using predicted information of future) using the same relationship. The dependent variable is called the “target” while the independent ones as “predictors”.
There are endless scenarios in both business and real-life where regression analysis can be put into use. Everything from the amount of homework to be received by a student to the sales made by a company can be predicted using the widely used analysis called Regression Analysis.
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Written by Sarthak Goel ( p B.com (hons) from Hindu College and 4 Actuarial Papers passed from IFOA and IAI)
Edited by Ayush Maskara ( Actuarial Management Trainee at WNS )