This course is suitable for young researchers or anyone who needs an understanding of introductory-level regressions analysis. Regression is widely use technique/tool to investigate the combined associations between one or more predictors and an outcome. This course takes you from the basics of types of regression to the formulation of a multiple linear regression model. 

Suppose you’re a sales manager of Tropical Fruits company and trying to predict next month’s demands for Papaya. Based on the usual trend analysis done by your department, you know that the required number of kilo's. Perhaps  there are many factors, from Weather to a competitor’s promotion, significantly affect the market demand. Research and Development department of the Tropical Fruit company has a new and improved model that can predict the demand considering these factors. People in your organization may also have a theory about what factor will have the biggest effect on sales. 

“More rain we have, more we grow.” 

“Six to eight weeks after the competitor’s promotion, sales rise up. ”     

Regression analysis is a way of mathematically/statistically sorting out which of those factor have effect on predicting the demand. It will answer the following questions: 

                        Which factors matter most? 

                        Which can we ignore?

                        How do those factors interact with each other?  

Similarly, Regression Analysis techniques have been used to address the issues in Health Sector, Financial Field, Industries, Weather forecasting, Management of transportation, Food Production, Agriculture and our day-to-day life.