Linear Regression Model for Business Strategy

Abstract

This article is a case study that illustrates how a linear regression model can be implied in business strategy to find the relationship between each variable and advise price setting and revenue prediction. With the fast development of big data, a business can get a more thorough data set, so experiment in the real world is more reliable. The challenge is to clean, organize and detect wrong data. This paper aims to use the existing statistic modeling methods to make a business strategy for a company based on a relatively small data frame. R studio is used for all statistical calculations. This paper also examines the interaction effects for the centered and uncentered data set. The result of this study shows that price is negatively correlated to sales and advertising fees, and stores have a positive correlation. It also shows that centering makes a great difference in illuminating the collinearity of interaction terms. Finally, this article analyzes the estimation made by the marketing director and gives suggestions on business strategy in the end.