Application of Multiple Linear Regression on Sales Prediction

Chen Dong

doi:10.54097/9fbpvy50

Authors

Chen Dong

DOI:

https://doi.org/10.54097/9fbpvy50

Keywords:

Sales Prediction, Multiple Linear Regression, least square method.

Abstract

Hitherto, companies still facing issues of pricing and allocation of promotional funds. Some evidence already shows the relationship between the sales of the product and three elements which include price, in-store spending, and online advertisement spending. This project aims to predict sales to determine the equation between these factors to help companies maximize the efficiency of promotional funds and balance the product's price and its sales. With the use of multiple linear regression and the least square method, predicted sales can be indicated. This is done through using both the R-square and graph the R-square to evaluate the equation between sales and the three factors mentioned earlier, discovering the fitness of equation is 0.8 (the upper limit is 1) according to the R-square and the trend of predicted values meet the observed values according to the graph. This finding can be used to predict the sales trend for the product and help the enterprise manage the allocation of promotional funds.

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