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JRRS LASU

Application of Mathematical Modelling in Sales Forecast Using Time Series

Authors: Yakub Tunde OYEB1, Azeez SULAIMON2, Abdulafeez Olalekan ABDULKAREEM1, Kazeem AdekunleSHONIBARE1,

Affiliations: 1. Department of Mathematics, Faculty of Science, Lagos State University, Nigeria
2. Department of Mathematics, Faculty of Science, National Open University of Nigeria (NOUN)

Abstract

Sales forecasting is a crucial aspect of business management, which involves predicting future sales based on historical data and market trends. Accurate sales forecasts are essential for effective decision-making, such as inventory management, production planning, and resource allocation.
This study explores the application of mathematical modelling in sales forecasting. A case study approach was used to demonstrate how mathematical modelling can be deployed to develop accurate sales forecasts. Specifically, historical sales data and market trends were used to develop mathematical models, including regression analysis, and time series analysis, to predict future sales.

Keywords

Seasonal decomposition Domain expertise Exponential smoothing SARIMA ARIMA LSTM and STL