Prediction of Cement Sales Using the Linear Regression Model Equation Method (2022-2024): A Case Study of Building Material Retail Stores in Rattaphum District, Songkhla Province
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Abstract
This research aimed to develop and evaluate a simple linear regression model for forecasting monthly cement sales in Rattaphum District, Songkhla Province, using data from January 2022 to September 2024 (n=33). The analysis revealed the most suitable equation to be indicating a statistically significant decreasing trend (p < 0.001) in sales by an average of 7.35 sacks per month. The relationship between time and sales showed a moderate negative correlation (r = -0.6613). However, the model's explanatory power was limited, with R² = 0.437 (43.7%), suggesting that other factors not included (e.g., economic conditions, seasonality, competition) significantly influence sales. Furthermore, checks of the underlying assumptions revealed important limitations, particularly significant positive autocorrelation, a common issue when applying basic models to time series data. The derived equation was used to forecast future sales. While subject to these limitations, these forecasts can provide preliminary information for decision-making in production planning, inventory management, and marketing strategy development, provided they are considered alongside other factors and the model's constraints.
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