Validation of a predictive model using linear regression and anova
DOI:
https://doi.org/10.61273/neyart.v4i4.221Palabras clave:
Forecasting, Mathematical model, Planning, Quantitative methods, Statistical analysisResumen
This paper verifies a simple linear regression prediction model, whose function is to predict in advance the monthly number of new customers of an institution. This verification uses the institution's full five-year historical monthly customer growth data. The tools used to verify the reliability of the model are the commonly used Excel, and the professional statistical software Minitab 19. The specific verification method is analysis of variance, which is the ANOVA mentioned in studies. After the verification, the model draws a clear conclusion: the correlation between the passage of time and customer growth is very high. The three statistical values supporting this conclusion are the coefficient of determination R²=0.8094, the F-value=246.37, and the p-value≈0. Finally, the authors of the paper propose that in the future, these variables that may affect customer growth can all be incorporated into the model to carry out multiple regression analysis, to further help the institution formulate more reasonable decisions.
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