Version 1
: Received: 8 March 2024 / Approved: 12 March 2024 / Online: 14 March 2024 (05:28:48 CET)
How to cite:
Melesse, M.T.; Delele, G.M. Predicting and Analyzing Rainfall Patterns in Ethiopia Using Linear Regression Modeling. Preprints2024, 2024030679. https://doi.org/10.20944/preprints202403.0679.v1
Melesse, M.T.; Delele, G.M. Predicting and Analyzing Rainfall Patterns in Ethiopia Using Linear Regression Modeling. Preprints 2024, 2024030679. https://doi.org/10.20944/preprints202403.0679.v1
Melesse, M.T.; Delele, G.M. Predicting and Analyzing Rainfall Patterns in Ethiopia Using Linear Regression Modeling. Preprints2024, 2024030679. https://doi.org/10.20944/preprints202403.0679.v1
APA Style
Melesse, M.T., & Delele, G.M. (2024). Predicting and Analyzing Rainfall Patterns in Ethiopia Using Linear Regression Modeling. Preprints. https://doi.org/10.20944/preprints202403.0679.v1
Chicago/Turabian Style
Melesse, M.T. and Gezahegn Mulusew Delele. 2024 "Predicting and Analyzing Rainfall Patterns in Ethiopia Using Linear Regression Modeling" Preprints. https://doi.org/10.20944/preprints202403.0679.v1
Abstract
With the use of linear regression modeling, this study sought to forecast and analyze rainfall patterns in Ethiopia. The dataset included historical rainfall data as well as pertinent independent variables. The R-squared score and mean squared error (MSE) were used to assess the effectiveness of the linear regression model. The results showed that the model's ability to forecast and analyze rainfall patterns was not very good. Only around 5.3% of the variance in rainfall could be explained by the chosen independent variables, according to the R-squared score of 0.053. This low number indicated that there was little correlation between the selected variables and rainfall, and that a sizable percentage of the variation in the dependent variable was not captured by the model. The model's accuracy in forecasting rainfall was shown to be quite low by the MSE error, with significant squared discrepancies between the expected and actual amounts. These results support the notion that the linear regression model as it is now designed is not appropriate for studying or forecasting Ethiopia's rainfall patterns. Alternative modeling approaches, the inclusion of other pertinent factors, and the assurance of the availability of high-quality data that faithfully captures the intricate dynamics of rainfall in the area all require more investigation.
Keywords
Rainfall patterns; Ethiopia; Linear regression modeling; R-squared score; Mean squared error
Subject
Computer Science and Mathematics, Computer Science
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
