Applied Mathematics and Nonlinear Sciences
Journal license

Journal

Applied Mathematics and Nonlinear Sciences


Volume
& Issue

Volume 7, Issue 2


Published
on

July 15, 2022


Pages

409-416


DOI

Article

Mathematical Modeling and Forecasting of Economic Variables Based on Linear Regression Statistics

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Authors

Jiong Huang Affiliation:
School of Management and Economics, Kunming University of Science and Technology, Kunming, Yunnan, 650092, China
and Horiya Aldeeb Affiliation:
College of Administrative Sciences, Applied Science University, Bahrain


Abstract

Many economic variables are interdependent, restrictive, and influential. Finding the law of change between economic variables and influencing factors and expressing this law in mathematical expressions will bring great convenience to forecasting. A statistical analysis method that uses mathematical equations to determine the quantitative relationship between two or more variables. This is more commonly used when estimating and predicting the value of the dependent variable. The article analyzes the data on the National Bureau of Statistics website and uses the method of multiple linear regression to fit the graphs of economic indicators. Finally, the forecast data is analyzed in detail. We evaluated the modeling method of the prediction model and the credibility of the prediction data from a practical level.


Keywords

Linear regression analysis, Economic variables, Gross regional product, Mathematical modeling, 62J02


Citation

Huang, J. & Aldeeb, H. (2022). Mathematical modeling and forecasting of economic variables based on linear regression statistics. Applied Mathematics and Nonlinear Sciences, 7(2), 409–416. https://doi.org/10.2478/amns.2022.2.00023

Published by: Engineering Journals

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