USING STATISTICAL MODELS IN FORECASTING ECONOMIC INDICATORS USING THE R STUDIO PROGRAM

Authors

  • I.K. Kho'jakulov "Tashkent Institute of Irrigation and Agricultural Mechanization Engineers" National Research University 4th year student of the Faculty of Economics, Department of Statistics

Keywords:

R Studio, economic indicators, statistical modeling, forecasting, time series analysis, ARIMA, exponential smoothing, economic planning, predictive analytics.

Abstract

This study investigates the application of statistical models for forecasting economic indicators using R Studio. The research focuses on time series analysis, including ARIMA and exponential smoothing methods, to predict GDP, inflation, and exchange rates. The study demonstrates how R Studio’s data analysis and visualization tools enhance the accuracy and efficiency of economic forecasts. The results are valuable for policymakers, economists, and businesses for strategic planning, resource allocation, and decision-making.

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References

Hyndman, R.J., Athanasopoulos, G. Forecasting: Principles and Practice. Otexts, 2018.

Shumway, R.H., Stoffer, D.S. Time Series Analysis and Its Applications. Springer, 2017.

Hyndman, R.J., Khandakar, Y. Automatic Time Series Forecasting: The forecast package for R. Journal of Statistical Software, 2008.

James, G., Witten, D., Hastie, T., Tibshirani, R. An Introduction to Statistical Learning with Applications in R. Springer, 2013.

Grolemund, G., Wickham, H. R for Data Science. O’Reilly Media, 2017.

Kuznetsov, A. Econometrics and Forecasting in R. Moscow: Finance, 2020.

Sharipov, S. Using Statistical Models in Economic Forecasting. Tashkent, 2021.

Moore, M.G., Kearsley, G. Distance Education: A Systems View of Online Learning. Belmont: Wadsworth, 2011.

Hyndman, R.J., Athanasopoulos, G. Time Series Data Analysis in R: Practical Applications. Otexts, 2020.

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Published

2026-02-04

How to Cite

I.K. Kho'jakulov. (2026). USING STATISTICAL MODELS IN FORECASTING ECONOMIC INDICATORS USING THE R STUDIO PROGRAM. Journal of Applied Science and Social Science, 16(02), 30–35. Retrieved from https://www.internationaljournal.co.in/index.php/jasass/article/view/3145

Issue

Vol. 16 No. 02 (2026): Volume 16 Issue 02

Section

Articles

License

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