The Use of Data Analysis to Analyze Education Trends in Azerbai-jan
Year: 2025
Type: article
Abstract: In recent years, the importance of understanding educational trends has significantly increased, especially in developing countries like Azerbaijan. This study focuses on using data analysis methods to examine and predict changes in the field of education. The aim is to analyze educational datasets and identify key indicators that reflect long-term trends, such as student enrollment rates, graduation statistics, and public spending on education. Using Python-based tools and time series forecasting models, this research explores how these indicators change over time and what they suggest about the future of education in Azerbaijan. The study also applies statistical models such as linear regression and autoregressive models to perform trend analysis and generate forecasts. The findings of this study can help policymakers, educators, and institutions make data-driven decisions to improve the quality and accessibility of education.
Authors: Jabbarova K., Ismayilov H.
Language: English
Subfield: Computer Science Applications
Field: Computer Science
Domain: Physical Sciences
SDG: Quality education
Open Access status: green
OpenAlex ID: W6949461835
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