Energy Transitions over Five Decades: A Statistical Perspective on Global Energy Trends
This study analyzes global energy trends from January 1973 to November 2022, using the “World Energy Statistics” dataset from Kaggle, which includes data on the production, consumption, import, and export of fossil fuels, nuclear energy, and renewable energy. The analysis employs statistical techniq...
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| Main Authors: | , , , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2025-05-01
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| Series: | Computers |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2073-431X/14/5/190 |
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| Summary: | This study analyzes global energy trends from January 1973 to November 2022, using the “World Energy Statistics” dataset from Kaggle, which includes data on the production, consumption, import, and export of fossil fuels, nuclear energy, and renewable energy. The analysis employs statistical techniques such as correlation analysis, quantile–quantile (Q–Q) plots, seasonal decomposition, and seasonal autoregressive integrated moving average (SARIMA) modeling. The results reveal strong positive correlations between nuclear energy production and consumption, as well as between renewable energy production and consumption. Seasonal decomposition highlights annual patterns in renewable energy use and a declining trend in fossil fuel dependency. SARIMA modeling forecasts continued growth in renewable energy consumption and a gradual reduction in fossil fuel reliance. These findings provide critical insights into long-term energy patterns and offer data-driven implications for global energy policy and strategic planning. |
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| ISSN: | 2073-431X |