The World Happiness Report 2024 examines global happiness through various factors like GDP, social support, and life expectancy. This analysis highlights key trends, regional comparisons, and the impact of socio-economic elements on happiness, offering insights into how countries can enhance the well-being of their populations.
source: kaggle
Given the dataset, Powerdrill detects and analyzes the metadata, then gives these relevant inquiries:
1. Overall Happiness Scores
Top Countries
Top Countries by Ladder Scores in 2024
Lowest Countries
Lowest Countries by Ladder Scores in 2024
Trends
Trends in Happiness Scores Over the Years
2. Factors Contributing to Happiness
GDP per Capita
Correlation Between Ladder Scores and GDP per Capita
Social Support
Impact of Social Support on Ladder Scores
Healthy Life Expectancy
Relationship Between Healthy Life Expectancy and Ladder Scores
Freedom to Make Life Choices
Correlation Between Freedom to Make Life Choices and Ladder Scores
Generosity
Impact of Generosity on Ladder Scores
Perceptions of Corruption
Influence of Perceptions of Corruption on Ladder Scores
3. Regional Analysis
Comparison by Continent
Happiness Scores Comparison Across Different Continents
Regional Trends
Regional Trends and Patterns in Happiness Scores
4. Comparative Analysis
High vs. Low Happiness Countries
Comparison of Contributing Factors: High vs. Low Happiness Countries
Yearly Comparison
Changes in Happiness Scores and Contributing Factors Over Time
5. Distribution and Statistical Analysis
Distribution Analysis
Distribution of Happiness Scores and Contributing Factors
Statistical Correlation
Statistical Correlation Analysis of Contributing Factors
Overall Happiness Scores
Top Countries
The countries with the highest ladder scores, indicating the highest levels of happiness reported, are as follows:
Finland: 7.741
Denmark: 7.583
Iceland: 7.525
Sweden: 7.344
Israel: 7.341
These scores suggest that Nordic countries, particularly Finland, Denmark, and Iceland, continue to dominate the top positions in global happiness rankings, likely due to strong social support systems, high levels of personal freedom, and robust health services.
Lowest Countries
Conversely, the countries with the lowest ladder scores are:
Afghanistan: 1.721
Lebanon: 2.707
Lesotho: 3.186
Sierra Leone: 3.245
Congo (Kinshasa): 3.295
These low scores highlight regions facing significant challenges such as economic instability, political conflicts, or poor health infrastructure, which severely impact the well-being and perceived happiness of their populations.
Trends in Happiness Scores
The visualization of happiness scores over the years shows a general decline in ladder scores as we move from the highest-ranked countries to the lowest. The line chart indicates a steep initial drop, which gradually levels off but continues to trend downwards. This suggests a wide disparity in happiness scores globally, with a significant drop-off from the highest scores to median values.
Key Observations:
The highest happiness scores are significantly above the global average, concentrated in countries with strong economic and social structures.
The lowest scores are found in countries experiencing severe disruptions such as war, political instability, or economic hardships.
The overall trend shows a decrease in happiness scores, indicating a global variation in how countries are able to provide environments that contribute to the well-being of their citizens.
Conclusion: This analysis underscores the importance of stable social, economic, and political environments in contributing to the happiness and well-being of populations. The stark contrast between the highest and lowest-ranked countries provides valuable insights into the potential areas of intervention for international organizations and governments to improve the quality of life for their citizens.
Factors Contributing to Happiness
Correlation Analysis
The analysis of various factors from the World Happiness Report 2024 dataset reveals the following correlations with the Ladder score, which measures happiness levels:
Log GDP per capita:
Correlation Coefficient: 0.768504
Interpretation: Strong positive correlation, indicating that higher GDP per capita is associated with higher happiness levels.
Social Support:
Correlation Coefficient: 0.813542
Interpretation: Very strong positive correlation, suggesting that better social support is crucial for higher happiness levels.
Healthy Life Expectancy:
Correlation Coefficient: 0.759659
Interpretation: Strong positive correlation, showing that longer healthy life expectancy is linked to greater happiness.
Freedom to Make Life Choices:
Correlation Coefficient: 0.644451
Interpretation: Moderate positive correlation, indicating that freedom in life choices positively impacts happiness, though less strongly than other factors.
Generosity:
Correlation Coefficient: 0.130038
Interpretation: Very weak positive correlation, suggesting that generosity has a minimal impact on happiness levels.
Perceptions of Corruption:
Correlation Coefficient: 0.451829
Interpretation: Moderate negative correlation, indicating that lower perceptions of corruption are associated with higher happiness levels.
Key Insights
Most Influential Factors: Social support and GDP per capita are the most influential factors for happiness, as indicated by their high correlation coefficients.
Least Influential Factor: Generosity has the least influence on happiness levels among the factors analyzed.
Policy Implications: Enhancing social support systems, improving economic conditions, and reducing corruption could be effective strategies for nations to improve their happiness scores.
Recommendation: Policymakers should focus on strengthening social support and economic development as primary targets for enhancing national happiness levels, while also addressing corruption to further boost well-being.
Regional Analysis
Comparison of Happiness Scores Across Continents
Key Findings:
Significant Disparity in Happiness Scores: The analysis reveals a stark contrast in the mean happiness scores between the continents of Asia and Europe.
Europe's Higher Happiness Scores: Europe exhibits a significantly higher mean happiness score of 7.54825, indicating a generally higher level of well-being and satisfaction among its countries.
Asia's Lower Happiness Scores: Asia, on the other hand, shows a much lower mean happiness score of 1.721, suggesting lower levels of well-being and satisfaction.
Regional Trends and Patterns:
Europe's Consistent High Scores: European countries consistently rank high in happiness scores, which could be attributed to strong social support systems, high GDP per capita, and greater freedom to make life choices.
Challenges in Asia: The low average score in Asia might reflect economic disparities, political instability, or lower levels of social support and healthcare in some countries.
Visualization Insights:
The provided bar chart visually underscores the significant difference in happiness scores between the two continents. Europe's bar is notably taller, representing its much higher happiness scores compared to Asia.
Implications:
Policy Focus in Asia: There may be a need for targeted policies to improve economic conditions, healthcare, and social support systems in Asian countries to enhance overall happiness.
Understanding Cultural Differences: It is also crucial to consider cultural differences in the perception of happiness and factors contributing to well-being.
This analysis provides a clear overview of how happiness scores vary significantly across continents, with Europe leading in higher scores compared to Asia. Further investigation into the specific factors contributing to these differences would be beneficial for targeted interventions and policy planning.
Comparative Analysis
High-Ranking vs Low-Ranking Countries
1. Economic Influence (Explained by: Log GDP per capita)
High-Ranking: Mean = 1.815
Low-Ranking: Mean = 0.918
Observation: High-ranking countries have nearly double the GDP per capita score compared to low-ranking countries, indicating a strong correlation between economic strength and happiness.
2. Social Support
High-Ranking: Mean = 1.407
Low-Ranking: Mean = 0.742
Observation: There is a significant difference in social support between the two groups, with high-ranking countries enjoying much higher levels of social support.
3. Healthy Life Expectancy
High-Ranking: Mean = 0.663
Low-Ranking: Mean = 0.347
Observation: High-ranking countries report a healthier life expectancy, which is a crucial factor contributing to overall happiness.
4. Freedom to Make Life Choices
High-Ranking: Mean = 0.741
Low-Ranking: Mean = 0.492
Observation: Freedom, a vital component of happiness, is significantly higher in high-ranking countries.
5. Generosity
High-Ranking: Mean = 0.167
Low-Ranking: Mean = 0.149
Observation: Although generosity scores are relatively close, high-ranking countries still show slightly higher levels.
6. Perceptions of Corruption
High-Ranking: Mean = 0.289
Low-Ranking: Mean = 0.116
Observation: High-ranking countries perceive less corruption, which positively impacts their happiness scores.
7. Dystopia + Residual
High-Ranking: Mean = 1.793
Low-Ranking: Mean = 1.148
Observation: The dystopia residual, which reflects the unexplained components of happiness, is also higher in high-ranking countries.
Changes Over Time
Conclusion: The analysis clearly shows that high-ranking countries outperform low-ranking ones across all measured factors contributing to happiness. Economic strength, social support, and healthy life expectancy are the most distinguishing factors between the two groups. For a comprehensive temporal analysis, historical data spanning multiple years would be necessary to observe trends and changes in these happiness factors.
Distribution and Statistical Analysis
Distribution of Happiness Scores
Mean Happiness Score: 5.53
Standard Deviation: 1.17
Range: Scores range from a minimum of 1.72 to a maximum of 7.74.
Median Score: 5.79, indicating that the median happiness score is slightly above the mean.
Distribution of Contributing Factors
Log GDP per Capita: Mean of 1.38, with values ranging from 0.00 to 2.14. The histogram shows an increasing frequency as GDP increases, indicating that higher GDP per capita is more common among the surveyed countries.
Social Support: Mean of 1.13, ranging from 0.00 to 1.62. The distribution likely follows a similar pattern to GDP, emphasizing the prevalence of better social support in wealthier nations.
Healthy Life Expectancy: Mean of 0.52, with a range from 0.00 to 0.86. This factor shows a moderate spread across the dataset.
Freedom to Make Life Choices: Mean of 0.62, ranging from 0.00 to 0.86. The distribution suggests a moderate level of freedom in most countries.
Generosity: A lower mean of 0.15 and a narrower range up to 0.40, indicating lower variability and generally lower levels of perceived generosity.
Perceptions of Corruption: Mean of 0.15, with a maximum value of 0.57. This factor shows significant variability, indicating differing levels of corruption perception across countries.
Dystopia + Residual: Mean of 1.58, ranging from -0.07 to 3.00, suggesting a wide variation in how much 'dystopian' factors and unexplained residuals contribute to happiness scores.
Correlation Analysis
Strong Positive Correlations: Ladder score shows strong positive correlations with Log GDP per capita (0.81), Social support (0.88), and Healthy life expectancy (0.81), indicating that higher values in these factors are associated with higher happiness scores.
Moderate to Weak Correlations: Freedom to make life choices (0.48) and Perceptions of corruption (0.08) show weaker positive correlations with the Ladder score.
Negative Correlation: Generosity shows a negative correlation (-0.78) with the Ladder score, suggesting that higher generosity scores might be associated with lower happiness scores, which could be counterintuitive and warrants further investigation.
Heatmap Visualization: Provides a clear visual representation of these correlations, highlighting the strengths and directions of relationships between the Ladder score and each contributing factor.
Overall, the analysis of the World Happiness Report 2024 dataset reveals significant insights into the factors contributing to happiness across different nations, with economic factors like GDP, social support, and health playing crucial roles in determining overall happiness scores.
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