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Construct multivariate linear regression to predict the determinant factors for the Happiness Score in World's Happiness Report 2015

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HappinessScoreRegression

Construct multivariate linear regression to predict the determinant factors for the Happiness Score in World's Happiness Report 2015

1. Data collection and preparation

  • The data was collected from Kaggle.com based on World Happiness Report 2015
  • 158 countries ranked by happiness scores following by 6 factors
  • Remove all the NA values
  • Investigate the predictors

2. Model selection

  • AIC test (assume linear relation w/ interactions between factors)
  • Linear Regression model based on correlation
    • ANOVA(full, reduced)

3. Model diagnosis

  • Residual properties
  • Residual normality
  • Residual vs. predictors
  • Constancy of error variance
  • Data vs. model
  • Outlier & Leverage

4. Model validation

  • Used the fitted model to predict 2016 data and compare with the actual 2016 data

Sample graphical analysis

analysis

Comparison between predicted result and actual 2016 data

prediction

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Construct multivariate linear regression to predict the determinant factors for the Happiness Score in World's Happiness Report 2015

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