Exploratory data analysis involves examining the dataset to gain insights, identify patterns, and understand the distributions and relationships between variables. EDA techniques such as data visualization, summary statistics, and correlation analysis can be applied to uncover interesting trends or relationships in the data.
Statistical analysis techniques can be used to explore the statistical significance of relationships between predictors and life expectancy. This may include hypothesis testing, regression analysis, analysis of variance (ANOVA), variance inflation factor and wrapper method method for variable selection
The dataset is utilized to build predictive models to forecast life expectancy based on various predictors. Linear regression is applied for this purpose.