Part $2$: Predictive Modeling & Visualization $(5$ mins$)$

Dataset Overview and Analysis Objectives

You're given a dataset from the World Health Organization $($WHO$)$ that contains information from

$193$ countries. The dataset includes various metrics such as life expectancy, as well as health and

economic indicators for each country. Your task is to employ exploratory data analysis $($EDA$)$

methods to address a set of four questions related to this dataset. To illustrate your responses, you

should create at least one visualization for each question, such as charts, graphs, or tables.

Questions:

What are the predicting variables actually affecting the life expectancy?

Should a country having a lower life expectancy value $(<mn\; id="EditorElement\_1442611">6</mn><mn\; id="EditorElement\_1442612">5</mn><mi\; id="EditorElement\_1442614">)</mi>$ increase its healthcare

expenditure in order to improve its average lifespan?

How does Infant and Adult mortality rates affect life expectancy?

Does Life Expectancy have positive or negative correlation with eating habits, lifestyle,

exercise, smoking, drinking alcohol etc.

What is the impact of schooling on the lifespan of humans?

Does Life Expectancy have positive or negative relationship with drinking alcohol?

Do densely populated countries tend to have lower life expectancy?

What is the impact of Polio & Diptheria Immunization coverage on life Expectancy?