Data-Science-Project

Analysis on Various Factors Affecting Insurance Costs of U.S. Adults

In this project, I intend to analyze a sample of insurance costs of individuals across the United States, classified by age, sex, bmi, number of children, and inhabiting region. Through my analysis, I aim to find out:

1. The variable that has the largest correlation to the cost of health insurance charges
2. How the smoking habits in each sex affect the insurance charges
3. How the insurance charges differ (and maybe why) in each age group.

Prior to any analysis or examination of the dataset, I initially hypothesize that:

1. The variable with the largest correlation to the insurance costs is the "bmi", since it is a good indicator of one's health condition
2. The smoking habit of a female incurs a higher insurance charges than that of a male, since researches show that female smokers have higher chance of getting respiratory diseases than do male smokers
3. As the age group moves from a younger group to an older group, the insurance charges increase, and the insurance charges of each age group are affected by the 'bmi' variable.

Note: The dataset 'insurance.csv' was acquired from CodeCademy.com.