This project demonstrates the application of Hypothesis Testing including Normality Test, T-Test, Chi-Square Test etc. to analyze relationships between variables of medical insurance dataset. The results of the hypothesis conducted provide great insights about the distribution of medical charges among diffent bmi categories, whether gender a significant factor in patients over medical charges and much more.
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Is there a statistically significant difference between the population medical charges and sample mean charges based on BMI Category? (ONE-SAMPLE T-TEST)
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Is the medical charges significantly different for Normal and Overweight BMI Categories?(T-TEST FOR INDEPENDENCE)
NOTE: Power Analysis to check whether our Hypothesis is sustainable and matches the praticality for T-TEST.
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Among smoking individuals, who are seeking medical insurance, is gender a significant factor or not? (CHI-SQUARE GOODNESS OF FIT-TEST)
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Do patients from different regions have an equal likelihood of seeking medical insurance? (CHI-SQUARE GOODNESS OF FIT-TEST)
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Is there enough evidence to suggest that BMI Category is independent of sex? (CHI-SQUARE TEST FOR INDEPENDENCE)