CardioState: Exploring Heart Health Through Hypothesis Testing and Confidence Intervals
Welcome to CardioState, a project dedicated to exploring heart health through the lens of hypothesis testing and confidence intervals. This repository aims to delve into the fascinating realm of cardiovascular health by conducting hypothesis tests and calculating confidence intervals using real-world data
Hypothesis testing and confidence intervals are powerful statistical tools that enable us to make informed inferences about the dataset. By formulating research questions and hypotheses, we can use appropriate statistical tests to analyze relationships between variables and calculate confidence intervals to estimate parameter values.
CardioState addresses four key research questions:
- Is there a significant difference in cholesterol levels between patients with and without heart disease?
- Is there a significant difference in genders between patients with and without heart disease?
- Is there a significant difference in maximum heart rate between patients with and without heart disease?
- Is there a significant difference in ages between patients with and without heart disease?