Data Set: Predicting Heart Disease Using Clinical Variables
Background: I chose this data set in order to analyze different clinical variables and how they pertain to heart disease. This data contains categories such as age, sex, cholesterol levels, blood pressure, and the classification of the individual’s chest pain.
Goal: I chose this data set in order to analyze different factors that pertain to heart disease and to identify significant relationships between variables and the presence of heart disease.
The exploratory questions that were formulated are:
- Is there a significant correlation between age and heart disease?
- Is there a significant relationship between blood pressure and cholesterol levels?
- Is there a correlation between sex and heart disease?
One interesting part of this data set is that sex is denoted as ‘0’ and ‘1’, but never clarifies the sex assigned to each number. This led to the formulation of the next exploratory question:
- Which sex do 0 and 1 represent, given that heart disease usually occurs sooner in men?
Methods: Using Spyder software, the exploratory questions were answered by utilizing various plots and statistical tests.
Results:
Observations and Analysis:
A T-test was performed in order to solidify the conclusion that there is a significant relationship between age and the presence of heart disease. This test resulted in a p value of 0.026. Since this value is less than 0.05, the null hypothesis can be rejected and we can assume that there is a significant relationship between the two variables.
A Pearson’s Correlation Coefficient Test was performed in order to solidify the conclusion that there is a significant relationship between cholesterol and blood pressure. This test resulted in a p value of 0.00435. Since this value is less than 0.05, the null hypothesis can be rejected and we can assume that there is a significant relationship between those two variables.
Future Directions: I would be interested to find data that includes genetic disposition and research how that is correlated with the presence of heart disease.
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