Size Matters!
Analytics Challenge 2019 Fall
Course: Data Analytics
Professor: Siddharth Bhattacharya
Goal: To answer \\\”What makes rare disease clinical trials successful?\\\”
Method: My group and I decided to pick 10 randomized conditions from Alexion Data with their relevant clinical trial methods. In order to define a clinical trial as \\\”successful or \\\”failure\\\”, we compared the data with sample points including age groups and gender. More importantly, we came to the assumption that the rate of success depends on the number of individuals that are enrolled in a clinical trial.
Result: We came up with a conclusion that the total number of enrollment helps determine the rate of \\\”success\\\” in Clinical Trials as there is less room for biased results due to size.
- I learned that when dealing with a huge data set, separating the data with various sample points (ex. age, gender, etc) provides a clear analysis than dealing with all of the data at once. Additionally, random sampling provides accurate representation of the whole population of data. Though it is difficult and requires effort, random sampling avoids biases as it is considerate in involving different data points from the population.
Link: https://create.piktochart.com/output/42048034-size-matters-snehal-patel