Statistical tests and analysis can be confounded by a simple misunderstanding of the data Statistics rarely offers a single “right”way of doing anything — Charles Wheelan in Naked Statistics In 1996, Appleton, French, and Vanderpump conducted an experiment to study the effect of smoking on a sample of people. The study was conducted over twenty years and included 1314 … Continue reading The curious case of Simpson’s Paradox
Taking the confusion out of classification metrics. Photo by Daniele Levis Pelusi on Unsplash “The definition of genius is taking the complex and making it simple.”― Albert Einstein ROC and AUC curves are important evaluation metrics for calculating the performance of any classification model. These definitions and jargons are pretty common in the Machine learning community and … Continue reading Understanding the ROC and AUC metrics.
“Reading is essential for those who seek to rise above the ordinary.” — Jim Rohn Data Science is an emerging field, and everybody is trying to hone their skills to master it. People are curious about the vital ingredients needed to become a ‘good’ Data Scientist. I believe a sound understanding of statistics, good command over tools like … Continue reading My Top Five Data Science Reads of 2018
Breaking the Jargons 