The Data Scientist’s Toolbox.
Hi hi hi! I’m Ping, and this is my little corner of the internet.
I write to think, to connect with people, and hopefully to inspire someone.
Several years ago, I came accross this old saying for medical students:
“To cure sometimes, to relieve often, to comfort always.”
It reminds doctors the importance of the human side of medicine: caring for the people.
“To predict sometimes, to estimate often, to enlighten always.”
And then we need tools to do that. On this website, you'll find a collection of data science methods to help you expand your knowledge, understand the world a little better, and perhaps make better decisions.
However, do remember George Box’s words:
“All models are wrong, but some are useful.”
Also don’t forget John von Neumann's:
“In mathematics you don’t understand things. You just get used to them.”
:)
Recently added
- Bootstrap confidence intervalSeedling
Resampling. Estimates the uncertainty of almost any statistic by resampling the data with replacement.
- Mann–Whitney U testSeedling
Comparing groups. A rank-based test of whether values in one independent group tend to be larger than in the other.
- Welch’s t-testGrowing
Comparing groups. Compares the means of two independent groups without assuming they have the same variance.