📝 Note: "I was deducing from the above that I have been slowing down steadily in these thirty-six years, but I perceive that my statistics have a defect: three thousand words in the spring of 1868, when I was working seven or eight or nine hours at a sitting, has little or no advantage over the sitting of to-day, covering half the time and producing half the output. Figures often beguile me, particularly when I have the arranging of them myself; in which case the remark attributed to Disraeli would often apply with justice and force: 'There are three kinds of lies: lies, damned lies, and statistics.'"
From Mark Twain's Autobiography
This repository will give some cursory stats gleanings. Basic descriptive statistics, probability distributions, hypothesis testing all appear.
- Build atop statistics knowledge from the Khan Academy prework
- Understand how to use the uniform, binomial, poisson, and normal distributions to model real-world scenarios
- Understand in general how hypothesis testing is performed
- Know when to use a t-test, correlation test, and Chi-Squared test
- Write python code that simulates experiments in order to calculate an experimental probability
- Use various statistical distributions in python through scipy.stats
- Perform hypothesis testing in python code