《STATISTICS 101》 by Sebastian Thrun
1. Teaser
2. Linear
3. Scatter Plots
4. Bar charts
5. Pie charts
6. visualiztion
7. Bayes Rules
在某種程度上，概率論和統計學的目的是完全相反(inverse)的：
In probability theory we consider some underlying process which has some randomness or uncertainty modeled by random variables, and we figure out what happens. 在概率論中，我們是基于已有的理論模型，推斷未知事件發生的概率。
In statistics we observe something that has happened, and try to figure out what underlying process would explain those observations.在統計學中，我們觀察數據，并推斷什么樣的理論模型可以解釋我們觀察到的數據。
Bayes是用于推理的，而推理講究證據，因此如果非要歸類的話，Bayes會屬于統計學范疇而不是概率論。
8. Probability Distributions
9. Correlation VS Causation
10. Estimation
11. Averages
12. Variance
13. Outliers
14. Binomial Distribution
15. Central Limit Thereon
16. The Normal Distribution
17. Manipulating Normals
18. Best Better Than Average
