《STATISTICS 101》 by Sebastian Thrun
1. Teaser
2. Linear
3. Scatter Plots
4. Bar charts
5. Pie charts
6. visualiztion
7. Bayes Rules
在某种程度上，概率论和统计学的目的是完全相反(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. 在概率论中，我们是基于已有的理论模型，推断未知事件发生的概率。
In statistics we observe something that has happened, and try to figure out what underlying process would explain those observations.在统计学中，我们观察数据，并推断什么样的理论模型可以解释我们观察到的数据。
Bayes是用于推理的，而推理讲究证据，因此如果非要归类的话，Bayes会属于统计学范畴而不是概率论。
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
