Ok. I retook GRE, took ST 512 and MA 425, and then finally I got admitted to Statistics programs.

This semester, I took ST 520 (statistical clinical trail principles), ST 521 (statistical inference), ST 711 (Design of Experiments), ST 730 (Applied Time Series). Before starting class, I thought I was smart. But after one week, I think everybody is smart. Yesterday I searched on the website : how to become smart. Two things I kept in mind. One is being with smart people. Great, I am now surrounded with many smart PhD Candidates, excellent in math. The other one is writing blog. Out of this motivation, also encouraged by David Smith’s interview, saying that blogging can keep track of what you learned everyday, I reset my forgotten password for this blog, and hope I can write something down everyday.

**ST 520**: study two areas epidemiology and clinical trails.

Epidemiology studies what cause a disease. Since you can only observe what happen in a population and cannot control treatment, epidemiology is about observational study. So you can only reach a conclusion about the association between disease and exposure. To determine whether there is association between disease and exposure, we can use Pearson Chi-Square Test’s Test of Independence. But to qualify the association, we have relative risk or odds ratio. Generally, there are cross-sectional study, perspective study, retrospective study ( or case-control study) and match case-control study. **Cross-sectional study** is to get a random sample representing the population at one time and then collect the data from the sample, so you can know the prevalence of disease. Prevalence is the proportion of individuals getting diseases in the population, including all the disease cases. **Perspective study** is to find a group of people, record their all factors, especially something you want to study, like some smokers and nonsmokers, follow them for a period of time, and then see how many die or still live. Of course, there are problems, like somebody quits in the middle. **Retrospective study** is to get two groups of people of the same number, one group of getting disease, and one group of not. Then you ask them about their habit or exposure to something like getting lung cancer, asking they are smoker or not. Since some confounding variables (variables related with primary variables and the response) like age or gender affect one’s habit or exposure, like men tend to smoke, match case-control study can control those confounding variables to separate the effect of main exposure on diseases from confounding variables.

Clinical trails can control the treatments to study the causal relationship between treatments (drugs) and diseases, so they are experimental study. Before applying drugs to human being, **Pre-Clinical Phase** can apply drug to animals and see efficacy and test toxicity. Then **Phase I** is the first time to apply drugs to man. This phase, the maximum tolerable dose (**MTD,** the amount that cause one out three toxic problem) need be determined.

**ST 521**: Statistical Inference

One abstract idea I recently learned is algebra and sigma algebra. But the good thing is the idea of variable, Y(w), which mapped any element of sample space onto the real value. So sample space of rolling of die is {one dot, two dots,…six dots}. Now any element of sample space, the number of dots, is mapped to a real number.

(S, A, P) —> Y(w) —> (R, B, F(.)) Sample space S is replaced by real number R. The algebra A is mapped onto Borel set (B). You can assign the probability to random variable and its cumulative distribution function is F(.).