Lecture syllabus

Lecture syllabus

1. Welcome and Basic Statistics
2. git & GitHub
3. Statistical distributions & exploring with histograms
4. And, Or, Convolution
5. Asking a statistical question pt. 1
   1. Feldman-Cousins lite 
   2. Words to Math
6. Asking statistical questions pt. 2
   1. Practicum
7. Confidence intervals
   1. Classic
   2. Case of uncertainty on an observed value
   3. Case of an upper limit
   4. Transitional cases
8. Confidence intervals pt 2
   1. Priors
   2. Bayes theorem
   3. Power & caution
   4. Idea of flat(ish) priors
9. Signal-free data sets
   1. Why, and how to create
   2. Data exploration
   3. Introduction to systematics
10. Repeatability of datasets
    1. Error bars on histograms
11. Jackknife tests
12. Hunting for systematics pt 1
    1. List of worries
    2. Developing tests based on worries
13. Hunting for systematics pt 2
    1. Specific tests (quantitative)
    2. General tests (plots and data rampages)
14. Using Github to plan an analysis
    1. Final project proposal