Statistics 13: Introduction to Statistical Methods for the Health and Life Sciences
For the course syllabus click here.
- First lecture is on Thursday, 02 Otober 2014.
Location: WGYOUNG CS24.
Day/time: TR 09:30- 10:45.
See you then!
For some of the labs you will need to access the Statistics Online Computational Resource (SOCR) at:
It's online, therefore it exists!
The labs are listed under the following link (instructions will be given as to which lab is due when etc. - mainly distributions and experiments activities):
Probability and Statistics EBook.
Download R and packages.
Numbers matter (text file).
Lab 1: Lab based on the beeswax paper. Due on Wednesday, 15 October before 23:59.
Lab 2: Introduction to R. Due on Wednesday, 22 October before 23:59.
Lab 3: North Carolina SIDS data. Due on Thursday, 06 November before 00:05.
Lab 4: Breast cancer mortality data and asbestos fibers data.
Due on Thursday, 06 November before 00:05.
Asbestos paper (see lab 4).
Resistance to breathing paper (see hw 2).
Lab 5: Normal and binomial distribution.
Due on Monday, 17 November, by 11:55 pm.
Lab 6: Simple regression analysis.
Due on Wednesday, 19 November, by 11:55 pm.
Lab 7: Testing for two proportions: Simulated-based approach.
Due on Tuesday 25 November, by 11:55 pm.
Article for lab 7: "Statistics in the courtroom", by George Cobb and Stephen Gehlbach.
1. Measures of central tendency and
2. Empirical cumulative distribution function - example.
3. Survival analysis - example.
4. Survival analysis - R commands.
5. Introduction to R.
6. Introduction to regression
7. Leverage values and outliers in regression - example.
8. Influential analysis - example.
9. Influential analysis - R commands for handouts 7 and 8.
10. Regression - practice questions.
11. Introduction to stock market portfolio
13. stockPortfolio package - R commands.
14. Simulating points using the maps package - R commands.
15. Permutation test in simple regression - R commands.
16. Compare variability around sample mean of y against variability
around the fitted line.
17. Normal distribution.
18. Linear combinations of normal random variables.
19. Discrete probability distributions (only binomial).
20. Binomial and Poisson distributions - summary.
21. The t distribution.
22. Simulations-based inference for one proportion.
23. Theory-based inference for one proportion.
24. Simulations-based inference for two proportions.
25. Simple regression - useful formulas.
26. Practice questions.
Homework 1: Due on Wednesday, 15 October.
Homework 2: Due on Wednesday, 29 October.
Homework 3: Due on Thursday, 13 November.
Homework 4: Due on Friday, 21 November.
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