Statistics 13: Introduction to Statistical Methods for the Health and Life Sciences

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For the course syllabus click here.

Useful links:

For some of the labs you will need to access the Statistics Online Computational Resource (SOCR) at:
  • http://www.socr.ucla.edu

    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):
  • http://wiki.stat.ucla.edu/socr/index.php/SOCR_EduMaterials.
  • Probability and Statistics EBook.
  • Download R and packages.

    Read this:

  • Numbers matter (text file).

    Labs

  • 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.
  • Lab 8: Simulations-based hypothesis testing for one mean and two means. Due on Friday, 05 December, by 11:55 pm.
  • Lab 9: Simulations-based hypothesis testing for paired data.
  • Article related to lab 9 (paired data).
  • Lab 10 - example: Simulations-based hypothesis testing for oneway ANOVA.
  • Lab 10: ANOVA using simulations and theory.

    Handouts

  • 1. Measures of central tendency and variation.
  • 2. Empirical cumulative distribution function - example.
  • 3. Survival analysis - example.
  • 4. Survival analysis - R commands.
  • 5. Introduction to R.
  • 6. Introduction to regression analysis.
  • 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 analysis.
  • 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.
  • 27. Confidence intervals.
  • 28. Confidence intervals - answers to sample problems.
  • 29. Hypothesis testing.
  • 30. Article related to the paired-t test.
  • 31. Testing for two population means.
  • 32. Analysis of variance (ANOVA).
  • 33. ANOVA - example.
  • 34. Contingency tables.
  • 36. Goodness-of-fit test.
  • 37. Goodness-of-fit test - example.

    Homework

  • 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.
  • Homework 5: Due on Monday, 08 December.
  • Homework 6: Due on Wednesday, 10 December.

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