Schedule 2017

qBio I

Thursday, September 14th, 2017 – Tuesday, December 12th, 2017
Tuesdays and Thursdays, 5:30 PM – 7:00 PM
Location: C-200 Weill Auditorium (or A-250 as indicated)
1300 York Avenue; 2nd Floor, Room C-200 (unless otherwise noted)
Midterm Exam: Thursday, November 2nd (5:30 pm – 7:00 pm) in Room C-200
Course Directors:

• Jason Banfelder (jbanfelder@rockefeller.edu)
• Luce Skrabanek (las2017@med.cornell.edu)

Teaching Assistants (qbioI2017@gmail.com):
Office hours and locations:

• Shana Bergman
  Mondays, 10-11am, E-511
• Dylan McNally
  Fridays, 9-10am, BRB 14th Floor conference room
• Ambrose Plante
  Tuesdays, 7:30-8:30pm, LC-504 conference room
• Andrew Schaumberg
  Thursdays, 1-2pm, E-511
• Jazz Weisman
  Wednesdays, 6-7pm, CRC 4th Floor large public table (RU)

We have also set up a Piazza forum.

This course will be fully graded: (Honors, High Pass, Low Pass, Fail)

Class Sessions and Lecture Notes

1. Quantifying a Sample Distribution part I (R code)
   Thursday, September 14th, 2017
   
   summary statistics, quantiles, SD vs. SEM

2. Quantifying a Sample Distribution part II (R code)
   Tuesday, September 19th, 2017
   
   summary statistics, SD vs. SEM, measurement variation vs. biological variation

3. Probability Density Functions and the Normal Distribution part I (R code)
   Thursday, September 21th, 2017
   
   binomial, Poisson, and normal distributions, testing for normality (part I): an introduction to formal statistical tests

4. Probability Density Functions and the Normal Distribution part II (R code)
   Tuesday, September 26th, 2017
   
   testing for normality (part II): qqplots vs. formal tests

5. TA-led Swirl tutorials
   Thursday, September 28th, 2017

6. Jeop-R-dy heats
   Monday-Friday, October 2nd-6th, 2017
   Will be held during TA sessions

7. Practical R part I (Rmd code)
   Tuesday, October 3rd, 2017
   
   introduction to R, common data structures (vectors, factors, lists, dataframes), importing data

8. Confidence Intervals and Contingency Tables (R code)
   Thursday, October 5th, 2017
   
   t-tests, working with proportional data, why CIs are more informative than p-values, study types (retrospective, prospective, and cross sectional), working with rare events

9. Final Jeop-R-dy
   Tuesday, October 10th, 2017

10. p-Values and Formal Statistical Testing (R code)
    Tuesday, October 17th, 2017
    
    duality between p-values and CIs, statistical vs. biological significance, choosing an appropriate α, type I and type II errors

11. Practical R part II (R code | Problem Set)
    Thursday, October 19th, 2017
    
    common data structures continued (lists and dataframes)

12. Statistical Power and Experimental Design (R code)
    Tuesday, October 24th, 2017
    
    why you cannot just add a few N to your dataset when p > 0.05, appreciating the economics (in time and money) of experimental design, statistical vs. biological significance revisited, designing experiments around hard-to-obtain samples

13. Multiple Hypothesis Testing and Non-parametric Tests (R code)
    Thursday, October 26th, 2017
    
    from Bonferroni to False Discovery Rate, dealing with non-normal data, t-tests re-visited

14. Extra TA office hours
    Tuesday, October 31st, 2017

15. Midterm Exam
    Thursday, November 2nd, 2017

16. Practical R: Optimal Stopping (R code)
    Tuesday, November 7th, 2017
    
    the role of simulation in statistics, non-parametric tests, exploring the optimal stopping problem

17. Bayesian Methods (R code)
    Thursday, November 9th, 2017
    
    how to incorporate prior knowledge into statistical models

18. Correlation vs. Linear Regression (R code)
    Tuesday, November 14th, 2017
    
    introduction to modeling in R; why $r^2$ is not the whole story

19. Code quality
    Thursday, November 16th, 2017
    
    data transformation and data reduction methods

20. Thanksgiving Break: No class
    Week of November 21st, 2017

21. Fitting Model Parameters to Data (R code)
    Thursday, November 30th, 2017
    
    non-linear regression, a statistical view of curve fitting, confidence intervals revisited

22. Quantitative Comparison of Models and ANOVA part I (R code | Problem Set)
    Tuesday, December 5th, 2017
    This lecture will be held in Room A-250
    
    how to avoid over-fitting, F-test and AICs, F-tests as a means of parameter estimation

23. Quantitative Comparison of Models and ANOVA part II (R code)
    Thursday, December 7th, 2017
    
    how to avoid over-fitting, F-test and AICs, F-tests as a means of parameter estimation

24. Principal Component Analysis (R code) | Intro to ggplot2
    Tuesday, December 12th, 2017
    
    publication-quality graphics with ggplot