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:

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 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