qBio I

Tuesday, September 13th, 2016 – Thursday, December 15th, 2016
Tuesdays and Thursdays, 5:30 PM – 7:00 PM
Location: Weill Auditorium (or A-250 as indicated)
1300 York Avenue; 2nd Floor, Room C-200 (unless otherwise noted)
Midterm Exam: Thursday, November 3rd (5:30 pm – 7:00 pm) in Room A-250
Final Exam: Thursday, December 15th (5:30 pm – 7:00 pm) in Room C-200
Course Directors:

Teaching Assistants (qbioi2016tas@gmail.com):

  • Nimra Asi
  • Gabriele Campanella
  • Kevin Hadi
  • Mehtap Isik
  • Zijun Zhao

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

Class Sessions and Lecture Notes

  1. Quantifying a Sample Distribution
    Tuesday, September 13th, 2016

    summary statistics, quantiles, SD vs. SEM, measurement variation vs. biological variation

  2. Probability Density Functions and the Normal Distribution (slides)
    Tuesday, September 20th, 2016

    binomial, Poisson, and normal distributions, testing for normality (part I): an introduction to formal statistical tests, testing for normality (part II): qqplots vs. formal tests

  3. Lab #1: Practical R (part I) (assignment due Tuesday October 4th)
    Thursday, September 22nd, 2016

    introduction to R, common data structures (vectors, factors, lists, dataframes), importing data

  4. Confidence Intervals and Contingency Tables
    Tuesday, September 27th, 2016
    This lecture will be held in Room A-250

    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

  5. p-Values and Formal Statistical Testing
    Tuesday, October 4th, 2016

    duality between p-values and CIs, statistical vs. biological significance, choosing an appropriate α, type I and type II errors

  6. Lab #2: Practical R (part II) (assignment due Thursday October 20th)
    Thursday, October 6th, 2016

    libraries and ggplot, producing publication quality plots, data driven graphics

  7. Statistical Power and Experimental Design
    Tuesday, October 11th, 2016

    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

  8. Multiple Hypothesis Testing
    Tuesday, October 18th, 2016

    from Bonferroni to False Discovery Rate, dealing with non-normal data, t-tests re-visited

  9. Lab #3: Optimal Stopping (due Thursday November 10)
    Thursday, October 20th, 2016

    the role of simulation in statistics, non-parametric tests, exploring the optimal stopping problem

  10. Bayesian Methods
    Tuesday, October 25th, 2016

    how to incorporate prior knowledge into statistical models

  11. Midterm Exam
    Thursday, November 3rd, 2016
    The midterm exam will be held in Room A-250

  12. Election Day – No Class
    Thursday, November 8th, 2016

  13. Correlation vs. Linear Regression (code | slides)
    Thursday, November 10th, 2016

    introduction to modeling in R; why is not the whole story

  14. Principal Component Analysis (code | slides)
    Tuesday, November 15th, 2016

    data transformation and data reduction methods

  15. Thanksgiving Break: No class
    Week of November 21st, 2016

  16. Fitting Model Parameters to Data
    Tuesday, November 29th, 2016

    non-linear regression, a statistical view of curve fitting, confidence intervals revisited

  17. Midterm Exam Review
    Thursday, December 1st, 2016

  18. Quantitative Comparison of Models (lab)
    Tuesday, December 6th, 2016
    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

  19. Lab #4: Practical R (part IV)
    Thursday, December 8th, 2016
    Lab #4 will be held in Room A-250

    data wrangling with melt, dcast, and plyr

  20. Final Exam
    Thursday, December 15th, 2016