Schedule 2020

qBio II

Tuesday, October 20th, 2020 – Thursday, December 10th, 2020
Tuesdays & Thursdays, 5:30 PM – 7:30 PM
Location: Zoom
Course Director: Derek Shore (des2037@med.cornell.edu)
Course Director: Jason Banfelder (jbanfelder@rockefeller.edu)
Office Hours: Mondays, 4:00 PM - 5:00 PM
This course will be fully graded: (Honors, High Pass, Low Pass, Fail)

Class Sessions and Lecture Notes

1. Introduction to Dynamic Systems and Linear Difference Equations (part I)
   Tuesday, October 20th, 2020

2. Introduction to Dynamic Systems and Linear Difference Equations (part II)
   Thursday, October 22nd, 2020

3. Periodic Behavior and Complex Eigenvalues
   Tuesday, October 27th, 2020

4. A First Look at Eigenvectors
   Thursday, October 29th, 2020

5. NO CLASS: Election Day (Principal Component Analysis lecture postponed)
   Tuesday, November 3rd, 2020

6. Principal Component Analysis | Linear Difference Equations Laboratory
   Thursday, November 5th, 2020 (6:15 PM - 7:45 PM)

7. Representing Time Dependent Phenomena with ODEs
   Tuesday, November 10th, 2020

8. Stability and Linearization of ODEs (part I)
   Thursday, November 12th, 2020

9. Stability and Linearization of ODEs (part II) | ODE Laboratory
   Tuseday, November 17th, 2020

10. No class | Lab 1 Due
    Thursday, November 19th, 2020

11. Thanksgiving Break: No class
    Tuesday, November 24th, 2020
    Thursday, November 26th, 2020

12. Markov Chains and Hidden Markov Models
    Tuesday, December 1st, 2020

13. Fourier Analysis and Signal Processing | Lab 2 Due
    Thursday, December 3rd, 2020

14. No Class (exam week)
    Tuesday, December 8th, 2020

15. FINAL EXAM
    Thursday, December 10th, 2020

qBio I

Tuesday, September 8th, 2020 – Tuesday, October 15th, 2020
Tuesdays and Thursdays, 5:30 PM – 7:00 PM (except where noted)
Location: Zoom

Course Directors:

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

Teaching Assistant:

• Ariana Clerkin (arb4007@med.cornell.edu)

Office Hours:

• Mondays, 4-6pm

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

Class Sessions and Lecture Notes

1. Quantifying a Sample Distribution | Code
   Tuesday, 8 September, 2020
   
   summary statistics, SD vs. SEM, measurement variation vs. biological variation

2. Probability Density Functions and the Normal Distribution | Code
   Thursday, 10 September, 2020
   (note time: 6:15-7:45)
   
   binomial, Poisson, and normal distributions, testing for normality: an introduction to formal statistical tests, qqplots vs. formal tests

3. R Happy Hour (optional)
   Friday, 11 September, 2020

4. Confidence Intervals and Contingency Tables | Code
   Tuesday, 15 September, 2020
   
   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 | Code
   Thursday, 17 September, 2020
   
   duality between p-values and CIs, statistical vs. biological significance, choosing an appropriate α, type I and type II errors
   
   Problem Set #1: Understanding Type I error rates
   R Markdown | Rmd file | HTML file
   Intro to R | Code

6. R Happy Hour (optional)
   Friday, 18 September, 2020

7. Statistical Power and Experimental Design | Code
   Tuesday, 22 September, 2020
   
   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. Group project: the optimal stopping problem | Code
   Thursday, 24 September, 2020

9. Multiple Hypothesis Testing and Non-parametric Tests | Code
   Tuesday, 29 September, 2020
   
   from Bonferroni to False Discovery Rate, dealing with non-normal data, t-tests re-visited

10. Bayesian Methods
    Unbiased Coin example | Fair Coin example 1 | Fair Coin example 2 | Unfair Coin example
    Thursday, 1 October, 2020
    
    how to incorporate prior knowledge into statistical models

11. Correlation vs. Linear Regression | Code
    Tuesday, 6 October, 2020
    (note time: 6:15-7:45)
    
    introduction to modeling in R; why $r^2$ is not the whole story

12. Fitting Model Parameters to Data | Code
    Thursday, 8 October, 2020
    
    non-linear regression, a statistical view of curve fitting, confidence intervals revisited

13. Quantitative Comparison of Models and ANOVA | Code
    Tuesday, 13 October, 2020
    
    how to avoid over-fitting, F-test and AICs, F-tests as a means of parameter estimation
    
    Problem Set #3

14. Graphics with ggplot2 | Rmd file
    ablation.csv
    Data wrangling with tidyverse | Code
    Thursday, 15 October, 2020