qBio I

Tuesday, September 7th, 2021 – Thursday, October 14th, 2021
Tuesdays and Thursdays, 5:30 PM – 7:30 PM (except where noted)
Location: A-250, and Zoom

Course Directors:

Teaching Assistant:

Office Hours:

  • Mondays, 5-6pm

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

Class Sessions and Lecture Notes

  1. Quantifying a Sample Distribution | Code
    Tuesday, 7 September, 2021

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

  2. Probability Density Functions and the Normal Distribution | Code
    Thursday, 9 September, 2021

    binomial, Poisson, and normal distributions, testing for normality: an introduction to formal statistical tests, qqplots vs. formal tests

  3. R Happy Hour (optional)
    Friday, 10 September, 2021 [6-7pm]

  4. Confidence Intervals and Contingency Tables | Code
    Tuesday, 14 September, 2021

    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, 16 September, 2021

    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. Statistical Power and Experimental Design | Code
    Tuesday, 21 September, 2021
    (Zoom only!)

    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

  7. Multiple Hypothesis Testing and Non-parametric Tests | Code
    Thursday, 23 September, 2021

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

  8. Group project: the optimal stopping problem | Code
    Code quality | R style
    Tuesday, 28 September, 2021

  9. Bayesian Methods | Code
    Lecture slides
    (presented by Emi Linden)
    Thursday, 30 September, 2021

    how to incorporate prior knowledge into statistical models

  10. Correlation vs. Linear Regression | Code
    Tuesday, 5 October, 2021
    (note time: 6:15-7:45)

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

  11. Fitting Model Parameters to Data | Code
    Thursday, 7 October, 2021

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

  12. Quantitative Comparison of Models and ANOVA | Code
    Tuesday, 12 October, 2021

    how to avoid over-fitting, F-test and AICs, F-tests as a means of parameter estimation

    Problem Set #3

  13. Graphics with ggplot2 | Rmd file
    ablation.csv
    Data wrangling with tidyverse | Code
    Thursday, 14 October, 2021