qBio I

Thursday, September 15th, 2022 – Thursday, October 27th, 2022
Tuesdays and Thursdays, 5:30 PM – 7:30 PM (except where noted)
Location: A-250, and Zoom

Course Directors:

Teaching Assistant:

Office Hours:

  • 5:30-6:30 on Wednesdays

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

Class Sessions and Lecture Notes

  1. Quantifying a Sample Distribution | Code
    Thursday, 15 September, 2022

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

  2. Probability Density Functions and the Normal Distribution | Code
    Tuesday, 20 September, 2022

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

  3. Confidence Intervals and Contingency Tables | Code
    Thursday, 22 September, 2022

    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

  4. p-Values and Formal Statistical Testing | Code
    Tuesday, 27 September, 2022

    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
    Optional resources: Intro to R | Code

  5. Statistical Power and Experimental Design | Code
    Thursday, 29 September, 2022

    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

  6. Multiple Hypothesis Testing and Non-parametric Tests | Code
    Tuesday, 4 October, 2022

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

  7. Group project: the optimal stopping problem | Code
    Code quality | R style
    Thursday, 6 October, 2022
    (note time change: 6:30-8:30)

  8. Correlation vs. Linear Regression | Code
    Tuesday, 11 October, 2022

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

  9. Fitting Model Parameters to Data | Code
    Thursday, 13 October, 2022

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

  10. Bayesian Methods | Code
    Lecture slides
    (presented by David Ballesteros Gomez)
    Tuesday, 18 October, 2022

    how to incorporate prior knowledge into statistical models

  11. Quantitative Comparison of Models and ANOVA | Code
    Thursday, 20 October, 2022

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

    Problem Set #3

  12. Graphics with ggplot2 | Rmd file
    ablation.csv
    Data wrangling with tidyverse | Code
    Tuesday, 25 October, 2022