Classes

Date	Title	Description
Jan 10, 2023	Week 01: Introduction	Why statistics? Why R? Why Quarto? Making a webpage and a plot in just seconds!
Jan 17, 2023	Week 02: Probability as a Model	A simple experiment. Random variables. Probability distributions. Probability as a model.
Jan 24, 2023	Week 03: Statistical Inference	Testing hypotheses, visualizing distributions, reading and writing tabular data, and learning how to work with it in R.
Jan 31, 2023	Week 04: Ordinary Least Squares	Calculating and testing bivariate statistics, including correlation and covariance. Visualizing probability densities. Fitting linear models using ordinary least squares. And some simple table indexing in R.
Feb 7, 2023	Week 05: Visualizing Distributions	A review and a deep dive into visualizing distributions in R, including bar chart, histogram, kernel density, cumulative density, and boxplot. Examples are given using base R {graphics} and {ggplot2}.
Feb 14, 2023	Week 06: Working with Tables	A review and a deep dive into working with rectangular data in R.
Feb 21, 2023	Week 07: Evaluating Linear Models	(Stats) Learn how to interpret linear models, make predictions, and use standard tests and diagnostics for evaluation, including making diagnostic plots. (R) Model summaries. Diagnostic plots. Prediction and plotting.
Feb 28, 2023	Week 08: Multiple Linear Models	(Stats) Learn how to interpret multiple linear models, make predictions, and use standard tests and diagnostics for evaluation, including making diagnostic plots. (R) Model summaries. Diagnostic plots. Prediction and plotting.
Mar 14, 2023	Week 10: Transforming Variables	(Stats) Learn how to add qualitative variables and transformed variables to linear models and interpret the results. (R) Scaling and centering variables, specifying model formulas to include intercept offsets, interactions, log transforms, and polynomial terms.
Mar 21, 2023	Week 11: Maximum Likelihood	(Stats) Making sense of maximum likelihood. (R) Learn how to save figures. Learn how to generate robust relative paths in project folders with `here()`.
Mar 28, 2023	Week 12: Logistic Regression	(Stats) Modeling binary outcomes and proportions with logistic regression. Evaluating GLMs with Deviance, Information Criteria, and the Likelihood Ratio Test. (R) Fitting logistic models and evaluating them with LRT.
Apr 4, 2023	Week 13: Poisson Regression	(Stats) Modeling count data with Poisson regression. Testing for dispersion and using a negative binomial to account for it. Log offsets. (R) Fitting Poisson and negative binomials models, testing for dispersion, and evaluating models with LRT.
Apr 11, 2023	Week 14: Partial Dependence	(Stats) Making sense of covariance in context. (R) Estimating and visualizing partial dependence.
Apr 18, 2023	Week 15: Regression Tables	(Stats) Nothing new. (R) How to report results of regression in a table with R.