Methods and Computing

Instructor: Benjamin Smith, (Email)

Syllabus

Click here to download the syllabus

Lectures

Lecture materials will be updated prior to the start of the lecture. There will be exercises for you to test your knowledge, and solutions will be provided after the lecture. If you have any questions, feel free to send me an email.

This course page will be updated periodically with new materials, so please check back often.

Module 0: Basic R Programming

This year, knowledge of basic R programming, RMarkdown, and RStudio will be assumed. Please familiarize yourself with the slides below for information on these topics (if you aren’t already).

Module 1: Tidyverse basics; data wrangling & graphing; Using LLMs to generate R code

R style guide - Full Guide

Suppliment 1: Git and Github

Module 2: Statistical inference (I)

Suppliment 2: Probability Theory

Module 3: Statistical inference (II)

Module 4: Linear Regression & Generalized Linear Models

Module 5: Simulation and parallel computing; Bootstrap

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This webpage was made using the distill R package and RStudio. GitHub Repo for this website: https://github.com/jlgrons/UofT-DoSS-SPB.