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Last updated: Sun Oct 12 2025, 15:40
| Step | Due Date |
|---|---|
| Data Selection/Project Proposal | October 10 |
| Data Reading/Check In | October 31 |
| Presentations | November 14 |
It’ll be the full 80 minutes. You may bring a notecard and a calculator. If you do not have a calculator you may leave your answer unsimplified. Eg predicted price = $ e^2.19.
| Study Guide | Date |
|---|---|
| Exam 1 Study Guide | Wednesday October 15th |
All homework is due at 9pm unless clearly specified otherwise.
| Rmd | Due Date | Helpful Things |
|---|---|---|
| Homework 1 | October 1st | Examples of the graphs you’ll be remaking |
| Title | Author | Journal | Year | Quiz |
|---|---|---|---|---|
| Tidy Data | Hadley Wickham | Journal of Statistical Software | 2014 | 9/15 |
| Principles of Effective Data Visualization | Stephen R. Midway | Patterns | 2020 | 10/6 |
Please note that you are fully allowed (encouraged even!) to visit during office hours to talk about the required reading if you’d like. I’m glad to chat about it and discuss any questions you might have. Also please note that I’d like you to understand the broad strokes of the paper/what the author is getting at. I will avoid quizzing you over the nitty-gritty details.
| Date | Lecture | Lab | Suggested Reading |
|---|---|---|---|
| Friday 8/28 | Syllabus | - | - |
| Introduction | - | IMS Sections 1.2.1-1.2.3 |
Assignments and Deadlines
Install R (https://cran.r-project.org/)
Install RStudio (https://posit.co/download/rstudio-desktop/)
Begin thinking of interesting data sources for you midterm projects
| Date | Lecture | Lab | Suggested Reading |
|---|---|---|---|
| Wednesday 9/3 | Intro to R | lab 1 | - |
| - | - | lab 1 Helpful Hints | - |
| Friday 9/5 | Visualizations in R | Continue lab 1 | - |
Assignments and Deadlines
| Date | Lecture | Lab | Suggested Reading |
|---|---|---|---|
| Monday 9/8 | Finish Data Visualization | - | |
| Wednesday 9/10 | Data Visualization Part II | lab 2 (to be posted later) | - |
| Friday 9/12 | Data Visualization Part III Accessibility | data vis lab- |
Assignments and Deadlines
| Date | Lecture | Lab | Suggested Reading |
|---|---|---|---|
| Monday 9/15 | ggplot2 | finish lab 2, ggplot 2 lab | - |
| Wednesday 9/17 | finish ggplot 2 lab | - | |
| ggplot2 lab helpful hints | |||
| Friday 9/19 | Numeric Summaries | If time work on ggplot2 lab | - |
Assignments and Deadlines
| Date | Lecture | Lab | Suggested Reading |
|---|---|---|---|
| Monday 9/22 | Numeric Summaries Cont. | NumericCode Along | |
| Wednesday 9/24 | Correlations | Numeric Code along finished | |
| Friday 9/26 | Finish Correlations | Correlation Code along | |
| Correlation Code along finished |
Assignments and Deadlines
| Date | Lecture | Lab | Suggested Reading |
|---|---|---|---|
| Monday 9/28 | Simple Linear Regression (SLR) | ||
| Wednesday 10/01 | Simple Linear Regression Cont. | ||
| Friday 10/03 | Cor., SLR, and R\(^2\) Lab |
Assignments and Deadlines
| Date | Lecture | Lab | Suggested Reading |
|---|---|---|---|
| Monday 10/6 | Regression: Transformations | Slide 29 corrected | |
| Wednesday 10/8 | Trans. continued, indicators possible | code along (not done) | |
| Wednesday 10/8 | Indicators Alternative Slide Deck | Same material, presented differently | |
| Friday 10/10 | Transform and Indicator (Non-graded) Lab | Solutions to Transform and Indicator lab |
Assignments and Deadlines
Welcome to the course website for SST 115, Introduction to Statistics. To begin, you can find the course syllabus linked below:
You can locate course content by scrolling, or by using the outline in the upper left. Please note: material will not be posted until we’ve reached that point in the course.
My goal is to include the R code that I use to make different graphs, expamples, etc…, for the course. Most of it will be more advanced than what I will teach you or that you need but I want you to have access to examples if you’d like.
Please go here.