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Last updated: Tue Oct 14 2025, 13:04
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 | Friday October 17th |
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 |
Homework 2 | October 15th | CODE NEEDED RIGHT AFTER YOU READ IN THE DATA: legos$Year <- as.factor(legos$Year) |
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 |
---|---|---|---|
Fri 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 | H. Wickham discussing enviroments in R |
Friday 9/5 | Visualizations in R | Continue lab 1 | - |
Assignments and Deadlines
Date | Lecture | Lab | Suggested Reading |
---|---|---|---|
Monday 9/8 | Data Visualization II (Boxplots) | - | |
Wednesday 9/10 | Data Visualization III (Accessibility) | data vis lab | - |
Friday 9/12 | - | Finish lab 2 | - |
Assignments and Deadlines
Date | Lecture | Lab | Suggested Reading |
---|---|---|---|
Monday 9/15 | ggplot2 | ggplot2 lab | - |
Wednesday 9/17 | Finish ggplot2 lab | - | |
ggplot2 helpful hints | |||
Friday 9/19 | Numeric Summaries | Code Along |
Assignments and Deadlines
Date | Lecture | Lab | Suggested Reading |
---|---|---|---|
Monday 9/22 | Correlation if time | - | Finished Code Along |
Wednesday 9/24 | Correlation | - | Correlation Code Along |
Friday 9/26 | Simple Linear Regression Part 1 | Finished correlation code along |
Date | Lecture | Lab | Suggested Reading |
---|---|---|---|
Monday 9/29 | Finish Simple Linear Regression | Linear Regression Code Along | |
Wednesday 10/01 | Linear Regression Lab | ||
Wednesday 10/01 | Finish Lab |
Date | Lecture | Lab | Suggested Reading |
---|---|---|---|
Monday 10/06 | Transformations | Slide 29 corrected | |
Wednesday 10/08 | Transformations Finished, Categorical Predictors | Lego code_along | |
Wednesday 10/08 | Lego code_along_finished | ||
Friday 10/10 | Lego Code Along for Transforms | ||
Friday 10/10 | Lego Code Along for Transforms Done |
Assignments and Deadlines Assignments and Deadlines
Date | Lecture | Lab | Suggested Reading |
---|---|---|---|
Monday 10/06 | Simulations |
Assignments and Deadlines
Welcome to the course website for SAT 209, Applied 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.