MAT 241 - Modern Statistics with Software (R), Hybrid
Syllabus (Fall 2025)
Course Description: This is a fundamental course in modern-day data, data visualization, and the application of statistical techniques to analyze and make inferences from sample data. In a world where data is being constantly collected, it is necessary for individuals to be data literate, to have exposure to the power of data, and to understand as well as practice proper and ethical analyses with data. In a world where data has become abundant, rather than scarce, statistical tools are evolving. This course looks at modern statistical techniques in the age of “Big-Data”.
Software Use: Students in this course should expect to use R and RStudio locally. I’ve written setup
instructions
for all required software and packages for this course. If you are a student planning to complete
this course with a Chromebook or tablet, then you may create a Posit Cloud
account and copy this pre-built Posit Cloud Workspace to
utilize R and RStudio from a web-browser.
Still not quite sure what to expect? Check out this in-browser version of the Day 1 Material
Note on Hybrid Structure: This section of Modern Statistics with Software is running in a hybrid
environment. That means that the class physically meets only once per week. Students will be expected
to do the vast majority of learning and work outside of class meetings.
Course Timeline and Notebooks
Below is a tentative timeline for our course. It includes a week by week summary of responsibilities. Several of the optional slide decks mention homework assignments and due dates in the closing. For this particular section, please ignore those and default to BrightSpace and/or the Items Due column in the table below.
| Week | Activities | Discussion Slides (Optional) | Items Due |
|---|---|---|---|
| Week 1: September 1 – 5 | Meeting 1: Course Overview and Preview Topic 1 Notebook: Introduction to Data Topic 2 Notebook: Introduction to R |
Intro to R | Week 1 assignment due in BrightSpace Submit notebook hash codes by 11:59pm on 9/5 |
| Week 2: September 8 – 12 | Meeting 2: Review of Introductory notebooks, basics of Quarto, and preview of Exploratory Data Analysis (EDA) Topic 3 Notebook: Descriptive Statistics Topic 4 Notebook: Data Visualization |
Descriptive Statistics Data Visualization |
Submit notebook hash codes by 11:59pm on 9/12 |
| Week 3: September 15 – 19 | Meeting 3: Review of EDA and Preview of Probability Topic 5 Notebook: Discrete Probability Topic 6 Notebook: Normal Distribution |
Discrete Probability Normal Distribution |
Submit notebook hash codes by 11:59pm on 9/19 |
| Week 4: September 22 – 26 | Meeting 4: Probability Review and Practice Practice Probability Problems Review Weeks 1 – 3 |
||
| Week 5: September 29 – October 3 | Meeting 5: Exam Preview Exam Week |
Complete Exam I on MyOpenMath by 11:59pm on 9/26 Submit Practical Exam I in BrightSpace by 11:59pm on 10/3 |
|
| Week 6: October 6 – 10 | Meeting 6: Exam Debrief and Preview of Inference Topic 9 Notebook: Foundations for Inference Topic 10 Notebook: Introduction to Inference Lab |
Introduction to Inference | Submit notebook hash codes by 11:59pm on 10/10 |
| Week 7: October 13 – 17 | Meeting 7: Additional Discussions on Inference and Preview of Formal Inference Techniques and Tools Topic 11 Notebook: Inference for Categorical Data Topic 12 Notebook: Inference Practice |
Inference for Proportions Additional Practice |
Submit notebook hash codes by 11:59pm on 10/17 |
| Week 8: October 20 – 24 | Meeting 8: More Practice with Inference Topic 13 Notebook: Inference for Categorical Data (Lab) Topic 14 Notebook: Chi Squared Tests |
Chi Squared | Submit notebook hash codes by 11:59pm on 10/24 |
| Week 9: October 27 – 31 | Meeting 9: Overview of Inference for Categorical Variables and Preview of Inference for Numerical Variables Topic 15 Notebook: Inference for Numerical Variables Topic 16 Notebook: Inference Practice (Start) |
Inference on Means Additional Practice (not slides) |
Submit notebook hash codes (Topic 15 only) by 11:59pm on 10/31 |
| Week 10: November 3 – 7 | Meeting 10: Continued Practice with Inference Topic 16 Notebook: Inference Practice (Finish) |
Two Examples and Error Types Continue Additional Practice (not slides) |
Submit notebook hash codes (Topic 16 only) by 11:59pm on 11/7 |
| Week 11: November 10 – 14 | Meeting 11: Additional Practice with Inference on Categorical and Numerical Variables for One and Two Populations Topic 17 Notebook: Inference for Numerical Data (Lab) Review for Exam II |
Reading Software Output Additional Practice (Answer Key) |
Submit notebook hash codes (Topic 17 only) by 11:59pm on 11/14 |
| Week 12: November 17 – 21 | Meeting 12: Exam Preview Exam Week |
Complete Exam II on MyOpenMath by 11:59pm on 11/21 Submit Practical Exam II in BrightSpace by 11:59pm on 11/21 |
|
| Week 13: November 24 – 28 | Optional Tuesday Class Meeting for MAT241 Thanksgiving Break (Wednesday – Friday) |
||
| Week 14: December 1 – 5 | Meeting 14: Exam Debrief and ANOVA [and beyond] Preview Topic 18 Notebook: Analysis of Variance Topic 19 Notebook: Linear Regression (Lab) |
ANOVA and Linear Regression | Submit notebook hash codes by 11:59pm on 12/5 |
| Week 15: December 8 – 12 | Meeting 15: Review and [In-Class] Final Exam Preview Prepare for Final Exam |
||
| Week 16: December 15 – 19 | Meeting 16: Final Exam, Part I (No Tech) At Home Final Exam |
Complete in-class Final Exam on 12/16 Complete Take-Home Final Exam on MyOpenMath by 11:59pm on 12/19 |