Introduction to STA 235
Lecture 0
Dr. Emre Yucel
2026-08-25
Course Goals
- Use regression in all its forms to build models for inference and for prediction
- Understand the benefits and limitations of the models we build
- Given a new business situation, select an appropriate analysis, carry it out, and effectively communicate the results
- This is a practical course!
Contact Information
Instructor: Emre Yucel, Ph.D.
- Class meetings: Thursdays, 8:00am-9:45am (UTC 1.132)
- Office hours: Th 9:45am-11:00am (CBA 3.436)
- By appointment on Zoom (email to schedule)
- Email: emre.yucel@utexas.edu
- Phone: 832-408-1686
Course assistants:
- Course assistant: Yanai Tagor
- You can also attend any other TA/CAs office hours
Statistical Computing
- We will use R for statistical analysis throughout the course
- We will access R through the RStudio graphical interface; make sure both are installed on your laptop and bring it to every class
Weekly Cadence
- Before Thursday class: Perusall pre-class preparation
- During Thursday class: Checkpoint quiz, lecture, and interactive practice
- Due by 11:59pm Wednesday: Post-class practice covering the week’s topic
- Three class sessions: Team Labs
- Three scheduled sessions outside class: Team Cases
Pre-Class Reading Assignments
- This course moves quickly—review material before class.
- Use Perusall to ask questions, help others, and share your insights.
- Your participation shapes class discussion and deepens your understanding.
- Make a reasonable effort to engage meaningfully in the discussion for full credit.
In-Class Practice
- Understanding the concepts really comes from practice
- Class will be synchronous and in person; class time will be divided between lecture and practice
- We will use Learning Catalytics so you can practice the concepts during class
- Graded on participation, not correctness; answer 75% of the questions to get 100% of the credit
Post-Class Practice
- Due each Wednesday at 11:59pm
- Credit is based on completion; you have unlimited attempts and feedback to revise your answers
- You are encouraged to form study groups and discuss the work, but do not simply copy answers
- AI can help you get unstuck, but do not outsource your thinking or analysis
Checkpoint Quizzes
- It is critical in this course to stay on top of things and not fall behind
- Most classes start with a 15-minute Checkpoint Quiz covering the previous week’s material
- Each quiz is worth 40 points
- You may use one 8.5 x 11-inch reference page; both sides are allowed
- Complete quizzes on your own; AI and smart devices are not permitted
Team Labs and Team Cases
Team-based activities are a core part of the course:
- Team Labs: Three in-class, 40-point activities to practice course material with your team
- Team Cases: Three 100-point, authentic business analytics tasks completed with your team outside class
- For a Team Case, your team will analyze a data set, prepare slide(s) that answer the business questions, and selected members will present and answer questions
- Students begin with two virtual tokens that may be used to request an alternate makeup assignment within one week of a missed assignment
Grading Breakdown
| Assignment Type | Points per Item | Total Points |
|---|---|---|
| Pre-class Preparation | — | 45 |
| Class Participation | — | 40 |
| Post-class Practice | 5 | 55 |
| Checkpoint Quizzes | 40 | 440 |
| Team Labs | 40 | 120 |
| Team Cases | 100 | 300 |
| Total | 1,000 |
Getting Help
- My office hours
- CA/TA office hours
- Post questions about readings in Perusall (for questions about the reading)
- Post questions in group chats in Perusall (for general questions about the course or post-class practice)
- Send course questions through Canvas email