Exam 3 review

STA 210 - Spring 2022

Author

Dr. Mine Çetinkaya-Rundel

Exam instructions

The exam is an individual assignment. Everything in your repository is for your eyes only.
You may not collaborate or communicate anything about this exam to anyone except the instructor. For example, you may not communicate with other students, the TAs, or post/solicit help on the internet, email or via any other method of communication.
The exam is open-book, open-note, so you may use any materials from class as you take the exam.
No TA office hours will be held during the exam. You may not email the TAs questions about the exam.
If you have questions, email or Slack me.

Focuses on content Weeks 09 - 14, but can include material from previous weeks
Similar format as previous exams
- Part 1: Multiple choice/fill-in-the-blank questions on Sakai
- Part 2: Open-ended data analysis in GitHub and submitted on Gradescope

Goal: Assess your understanding of the course material and how the methods you learned are applied to the analysis of real-world data.
Include all of your analysis steps in your exam write up, unless stated otherwise.
- For example, if the exam says “assume conditions are met,” You can reference that information in your write up but don’t have to recheck the conditions.

You can identify the correct approach, analysis method, and/or inferential results required to answer the question.
You understand the correct conditions and diagnostics needed to determine whether the conclusions drawn from the model will be reliable
You can write results and conclusions in a meaningful way that can be understood by a general audience (think a business or research partner)
You can produce a report that is suitable for a professional audience (e.g., narrative is written in complete sentences, all graphs have proper titles and axis labels, there is not extraneous output, all Latex is rendered)
You can conduct the analysis using a reproducible data analysis workflow that incorporates version control