Frequently Asked Questions

Posit Cloud is a full R programming environment (namely, RStudio) that you can access from your web browser, requiring no software or package installation on your part. All of the programming activities and homework assignments, as well as any auxiliary data files, will be distributed via Posit Cloud.

Sign up for a free Posit Cloud account here, and then join the STAT 4710 workspace by clicking the link in the fourth bullet point of this Ed Discussion announcement.

You may use your personal Posit Cloud workspace but not the class workspace; the latter is intended to be used only for class activities and homeworks.

Yes, you may use your own computer. However, you will be responsible for installing R and RStudio on your computer, as well as installing all of the R packages necessary to complete the homework. Due to limited teaching staff bandwidth, we will not be able to assist you with this process. However, Google and ChatGPT are great resources.

No, you must use R for this course.

Read the error message carefully. Sometimes, the message will suggest a solution. If not, try Googling the error message. If this does not help, try asking ChatGPT. If you still need help, either post on Ed Discussion or come to office hours.

• Avoid using underscores or other special characters in chunk headers or figure/table captions. If you must use special characters, you must *escape* them by prepending them with two backslashes. For example, use \\% instead of %.
• Put a blank line between each code chunk and the subsequent text, especially for code chunks containing figures.
• You might not have loaded all necessary R packages.
• Your R code may have bugs. Usually the error message will point you to a line number where the code broke. Debug your code by stepping through it line-by-line interactively before compiling your report.
• Try asking Google or ChatGPT for help.
• If you are stuck, post on Ed Discussion or come to office hours and the teaching staff will assist you.

Yes, you may. Please see the Syllabus and the instructor statement on AI for more information.

The readings are highly recommended. Especially in the first unit of the course, the learning curve for R programming will be steep and we will not be able to cover everything in class. All of the content in the readings is fair game for homeworks, quizzes, and exams.

The best way to prepare for quizzes is to work through the quiz practice questions and last year's quizzes, all available from the main course webpage or Canvas. Furthermore, students should have a strong conceptual understanding of all material from lectures. Students are encouraged to come to office hours to verify and solidify their understanding of the material.

Quizzes will typically have ten questions each.

The best way to prepare for exams is the same as the best way to prepare for quizzes.

This is not decided yet, but there will likely be in the range of 20-30 questions per exam.

This is the first year that exams have this format, so there are no exams from previous years. Due to the limited time of the teaching staff, we are unable to write a practice exam for you. However, the exam questions will be of a similar style to quiz questions, so going through the quiz practice questions and the quiz questions from this year and last will be a good way to prepare for exams.

We do not offer quiz or exam makeups. However, each student's lowest quiz grade will be dropped. Furthermore, each student may miss up to one quiz if the instructor approves the reason for the absence. Please see the Syllabus section "Policies concerning quizzes and exams" for more information.

Yes, your lowest quiz grade will automatically be dropped. Please see the Syllabus for more information.

Your three free late days are intended to offset such circumstances. Once you use these free late days, each day late will come with a 10-point late penalty. Please see the Syllabus for more details on the late policy.

Ultimately, the decision of whether to stay in this class is up to you. Here, I will provide some suggestions. If you are missing some of the statistical prerequisites, then you will begin the class at a disadvantage compared to most of your classmates. If you are able and willing to put in the extra time to make up for this difference, then you may want to stay in the class. If your plate is already full with other responsibilities, then you may want to drop the class. In order to make a more informed opinion, I recommend you read through Chapters 3, 4.3, 6.2, 6.4, and 7.1-7.4 of ISLR, and try some of the corresponding exercises. Chapter 3 is some of the material I will expect you to know already, and the other chapters include material we will cover in this class.