This is an on-line course so attendance is really the work you put in during your study. You are strongly encouraged to follow all the lecture slides and video, do the suggested readings and possibly even some or most of the extra readings. Most importantly, you need to try the examples and code we show, and experiment with it. Failure to do so may not have a direct effect on your course grade, but will likely have a significant indirect effect. Any known or potential extracurricular conflicts should be discussed in person with the instructor during the first week of classes, or as soon as they arise.

As a proxy for class participation, we consider participation in the Github issue topic discussion which, for an online class, is the closest we have to class discussions.

Smaller online tasks which are no-less required for smooth operations may be give a points as well. Examples are creation of a Github user account and formation of a project team.


Homework assignments serve as a way to interact with the material outside of the classroom. Homework will be due at either 8:00 PM on the assigned due date, which should generally be Thursday. You are allowed to drop one homework assignment over the course of the semester. In other words, while we aim for about six total assignments, with the lowest homework score being dropped the score will be the mean of the top five homeworks.

As a result, late homework will not be accepted. There will be no exceptions to this policy. Please start early, make sure your environment is working correctly, and that you are able to produce a working document. We have a course assistant with on-campus office hours, but in order to ask meaningful questions you need to try answering the material first.

Collaboration Policy

While working on homework, students are encouraged to work together in a group of at most 3 students. Students who opt to work together must list the full names and netids of the students that they have collaborated with at the top of the document. Each student must also turn in their own homework answers. This means that students should not share or copy homework answers, which may involve written explanations and code. In general, students should strive to independently write answers to the homework problems. Failure to do so will likely result in an academic integrity investigation being opened.

In addition, there is a lot of R (and shell, sql, …) code on the internet. Many students will be tempted to copy and paste code online or request help from programming communities. This behavior is okay as long as you cite where the code originated from and are not having someone answer the question in verbatim. Any code that is not cited but is able to be matched with available works online will be treated as plagiarism and fall under the class’ academic integrity policy.

Distribution Policy

Each homework will be distributed via PrairieLearn. We have GitHub as an option.


We you are logged into PrarieLearn, you are identified via your NetID and your submissions will be stored as combination of your NetID and the question. This should make it easy and failsafe to identify your submission.

Assignment Submission


Via PrairieLearn, answers are submitted directly in the web form.

Here are a few do and don’t tips for the submission. Consider the following stanza from the third homework:

# Enter your code below
# Do not alter the function signature: ensure it remains named 'iris_summary'
# and takes one argument
# Ensure you return a data.frame as indicated in the question

iris_summary <- function(irisdata) {

  # Enter code here


and consider these recommendations carefully:

  • Do follow the structure of the provided function. In general, the will be a stanza of the form above.
  • Do enter code where it says # Enter code here. That is a function body.
  • Do not write code before the opening brace.
  • Do not write code after the closing brace.
  • Do use the supplied irisdata object. The function signature clearly states that that is the (only) input you need and are given.
  • Do not load other data. You do not need data(something). You do not need to load anything (unless specifically asked when a question is about data loading or saving).
  • Do use the stated variable names: when the interface (or our instructions) say irisdata, do not deviate to iris or iris_data or any other form. Do write code to match the name exactly.
  • Do not load other packages unless asked to do so. We generally expect you to use an explicitly named package, or just the functions already in R, i.e. what is called ‘base R’.
  • Do follow the instructions. When it asks to return a data.frame do not return a matrix or data.table. Return a data.frame.
  • Do use the GitHub issue ticket linked to each question.
  • Do not post code or (partial or complete) answers at GitHub.


If GitHub is used for the assignment, homework must be submitted online through the GitHub Repository generated for each student.

The online submission must contain:

  • hw01-NetID.Rmd
  • hw01-NetID.html or hw01-NetID.pdf

The NetID component represents your NetID, e.g. the NetID is what is in front of your email, and 01 represent the two-digit homework assignment number. Inside the .Rmd file, please make sure to update the author value away from "Full Name (NetID)" to your name and NetID.

As an example, on the fifth homework assignment, your instructor, whose netid is deddel, would submit:

  • hw05-deddel.Rmd
  • hw05-deddel.html or hw05-deddel.pdf
  • Any files needed to create the output document, e.g. hw05-deddel.html, from hw05-deddel.Rmd.

The hw05-deddel.Rmd file would have

title: 'hw05: Radio Statistics'
subtitle: 'STAT 430 - Fall 2019'
author: 'Dirk Eddelbuettel (deddel)'
date: 'Due: Friday, Month Day, YYYY at HH:MM PM'
output: html_document

Depending on the assignment, you may need to place in the GitHub repository additional assets. For example, screenshots, scripts, or a package.

In general, the file structure for hw01 would look like:

|- /
   |- hw01-NetID.Rmd
   |- hw01-NetID.html
   |- image-exercise1.png
   |- image-exercise2.png
   |- image-exercise3.png
   |- test/
       |- render_rmds.R
   |- .travis.yml 
   |- project.Rproj 

All digital submissions must be made using either the RStudio git client or by using git terminal. Avoid adding, creating, renaming, or removing a file via the GitHub web interface. Any student found to be using the GitHub web interface to submit their homework will lose all points associated with committing.

Along with STAT 385, this is presently the only class that emphasizes git skills within the Statistics department curriculum. Please do not try to circumvent learning this skill.


Each homework assignment will be a variable number of points; however, each homework assignment will have equal weight towards your final grade. Grades will be based on both accuracy and presentation of information. In general, you should make your document as easy to read for the CAs as possible.

Documents that are difficult to read will receive overall point reductions depending on the level of difficulty.


  • Please read every exercise carefully. If the wording of an exercise is problematic, immediately let the course staff know.
  • Include your name and NetID in the final document, not only in your filenames.
  • Your .Rmd file must be written such that, when stored in a folder with any data you are asked to import, it will knit properly without modification. If your git repository is organized properly, this should not be an issue. That is, you should generally use relative references to external files.
  • Your resulting .html or .pdf file will be considered a “report” which is the material that will determine the majority of your grade. Be sure to visibly include all R code and output that is relevant to answering the exercises. (You do not need to include irrelevant code you tried that resulted in error or did not answer the question correctly.)
  • Be aware of directions for code randomization for each exercise.


Instead of examinations, there will be to six weekly quizzes — see the page Schedule on the left that begin during Week 3. The quizzes, just like the homework, will (generally) focus on the preceding (two weeks of) lectures and are (generally) not cumulative over the full course content.

And just like with the homework, you are allowed to drop one quiz grade over the course of the semester. We aim for six quizzes in total, and with the lowest quiz score being dropped the score will be the mean of the top five quiz scores.

This course uses the College of Engineering Computer Based Testing Facility (CBTF) in the Grainger Engineering Library in room 57 for its quizzes and exams:

As a result, students are both free to choose their examination date and time within a specified examination period, and answering questions using a computer.

Students will need to go to the CBTF to take the quiz. The examinations are tenatively scheduled to open in the morning and close in the evening. See the CBFT site for details on hours.

The policies of the CBTF are the policies of this course, and academic integrity infractions related to the CBTF are infractions in this course.

If you have accommodations identified by the Division of Rehabilitation-Education Services (DRES) for exams, please take your Letter of Accomodation (LOA) to the CBTF proctors in person before you make your first quiz reservation. The proctors will advise you as to whether the CBTF provides your accommodations or whether you will need to make other arrangements with your instructor.

Any problem with testing in the CBTF must be reported to CBTF staff at the time the problem occurs. If you do not inform a proctor of a problem during the test then you forfeit all rights to redress.

Group Project

There are several components associated with the group final project. They are:

  • Project Proposal
  • Project Report
  • Evaluation of Peers
  • Evaluations from Peers

See the (course-private) GitHub repository for details.


There are no midterm or final examinations in this course. Instead, we have homework, quizzes, and a group project.

Late or Missing Work

Late work will not be accepted for homework or the group project. Watch the deadlines, and plan accordingly.

As the date and time of an exam is chosen by a student over an examination window, there will be no make-up exams administered once the window closes.


Regrade requests must be made in writing within 3 days of when the assessment is returned. Please write an e-mail to the instructor that describes the grade issue and provides justification as to why a regrade should occur. Make sure to include what the grade is and what it should be. Please note, by disputing any grading, you agree to allow the course staff to review the entire assessment for other errors missed during grading.

Common requests for regrades:

  • Points totalled incorrectly
  • Answer should be considered correct

Course Grades

Type Percentage
Homework 35
Quizzes 35
Group Project 30

Grading is discretionary and generally done by both the instructor and course assistant. We may reflect online participation a com

Grading Scale

Minimum Grade Points
A- to A+ 90 to 100
B- to B+ 80 to 89.99
C- to C+ 70 to 79.99
D- to D+ 60 to 69.99
F below 60

Each ten point range is equally split over the three components (i.e. from minus to plus).

Grades may be curved at the end of term before being finalized.