Content for running instances of STAT 545/547M at UBC

View the Project on GitHub STAT545-UBC/Classroom


Assignments will be posted here as they are made available.

(Information about the peer review can now be found on the peer review page.)


Here are the deadlines for assignments, with links (to appear after assignments are released). All submissions are due by 23:59.

STAT 545

Assignment Assignment Due Date
Homework 01 September 18, 2018
Homework 02 September 25, 2018
Homework 03 October 02, 2018
Homework 04 October 09, 2018
Homework 05 October 19, 2018

STAT 547

UPDATE Nov 28, 2018: We will take the top four homework grades when calculating your final grade, which means you don’t have to do homework 10.

Assignment Assignment Due Date
Homework 06 November 09, 2018
Homework 07 November 13 15, 2018
Homework 08 November 20 21, 2018
Homework 09 November 27, 2018
Homework 10 Optional December 06, 2018


Here is the general flow that will happen for the assignments.

  1. When an assignment is released, I will post a GitHub Issue in Discussion-Internal, tagging the teaching team and students (you should get an email notification, too, unless you’ve somehow disabled this, are not Watching the Discussion-Internal repo, or did not inform me of your GitHub username).
  2. You will be prompted to create a repository through GitHub Classroom. Develop your homework responses on this repository, which will be contained in the STAT545-UBC-students Organization.
  3. Upon completion, it would be useful for you to submit a link to your URL in the UBC Canvas page. We will be putting your grades there.


Components of each assignment will be graded on a 3-point scale. Here is the general rubric (also consult any specific guidance given in the relevant assignment itself).

Topic Excellent: 3 Satisfactory: 2 Needs work: 1
Coding style Student has gone beyond what was expected and required, coding manual is followed, code is well commented Coding style lacks refinement and has some errors, but code is readable and has some comments Many errors in coding style, little attention paid to making the code human readable
Coding strategy Complicated problem broken down into sub-problems that are individually much simpler. Code is efficient, correct, and minimal. Code uses appropriate data structure (list, data frame, vector/matrix/array). Code checks for common errors Code is correct, but could be edited down to leaner code. Some "hacking" instead of using suitable data structure. Some checks for errors. Code tackles complicated problem in one big chunk. Code is repetitive and could easily be functionalized. No anticipation of errors.
Presentation: graphs Graph(s) carefully tuned for desired purpose. One graph illustrates one point Graph(s) well chosen, but with a few minor problems: inappropriate aspect ratios, poor labels. Graph(s) poorly chosen to support questions.
Presentation: tables Table(s) carefully constructed to make it easy to perform important comparisons. Careful styling highlights important features. Table(s) generally appropriate but possibly some minor formatting deficiencies. Table(s) with too many, or inconsistent, decimal places. Table(s) not appropriate for questions and findings. Major display problems.
Achievement, mastery, cleverness, creativity Student has gone beyond what was expected and required, e.g., extraordinary effort, additional tools not addressed by this course, unusually sophisticated application of tools from course. Tools and techniques from the course are applied very competently and, perhaps,somewhat creatively. Chosen task was acceptable, but fairly conservative in ambition. Student does not display the expected level of mastery of the tools and techniques in this course. Chosen task was too limited in scope.
Ease of access for instructor, compliance with course conventions for submitted work Access as easy as possible, code runs! Satisfactory Not an earnest effort to reduce friction and comply with conventions and/or code does not run

The grade mapping is as follows:

Grade Percentage
0 0%
1 50%
2 80% 90%
3 100%

Intermediate points are allowed, and follow a linear scale in between each point.

Peer Review

Information about the peer review can now be found on the peer review page.