统计网课代修 | STAT300W – Statistical Communication Syllabus

本次加拿大网课代修主要为统计学中的Statistical Communication相关，以下为该门课程的Syllabus

Grading Scheme
– About 4 reading assignments (papers, book chapters) with a set of basic questions, graded on correctness, worth 15% in total.

– About 4 fully in-class assignments, graded on participation,worth 15% in total.

– About 8 partially in-class assignments, graded on grammar and organization, worth 45% in total.

– A take-home final essay, graded on grammar, organization,and depth. Worth 25%.

Teaching and material delivery: Flipped

– All the material will be on Canvas. (no books!)

– Lecture times are for group work and for questions and answers about the material.

– Office hours are for individual questions in case you don’t like talking in a group or can’t make it to the lectures.

– Attendance is optional but recommended because it will make the homework easier to do.

So what’s on Canvas for you?

The 2020 version of the course notes are already available.
Some of these will be updated, and a few chapters will be added, but most of the material will be the same.

Before each lecture time, there will be a voice recording of a lecture based on 1 or 2 chapters of the notes. I recommend you study by opening the notes and listening along, because the recordings are readings of the notes with extra commentary, details, and explanation.

A recording for a one-hour lecture will be about 35 minutes because dead space and answering questions is removed.

With stopping-and-starting for note-taking, it should still take at least an hour to get through a recording.

Assignments

In-class assignments will be assigned on Tuesdays (the two-hour classes), and due Wednesday at 10pm. You don’t have to be in class (i.e. in Zoom) for these assignments, but I recommend you show up so that I can help you.

Assignments should take less than an hour to do. If you show up for the lectures, you should be able to have the assignments mostly done during those lecture times.

The first 4 (or so) “fully in-class” assignments are participation / formative feedback based. Grading is based on completion,and I’m happy to give as much advice as you want.

Please take advantage of these times not just for the participation marks, but for the chance to see what will get a higher grade in other assignments.

The rest of the in-class assignments are “partially in-class”.
These are graded based on quality.

I will still give general advice, especially about how to structure an assignment or what I’m looking for, but things like grammar are mostly up to you.

Please take advantage of this too, but don’t expect to guarantee a 100% on an assignment just because I looked at it.

Course Schedule
Week 0 (Readings that are recommended before starting)
Grammar: “the” vs “a”
Grammar: Complete Sentences

Week 1 (Friday, May 14)
Syllabus, introduction
Digital writing tools

Week 2 (Tuesday, May 18, and Friday, May 21)
Participation In-Class exercise: Forming scientific questions.
Combining math and language
LaTeX: The basics and math mode

Week 3 (Tuesday, May 25, and Friday, May 28)
Participation In-Class Exercise: Translating formulae into words.
Sentence Length and Word Choice
Tone and style

Week 4 (Tuesday, June 1, and Friday, June 4)
Making a data scientist resume and CV.
Participation In-Class Exercise Resume Critique (BRING YOUR
RESUMES)
Tables
LaTeX: Tables, Figures, and Floats
Markdown: Huxtable

Week 5 (Tuesday, June 8 and Friday, June 11)
Graphs: Basic principles
In-class Exercise: Improving Graphs
Graphs: ggplot
In-class Exercise: Modifying ggplot graphs

Week 6 (Tuesday, June 15, and Friday, June 18)
Citing articles
Copyright issues, data and the law
The absolute basics of intellectual property law.
Latex: Bibtex

Week 7 (Tuesday, June 22, and Friday, June 25)
Writing general instructions and manuals
In-Class Exercise: Explain a statistical method
Writing a paper using the Skeleton Method
Prep for Final Essay/Paper