2.2 Course Topics & Syllabus

Broadly speaking, the topics of this course are described by the Chapter Titles. Here’s what each entails:

  • Course Preliminaries: Introduction to R and the world of R
  • Installing R: Like it sounds, setting up your computer so you can work with R.
  • R Programming Fundamentals: The basics of programming in R, the building blocks that you need in order to do anything more interesting.
  • Working with Data: How to do meaningful things with data sets. Probably the most useful Chapter of the book.
  • Creating R Programs: More programming concepts to increase your R Power!

2.2.1 Syllabus

First, some important details:

  • Instructor: Lane Drew

  • Office Hours: Held in the Statistics Success Center (Weber 223A), schedule available on Canvas.

  • Webpages: Canvas, this textbook

  • Course Credits: 1. This means ~1 hours of lecture and 4 hours of work outside of lecture per week.

  • Textbook: You’re reading it right now. The textbook will be your primary learning resource. You’ll be expected to read through the required sections, watch any relevant videos, and complete any reflections, progress checks, and assessments along the way. On days when a quiz is due, you should complete the reading before you take the quiz.

  • Prerequisites: None

  • Assignments/What-to-turn-in: This course will be graded on three types of assignments: Progress Checks, Homeworks, and Quizzes. There will be four of each. Most weeks, you will have one of these three types of assignments due. Due dates will be specified on Canvas and assignments will be due at 11:59pm on the indicated day (please see schedule below).

  • Progress Checks: As you work your way through the textbook, you’ll encounter purple “Progress Check” boxes. For the first Progress Check, you’ll submit your responses directly to canvas. For Progress Checks 2-4, you’ll fill in an R Markdown document and submit it to canvas. You’ll be provided a template to fill in as you complete the progress checks. To turn in the document, you’ll knit the document to HTML or PDF and upload to Canvas. (More details coming later in the book!). Progress checks will be graded on completion, organization, and correctness. Progress Checks must be turned in by 11:59pm (Mountain) on the day they are due. Half credit will be given for a two-day window after the due date, after which no credit will be possible.

  • Homework: There are four homeworks during the semester. You’ll complete each homework using R. Homeworks must be turned in by 11:59pm (Mountain) on the day they are due. Half credit will be given for a two-day window after the due date, after which no credit will be possible.

  • Quizzes: There will be four 15 minute Canvas quizzes during the semester. Quizzes must be completed by 11:59pm (Mountain) on the day they are due. There are NO late quizzes accepted after the due date has passed. If you cannot complete the quiz on the day it is due, you are expected to do it early.

  • Exams: There will be no exams in this course

  • Lectures: Lectures will be held on Fridays. There will be mini-lectures, approximately 10-30 minutes. The mini-lectures will be based on previously read material, no new material will be presented. Students are expected to have read the material before the lecture. The reminder of the time will be student-led. We will cover questions students may have or work on homework together.

  • Grading: The grading for the course is apportioned like so:

    • Progress Checks: 30%
    • Homework: 40%
    • Quizzes: 30%

2.2.2 Assignment Templates

In order to complete the progress checks and course assignments, you’ll need to start from these templates:

Progress Checks

Assignments

2.2.3 Course Policies

  • Late Work: Homework and Progress Checks must be turned in on time to receive full credit. You may turn in Homework and Progress Checks up to 2 days late for up to 50% credit.
  • Group Work: Students are welcome to discuss the course with each other, but all work you turn in must be your own. This means no sharing solutions to homework, progress checks, or quizzes. You may not work with other students on quizzes. You are welcome to seek help on Canvas discussion boards and during office hours.
  • Students with Disabilities: The university is committed to providing support for students with disabilities. If you have an accommodation plan, please provide that to me as soon as possible so we can discuss appropriate arrangements.
  • Growth Mindset: This phrase was coined by Carol Dweck to reflect how your learning outcomes can be affected by the way you view the learning process. To quote Dweck: “The view you adopt for yourself profoundly affects the way you lead your life… Believing that your qualities are carved in stone - the fixed mindset - creates an urgency to prove yourself over and over. If you have only a certain amount of intelligence, a certain personality, and a certain moral character — well, then you’d better prove that you have a healthy dose of them. It simply wouldn’t do to look or feel deficient in these most basic characteristics… There’s another mindset in which these traits are not simply a hand you’re dealt and have to live with, always trying to convince yourself and others that you have a royal flush when you’re secretly worried it’s a pair of tens. In this mindset, the hand you’re dealt is just the starting point for development. This growth mindset is based on the belief that your basic qualities are things you can cultivate through your efforts. Although people may differ in every which way — in their initial talents and aptitudes, interests, or temperaments — everyone can change and grow through application and experience.” Programming may be a very new, intimidating thing for you. That’s okay! View this course as a way to grow and gain new skills which you can use to do incredible and important things!
  • Learn by doing: A wise statistics instructor once compared watching someone else solve statistics problems to watching someone else practice shooting basketball free throws. You may learn a little by watching, but at some point you won’t get any better until you try it yourself! The same can be said for programming. Reading a textbook and watching videos are a good start, but you’ll have to actually program in order to get any better! This textbook was designed to be interactive, and I encourage you to “code along with the book” as you read.

2.2.4 Grading Scale

Grades will be assigned according to the following scale:

Class.Score Letter.Grade
92%-100% A
90%-92% A-
88%-90% B+
82%-88% B
80%-82% B-
78%-80% C+
70%-78% C
60%-70% D
0%-60% F