Spring 2022 - STAT 360 D100

Advanced R for Data Science (2)

Class Number: 6875

Delivery Method: In Person

Overview

  • Course Times + Location:

    Tu 2:30 PM – 4:20 PM
    AQ 3005, Burnaby

  • Prerequisites:

    One of STAT 260 or STAT 341 and one of STAT 302, STAT 305, STAT 350, or ECON 333, all with a minimum grade of C-. CMPT 125 or CMPT 129 is also recommended. Corequisite: STAT 361.

Description

CALENDAR DESCRIPTION:

Advanced R programming methods for data science. Tools for reproducible research. Version control. Data structures, subsetting, functions, environments, and debugging. Functional programming. Code performance: profiling, memory, integrating R and C++.

COURSE DETAILS:

Course Outline:

  • Tools for reproducible research: RStudio, RMarkdown, version control with Git, collaborating with GitHub
  • Data structures, subsetting, control flow, functions, environments, conditions.
  • Functional programming.
  • Object-oriented programming
  • Code performance: debugging, profiling, memory, integrating R and C++.

COURSE-LEVEL EDUCATIONAL GOALS:

With an emphasis on modern methods, this course will introduce students to tools for reproducible research (RStudio and Markdown), data handling, data cleaning, visualization, and exploratory analysis.

Grading

  • bi-weekly quizzes, best 5 out of 6 50%
  • project 20%
  • Final Exam 30%

NOTES:

Above grading is subject to change

Materials

RECOMMENDED READING:

Advanced R, 2nd ed. by Hadley Wickham, Publisher CRC Press

Available online for free at https://adv-r.hadley.nz/
ISBN: 9780815384571

Department Undergraduate Notes:

Tutor Requests:
Students looking for a tutor should visit https://www.sfu.ca/stat-actsci/all-students/other-resources/tutoring.html. We accept no responsibility for the consequences of any actions taken related to tutors.

Registrar Notes:

ACADEMIC INTEGRITY: YOUR WORK, YOUR SUCCESS

SFU’s Academic Integrity web site http://www.sfu.ca/students/academicintegrity.html is filled with information on what is meant by academic dishonesty, where you can find resources to help with your studies and the consequences of cheating.  Check out the site for more information and videos that help explain the issues in plain English.

Each student is responsible for his or her conduct as it affects the University community.  Academic dishonesty, in whatever form, is ultimately destructive of the values of the University. Furthermore, it is unfair and discouraging to the majority of students who pursue their studies honestly. Scholarly integrity is required of all members of the University. http://www.sfu.ca/policies/gazette/student/s10-01.html

TEACHING AT SFU IN SPRING 2022

Teaching at SFU in spring 2022 will involve primarily in-person instruction, with safety plans in place.  Some courses will still be offered through remote methods, and if so, this will be clearly identified in the schedule of classes.  You will also know at enrollment whether remote course components will be “live” (synchronous) or at your own pace (asynchronous).

Enrolling in a course acknowledges that you are able to attend in whatever format is required.  You should not enroll in a course that is in-person if you are not able to return to campus, and should be aware that remote study may entail different modes of learning, interaction with your instructor, and ways of getting feedback on your work than may be the case for in-person classes.

Students with hidden or visible disabilities who may need class or exam accommodations, including in the context of remote learning, are advised to register with the SFU Centre for Accessible Learning (caladmin@sfu.ca or 778-782-3112) as early as possible in order to prepare for the spring 2022 term.