Spring 2019 - STAT 641 G100
Introduction to Statistical Computing and Exploratory Data Analysis - R (2)
Class Number: 3467
Delivery Method: In Person
Course Times + Location:
Th 12:30 PM – 2:20 PM
AQ 3181, Burnaby
Exam Times + Location:
Apr 16, 2019
8:30 AM – 11:30 AM
RCB IMAGTH, Burnaby
Prerequisites:STAT 285 or STAT 302 or STAT 305 or BUEC 333 or equivalent. Open only to students in departments other than Statistics and Actuarial Science.
Introduces the R statistical package in the context of statistical problems. Data management; reading, editing and storing statistical data; data exploration and representation; summarizing data with tables, graphs and other statistical tools; and data simulation. Students with credit for STAT 340 or STAT 341 may not take STAT 641 for further credit.
1. What is the R programming environment
- Downloading and installing
- Basics of writing R functions
- Basics of loops/if/while and other control-flow constructs
2. Data management in R
- Reading and writing data: plain text files and spreadsheets, other file formats
- Using R to query databases with SQL
- Merging and re-shaping data
3. Data exploration and representation in R
- Graphical displays. Customizing and extending these displays for your own research purposes.
- Cross-tabulations and tests of association.
4. Data simulation and resampling in R
a. Generating data from parametric distributions: uses in evaluating statistical procedures and in understanding classical large-sample results.
b. Generating data by resampling: introduction to permutation, bootstrapping, cross-validation and their uses.
- Quizzes 10%
- Homework Assignments 10%
- Term Test 30%
- Final Exam 50%
Above grading is subject to change.
Advanced R, Author: Hadley Wickham, Publisher: CRC Press 2015
ggplot2 Elegant Graphics for Data Analysis, 2nd ed., Author: Hadley Wickham, Publisher: Springer 2016
Graduate Studies Notes:
Important dates and deadlines for graduate students are found here: http://www.sfu.ca/dean-gradstudies/current/important_dates/guidelines.html. The deadline to drop a course with a 100% refund is the end of week 2. The deadline to drop with no notation on your transcript is the end of week 3.
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
ACADEMIC INTEGRITY: YOUR WORK, YOUR SUCCESS