Overview
The idea for the course is to be very applied and hands-on, and based around worked examples and case studies, with a focus on the code used to generate an analysis.
The course is entirely in R, and the goal of the course is as much to introduce students to R and develop R skills as to cover the theory of EDA.
Structure of the Course
24 lectures in classroom environment Mon/Wed/Fri 4-6pm.
8 lectures by Drs ebnem Er, 16 lectures by Mr Mzabalazo Ngwenya
Lecturers
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Photo credit Amanda Torr
Dr. Sebnem Er (she/her) is a senior lecturer at UCT, Statistical Sciences Department, and program coordinator for MSc Data Science degree at UCT.
I am located at PD Hahn Building 5th Floor, Room 5.55 however I will not be always in my office. If you would like to see me in person in my office please schedule a meeting by sending an email: Sebnem.Er@uct.ac.za
Grading
|Component|Weight| |Class exercises | 20%| |Assignment1|15%| |Assignment2|45%| |Exam|20%|
Resources
Exploratory Data Analysis with R by Roger Peng (RP)
STA545: Data wrangling, exploration, and analysis with R by Jenny Bryan (JB))
R for data science by Hadley Wickham (HW)
Exploratory Data Analysis, 1977 Addison-Wesley Publishing Company (John Wilder Tukey)
Exploratory Data Analysis: Past, Present and Future, 1993 Technical Report (John W Tukey)
How to look at data: A review of John W. Tukey’s Exploratory Data Analysis, 1979 (Russell M. Church
COURSE MATERIALS
There is no prescribed textbook for this course. Please follow the github link provided.
DULY PERFORMED AND EXAMINATION REQUIREMENTS
9. NOTICES
All correspondence with the department must contain your student number.
10. COMPUTER USE
You will have access to SCILAB C, D for several services: the Web, e-MAIL, R, WORD, and EXCEL.
All content for this course is available in this link. You will find all the necessary slides, pdfs, R examples in this link.
