ETC5521: Diving Deeply into Data Exploration
Lecturer/Chief Examiner
- Professor Di Cook
- Email: etc5521.clayton-x@monash.edu
- Consultation: Thu 11:00-12:00, 352 Education Blg, and zoom
Tutors
- Krisanat Anukarnsakulchularp
- Tutorials: Wed 9:30-11:00am and 7:30-9:00pm CL_Anc-19.LTB_134
- Consultation: Mon 9.30-11:00 am, Menzies W9.20
Weekly schedule
- Lecture: Tues 10-12 on zoom (link in Moodle)
- Tutorial: 1.5 hours
- Weekly learning quizzes due each Wednesday 9am, from week 2
Assessments
- Weekly learning quizzes: 5%
- Assignment 1: Instructions (15%)
- Assignment 2: Instructions (20%)
- Assignment 3: Instructions (20%)
- Assignment 4 part 1: Instructions (20%)
- Assignment 4 part 2: Instructions (20%)
Software
We will be using the latest versions of R and RStudio.
Here is the code to install (most of) the R packages we will be using in this unit.
install.packages(c("tidyr", "dplyr", "readr", "readxl", "readabs", "forcats", "tsibble", "cubble", "lubridate", "ggplot2", "GGally", "ggthemes", "sugrrants", "ggbeeswarm", "plotly", "gganimate", "tourr", "sugarbag", "tsibbletalk", "visdat", "inspectdf", "naniar", "validate", "vcd", "mvtnorm", "nullabor", "visage", "forecast", "cassowaryr", "brolgar", "palmerpenguins", "housingData", "broom", "kableExtra", "lvplot", "colorspace", "patchwork"), dependencies=TRUE)
From GitHub, install
remotes::install_github("casperhart/detourr")
If you are relatively new to R, working through the materials at https://learnr.numbat.space is an excellent way to up-skill. You are epsecially encouraged to work through Chapter 3, on Troubleshooting and asking for help, because at some point you will need help with your coding, and how you go about this matters and impacts the ability of others to help you.
These materials are licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.