Lecturers

Tutors

Consultations

All consultations will be in using zoom. Check Moodle for the links.

Expectations

Tentative Schedule

There are no lectures or tutorials during the midsemester break.

Week Lecturer Slides Tutorial Topic Readings Assessments
0 Di A: Course information
1 Di A: ; B: Overview. Why this course? What is EDA? 50 Years of Data Science
  • Reading quizzes each week.
  • Engagement each week counts.
2 Di A: ; B: Learning from history EDA Case Study: Bay area blues
3 Emi A: ; B: Initial data analysis: Model dependent exploration and how it differs from EDA The initial examination of data
4 Emi A: ; B: Working with a single variable, making transformations, detecting outliers, using robust statistics Case Study: Behaviours of dairy calves & Unwin (2015) Graphical Data Analysis Ch 3-4 Assignment 1 due Fri 28 Aug 11:55 PM
5 Di A: ; B: Bivariate dependencies and relationships, transformations to linearise Wilke (2019) Ch 7 Visualising distributions & Unwin (2015) Graphical Data Analysis Ch 5
6 Di A: ; B: Going beyond two variables, exploring high dimensions Wilke (2019) Ch 9 Visualising many distributions & Unwin (2015) Graphical Data Analysis Ch 6
7 Emi A: ; B: Making comparisons between groups and strata Unwin (2015) Graphical Data Analysis Ch 10 Assignment 2 due Fri 18 Sep 11:55 PM
Midsemester Break (2 weeks)
8 Emi A: ; B: Sculpting data using models, checking assumptions, co-dependency and performing diagnostics Cook & Weisberg (1994) An Introduction to Regression Graphics Ch 6 and Cleveland (1993) Visualising Data Ch 4
9 Di A: ; B: Exploring data having a space and time context Reintroducing tsibble: data tools that melt the clock; Unwin (2015) Graphical Data Analysis Ch 11
10 Di/Guest A: Exploring data having a space and time context Healy (2018) Data Visualization, Chap 7, Draw maps; Perpinan Lamigueiro (2018) Displaying Time Series, Spatial and Space-Time Data with R
11 Emi A: ; B: Using computational tools to determine whether what is seen in the data can be assumed to apply more broadly Wickham et al. (2010) Graphical inference for Infovis
12 Emi/Di Your turn to present your project work
  • Group presentation Mon 2 Nov 4:00PM.
  • Assignment 3 due Fri 6 Nov 11:55 PM