ETC5521: Diving Deeply into Data Exploration
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Schedule
Week 1: Overview. Why this course? What is EDA?
Week 2: Learning from history
Week 3: Initial data analysis and model diagnostics: Model dependent exploration and how it differs from EDA
Week 4: Using computational tools to determine whether what is seen in the data can be assumed to apply more broadly
Week 5: Working with a single variable, making transformations, detecting outliers, using robust statistics
Week 6: Bivariate dependencies and relationships, transformations to linearise
Week 7: Making comparisons between groups and strata
Week 8: Going beyond two variables, exploring high dimensions
Week 9: Exploring data having a space and time context Part I
Week 10: Exploring data having a space and time context Part II
Week 11: Sculpting data using models, checking assumptions, co-dependency and performing diagnostics
Week 12: Long help session
Moodle
Resources
On this page
Reading
What you will learn this week
Lecture slides
Worksheet
Tutorial instructions
Week 1: Overview. Why this course? What is EDA?
Reading
The Landscape of R Packages for Automated Exploratory Data Analysis
What you will learn this week
How exploring data is different from a confirmatory analysis
Lecture slides
html
pdf
qmd
R
Worksheet
qmd
html
Tutorial instructions
html
qmd