Computing for the Social Sciences (Spring 2020)
Exploratory data analysis
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Computing for the Social Sciences (Spring 2020)
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Last edited by
deblina
on
Apr 15, 2020
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Exploratory data analysis
Learning objectives
Define
exploratory data analysis
(EDA) and types of pattern exploration
Demonstrate types of graphs useful for EDA and precautions when interpreting them
Practice exploring data
Approaches to EDA
Look for
variation
and
covariation
Don't need to have pretty charts (for publishing purposes, you want to add titles, legends, themes etc.)
Variation
dispersion of one variable
Histograms
w/ Rug plot gives 1D marginal distributions (best used with smaller, high-variance datasets)
Bin width is important!
Continous variables
Bar Chart
Categorical variables
Covariation
multiple variables (x and y axis)
Categorical on x, continuous on y -> boxplot
Two continuous -> scatterplots
Could also facet or layer variables on a single graph
When layering, use different channels to distinguish patterns
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