Types of Charts
Completion requirements
These lecture note slides walk through various charting options at your disposal. The slide collection also includes some working examples to show how one dataset can be visualized with many different charts. Take note of which charts are associated with each data type. Some are quite creative.
Three principles for visualization
- be true to your research – design your display to illustrate a particular point
- maximize information, minimize ink –use the simplest possible representation for the bits you want to convey
- organize hierarchically – what should a viewer see first? what if they look deeper?
Worked example
- Participants heard examples from an artificial language
- Three different presentation methods for examples – index cards, list of sentences, mp3 files on ipod
- Task was to spread $100 of "bets" across different continuations for a new example
- Dependent measure was bet on the correct answer
bar graph
bar graph with standard errors
bar graph with 95% CIs
box plot
viola plot
strip chart
strip chart with means
strip chart with means
Morals of the example
- Summary statistics
- almost always necessary
- but at what level of analysis?
- Distribution is important
- what is the form of the data?
- is your summary misleading?
- Fancier is not always better
- pretty pictures are awesome
- but not if they obscure the data
Source: Mike Frank and Ed Vul, https://ocw.mit.edu/courses/res-9-0002-statistics-and-visualization-for-data-analysis-and-inference-january-iap-2009/96df7f49cd50ed9bb0feb4793b9c8d89_lec1_visulzatn.pdf
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