253 lines
5.1 KiB
Markdown
253 lines
5.1 KiB
Markdown
# Visualizing Uncertainty
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## CAPP 30239
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---
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<!--
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What is this trying to show?
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source: https://www.ipcc.ch/report/ar6/wg1/figures/chapter-3/figure-3-4/
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-->
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---
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<!--
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These are showing essentially the same thing, one shows individual models and the other uses some aggregates with confidence intervals.
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These are from the same page of the IPCC report.
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-->
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---
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## What causes uncertainty?
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1) **measurement error** - An instrument used has some non-perfect degree of accuracy. In a survey, this could be a poorly-worded question.
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2) **model uncertainty** - Models make assumptions and simplifications, different assumptions lead to different outcomes.
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3) **sampling variability** - Differences between sample & population.
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4) **missing data** - How missing data is accounted for & represented.
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The result is that we have a range or distribution, where we want a number to use with one of our channels (Hue, X, Y, etc.).
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---
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## Challenges of Uncertainty
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Often left out, in part due to being hard to understand, and even harder to visualize.
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Omission however misleads audiences, especially where a lot of significant figures are included.
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*Global Population Uncertainty: ±160 million people (2%)*
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## Challenges of Uncertainty
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Uncertainty estimates are simplified, often out of necessity.
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30% chance of rain: "A 30% chance that at least 0.01" of rain will fall somewhere within a given area over a 12 hour period."
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**Do I bring an umbrella?**
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---
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## Challenges of Uncertainty
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Complexity of visualization can overwhelm audience, obscure other meaning.
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From a data-ink ratio perspective, it is understandable why if the error bars do not seem relevant to a narrative, that they would be omitted.
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---
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## Including Uncertainty
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If omitting uncertainty misleads, it violates our prime directive of **graphical integrity**.
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The job then, is to find ways that are **audience appropriate** & **don't obfuscate the meaning**.
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The difficulty will be in resolving this tension.
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---
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## Common Techniques
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- Uncertainty as Probability
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- Error Bars
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- Confidence Bands
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---
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## Uncertainty As Probability
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Random waffle chart: works for cases with discrete outcomes.
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---
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## Uncertainty As Probability
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In practice, we often care about more than boolean outcome.
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<!--
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We can convert this to discrete measurements: quantile dot plot.
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-->
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---
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<!-- source: fivethirtyeight -->
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---
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## Uncertainty of Point Estimates
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These work when we're focused on uncertainty around a particular outcome.
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Sometimes we need to show uncertainty around discrete measurements, or projections.
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---
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### Error Bars
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---
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### Error Bands
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```python
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line = alt.Chart(source).mark_line().encode(
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x='Year',
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y='mean(Miles_per_Gallon)'
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)
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band = alt.Chart(source).mark_errorband(extent='ci').encode(
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x='Year',
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y=alt.Y('Miles_per_Gallon').title('Miles/Gallon'),
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)
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band + line
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```
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---
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### Issues with Error Bars & Confidence Bands
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1) There is no pre-defined meaning of these intervals.
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**If error bars or bands are included, the legend must include information on the meaning.**
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2) Error bars are common in scientific & academic literature, other audiences cannot be assumed to understand them.
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3) Restricted to 1D/2D dots. If variable being expressed is mapped to color, area, etc. then alternative presentations needed.
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---
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---
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### Variations on Error Bars & Intervals
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<!-- when appropriate, can also be used to show multiple intervals -->
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---
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<!--care should be taken that distribution is indeed normal if curves/etc. chosen -->
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---
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---
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### Regression Uncertainty
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---
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### Regression Uncertainty
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---
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## Other Approaches
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### Showing Multiple Futures
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---
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---
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### Hurricane Uncertainty
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<div class="container">
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<div class="col">
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</div>
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<div class="col">
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</div>
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</div>
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<!-- source: https://tamucoa.b-cdn.net/app/uploads/2021/10/House2011TrackUncertaintyVisualization.pdf -->
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---
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### On Maps
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<!-- source: https://www.e-education.psu.edu/geog486/sites/www.e-education.psu.edu.geog486/files/Lesson_07/Images/ex_vs_ont.PNG -->
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---
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### "Sketchiness"
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---
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### Animating Uncertainty
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- <https://www.nytimes.com/interactive/2018/03/27/upshot/make-your-own-mobility-animation.html>
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- HOP Plot: <https://vallandingham.me/animating_uncertainty.html>
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---
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## References & Acknowledgements
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- <https://mucollective.co/uncertainty_collection/>
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- <https://clauswilke.com/dataviz/visualizing-uncertainty.html>
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- <https://www.mjskay.com/presentations/aalto2020-uncertainty.pdf>
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- <https://nightingaledvs.com/dark-sky-weather-data-viz/>
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