04 critique reordering
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@ -5,7 +5,10 @@
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- Review common rules & mistakes.
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- Review common rules & mistakes.
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- What makes a useful critique?
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- What makes a useful critique?
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- Look at a lot of data viz examples.
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- **Look at a lot of examples.**
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Like any kind of visual art, creating good visualizations takes *learning to see*.
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@ -22,8 +25,8 @@
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- Data variation, not design variation.
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- Data variation, not design variation.
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- Maximize data-ink ratio.
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- Maximize data-ink ratio.
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- Remove all chart junk. (gridlines, shadows, 3d effects)
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- Strip out chart junk. (gridlines, shadows, 3d effects)
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- Context: title, axes, units, important events.
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- Add Context: title, axes, units, important events.
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- Alignment/Proximity: make comparisons easy & avoid misleading choices like changing axes between two otherwise identical graphs
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- Alignment/Proximity: make comparisons easy & avoid misleading choices like changing axes between two otherwise identical graphs
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@ -31,10 +34,8 @@
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## What to Look For
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## What to Look For
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**Expressiveness**: Does every choice further the understanding of the data?
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**Expressiveness**: Does every choice further the understanding of the data?
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- Example: Consistent and clear channel mappings.
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**Effectiveness**: Can audience decipher data and meaning quickly?
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**Effectiveness**: Can audience decipher data and meaning quickly?
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- Example: Highlighting of primary elements.
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**Non-Data Elements**
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**Non-Data Elements**
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- Title, Label, Caption, Data Source, Annotations
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- Title, Label, Caption, Data Source, Annotations
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@ -56,7 +57,7 @@
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You are the expert on your data source, and it can be challenging to look at things through the eyes of your audience.
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You are the expert on your data source, and it can be challenging to look at things through the eyes of your audience.
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Also it is likely that you've stared at variations of the same chart for an hour or more, easily overlooking small flaws.
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It is likely that you've stared at variations of the same chart for an hour or more, easily overlooking small flaws.
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Extra eyes will help you identify what people are actually taking away from your graphic:
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Extra eyes will help you identify what people are actually taking away from your graphic:
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@ -77,9 +78,13 @@ Extra eyes will help you identify what people are actually taking away from your
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**Offer alternatives.** What could be done differently?
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**Offer alternatives.** What could be done differently?
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- *"I like..."* - point out what works.
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---
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- *"I wish..."* - frame negative feedback as ways that it could improve for audience.
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- *"What if..."* - new ideas and alternatives to consider.
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## Critique Language
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**"I like..."** - point out what works.
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**"I wish..."** - frame negative feedback as ways that it could improve for audience.
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**"What if..."** - new ideas and alternatives to consider.
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**Be respectful.** Be mindful of your tone and word choice.
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**Be respectful.** Be mindful of your tone and word choice.
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@ -91,6 +96,10 @@ Extra eyes will help you identify what people are actually taking away from your
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**Bike-shedding.** Suggesting *arbitrary* changes based on your preferences. "If I made this, I'd have chosen green."
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**Bike-shedding.** Suggesting *arbitrary* changes based on your preferences. "If I made this, I'd have chosen green."
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![bg right height:200px](bikeshed.png)
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<https://bikeshed.org>
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---
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---
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## Receiving Critique
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## Receiving Critique
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@ -133,20 +142,73 @@ Extra eyes will help you identify what people are actually taking away from your
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---
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![bg fit](nightingale-mortality.jpg)
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## Practice Critique
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<!-- Crimean War via Livia, <https://edstem.org/us/courses/68015/discussion/5428917> -->
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---
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![bg fit](lee-1pct.png)
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![bg fit](nightingale-mortality.jpg)
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<!-- 1% of 1% via <https://sunlightfoundation.com/2013/06/26/1pct_of_the_1pct_polarization/> -->
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<!--
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Crimean War via Livia, <https://edstem.org/us/courses/68015/discussion/5428917>
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author: Florence Nightingale
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- legend?
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- labeling on the chart itself?
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-->
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---
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![bg fit](dubois-hourglass.png)
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<!--
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DuBois hourglass
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He pronounced his name De-bois
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not a pie chart! meant for direct comparison between the two types
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today this would be misread because people have seen pie charts
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-->
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![bg fit](chicago-segregation.png)
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![bg fit](chicago-segregation.png)
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<!-- Chicago Racial Segregation via Miguel, <https://edstem.org/us/courses/68015/discussion/5441644> -->
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<!--
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Chicago Racial Segregation via Miguel, <https://edstem.org/us/courses/68015/discussion/5441644>
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type: map
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-->
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---
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![bg fit](dubois-slaves.jpg)
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<!--
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DuBois slaves visualization
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-->
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---
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![bg fit](eye-colors.webp)
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<!--
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eye color
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uncertainity
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why are some slices larger than others?
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does the eye in the middle mislead?
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-->
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---
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![bg fit](lee-1pct.png)
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<!--
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1% of 1% via <https://sunlightfoundation.com/2013/06/26/1pct_of_the_1pct_polarization/>
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-->
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---
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---
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@ -229,29 +291,18 @@ Extra eyes will help you identify what people are actually taking away from your
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<!-- tribes in texas from Echo -->
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<!-- tribes in texas from Echo -->
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---
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![bg fit](eye-colors.webp)
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<!-- eye color-->
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---
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![bg fit](dubois-slaves.jpg)
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<!-- DuBois slaves -->
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---
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![bg fit](dubois-hourglass.jpg)
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<!-- DuBois hourglass -->
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---
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![bg fit](github.png)
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![bg fit](github.png)
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<!-- github -->
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<!--
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github
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two issues: scale is dependent on person's max commits
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more importantly: what we choose to visualize has an effect
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-->
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---
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