Draft episode/lesson content #15

brymz · 2016-12-27T16:40:42Z

The PR closes #13 with a rebase to include #14 in the history

brymz · 2016-12-28T21:49:31Z

This PR is ready for review.

I chose to develop the bones of a lesson in draft form to present more specific content that we can work from to continue to focus and develop the lesson structure. I incorporated feedback from #12 into the episode content without major revisions to the structure of the lesson. More detailed feedback may motivate such revisions.

gvwilson · 2016-12-29T13:11:04Z

_episodes/01-introduction.md

+
+### Audience
+
+Have you ever seen a figure that tried to convey way too much? Or a figure that just didn't seem to give you any useful information?


Add "Have you ever worried that you've created such figures yourself, and wondered if there was a reliable way to do better?"

gvwilson · 2016-12-29T13:11:23Z

_episodes/01-introduction.md

+This lesson is for scientists that are getting started using R to analyze their
+data and want to know more about data visualization using `ggplot2` and want to
+practice choosing the best figure to present their data and data analysis. The
+lesson should prepare you to choose and generate the best publication quality chart to answer your research question.


does the chart answer the research question?

address (?)

gvwilson · 2016-12-29T13:11:58Z

_episodes/02-data-management.md

@@ -9,119 +9,148 @@ objectives:
 - "To read Gapminder data to R"
 - "To evaluate Gapminder data structure"
 keypoints:
- "Be sure to `setwd()` to point to your data file before importing it."
+- "Be sure to setup an RStudio project or `setwd()` to point to your data file
+  before importing it."


"Be sure to setup" => "Set up"

gvwilson · 2016-12-29T13:12:50Z

_episodes/02-data-management.md

@@ -149,3 +178,5 @@ names(data)
 > > B.  38
 > {: .solution}
 {: .challenge}
+
+[data]: {{ site.baseurl }}/data/gapminder_all.csv


+1 to putting all the URLs at the bottom like this - we should do that for all our lessons.

gvwilson · 2016-12-29T13:14:48Z

_episodes/03-data-structures.md

+
+The shape of your data ought to be rectangular and can be described by the number of rows and columns.
+
+Column in your data can also be called __variables__ or __fields__. However, the general use of the term __variable__ to describe a column can also be used more specifically to describe numerically continuous data. As a complement to this specific use of variables, __categories__ describe discrete or categorical data


No change now, but you can also use [variables]({{site.baseurl}}/reference/#variable) to refer to a glossary entry in reference.md.

gvwilson · 2016-12-29T13:14:58Z

_episodes/03-data-structures.md

+Numerical values should be recognized as __absolute__ or __relative__. Absolute
+values receive context by their units, while relative values are standardized in
+some fashion (i.e., proportion, per unit) and most often used for comparison
+among categories.


Good summary.

gvwilson · 2016-12-29T13:16:10Z

_episodes/03-data-structures.md

+2. No duplicate rows
+3. Every cell contains one value
+4. One column per type of information
+5. No redundant information


Include link to Wickham's "Tidy Data" paper http://vita.had.co.nz/papers/tidy-data.pdf

gvwilson · 2016-12-29T13:16:43Z

_episodes/05-questions.md

@@ -13,6 +13,61 @@ keypoints:
 - "A well detailed research question can be answered with a good chart." 
 ---

+## Gapminder Ignorance Project


Why "ignorance"?

I think that is its name. The foundation name is Gapminder. The project name is Ignorance. I got these general questions from the about section of the Ignorance Project - https://www.gapminder.org/ignorance/.

gvwilson · 2016-12-29T13:16:55Z

_episodes/05-questions.md

+world view from a deeper understanding of reliable statistics. From their data,
+we can begin to formulate some research questions to explore:
+
+What are the major trends in global populations and economies?


Turn this into a bulleted list?

gvwilson · 2016-12-29T13:17:58Z

_episodes/05-questions.md

+
+## Defining your research question for visualization
+
+Dr. Andrew Abela from Catholic University of America and 'Extreme Presentation'


Link to Abela's home page?

I think "Extreme Presentation" is Abela's company, so probably more accurate to say "Dr. Andrew Abela from the Catholic University of America put together..."

gvwilson · 2016-12-29T13:18:28Z

_episodes/06-good-chart.md

+2. Determine the broad category that describes the goal of your research
+   question from [Choosing a Good Chart][good-chart]. 
+   - *You may need to redefine
+   or focus your research question to better suit visualization.*


Why make this a sub-bullet? Why not inline in the main bullet (in italics)?

I think you're right that conceptually the note is part of the main bullet. I just don't like how it looks. It extends the line across the page (unlike the other points) and has an awkward wrap. If you feel strongly about it, I would be happy to make the change or consider a different option.

gvwilson · 2016-12-29T13:20:11Z

_episodes/09-pub-quality-figs.md

+All visualization elements are clearly labeled and/or included in a legend and
+are described in the accompanying caption for the graphic. These elements
+include the axis, data shape and color, and any statistical elements giving
+analytical context to the data.


Q: is it worth having a callout somewhere saying that not all figures need to be publication quality? I.e., it's OK to cut corners and do the "wrong" thing sometimes, and explain when?

potentially relevant recommendation to reference: Rule 9 from Ten Simple Rules for Better Figures: Message Trumps Beauty

Figure 8. Message trumps beauty.
This figure is an extreme case where the message is particularly clear even if the aesthetic of the figure is questionable. The uncanny valley is a well-known hypothesis in the field of robotics that correlates our comfort level with the human-likeness of a robot. To express this hypothetical nature, hypothetical data were used () and the figure was given a sketched look (xkcd filter on matplotlib) associated with a cartoonish font that enhances the overall effect. Tick labels were also removed since only the overall shape of the curve matters. Using a sketch style conveys to the viewer that the data is approximate, and that it is the higher-level concepts rather than low-level details that are important [10].

gvwilson · 2016-12-29T13:20:23Z

_episodes/09-pub-quality-figs.md

+~~~
+{: .r}
+
+> ## Density Plot Fill-in Challenge Continued


gvwilson · 2016-12-29T13:20:42Z

_episodes/11-bubble-chart.md

-    across the world per country in 2007?"
-   Relationship with three variables (*at least two are continuous*)
-   Bubble Chart
+> ## What is it's category?


"its" (possessive) rather than "it's" (contraction of "it is")

gvwilson · 2016-12-29T13:22:40Z

_episodes/15-summarize.md

+2. Determine the broad category that describes the goal of your research
+   question from [Choosing a Good Chart][good-chart]. 
+   - *You may need to redefine
+   or focus your research question to better suit visualization.*


Again, why a sub-bullet?

gvwilson

Thanks for all of this - the lesson is looking really good.

brymz · 2017-01-04T19:50:17Z

Thanks for the thoughtful feedback, @gvwilson & @aflaxman. I have made revisions or added comments as per the review. This is ready for another look.

brymz added 6 commits December 27, 2016 10:35

introduction.md: add prereq sect

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01-introduction: draft episode content

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02-data-management.md: draft episode content

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03-data-structures.md: draft episode content

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04-dplyr.md: draft episode content

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05-questions.md: draft episode content

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brymz mentioned this pull request Dec 27, 2016

WIP: Draft episode/lesson content #13

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brymz added 13 commits December 27, 2016 13:26

05-questions.md: draft episode content

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06-good-chart.md: draft episode content

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07-ggplot.md: draft episode content

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08-line-histogram.md: draft episode content

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09-pub-quality-figs.md: draft episode content

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11-bubble-chart.md: draft episode content

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12-tidyr.md: draft episode content

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13-faceted-bar-chart.md: draft episode content

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14-stacked-area-chart.md: draft episode content

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15-summarize.md: draft episode content

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03-data-structures.md: ' -> __ for terms

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05-questions.md: add Avela book reference

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07-ggplot.md: footnote link format

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brymz changed the title ~~WIP: Draft episode/lesson content~~ Draft episode/lesson content Dec 28, 2016

gvwilson reviewed Dec 29, 2016

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_episodes/09-pub-quality-figs.md

~~~

{: .r}

> ## Density Plot Fill-in Challenge Continued

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Nice work.

gvwilson reviewed Dec 29, 2016

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Revise episodes as per GW comments

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Draft episode/lesson content #15

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brymz commented Jan 4, 2017


		### Audience

		Have you ever seen a figure that tried to convey way too much? Or a figure that just didn't seem to give you any useful information?


		The shape of your data ought to be rectangular and can be described by the number of rows and columns.

		Column in your data can also be called __variables__ or __fields__. However, the general use of the term __variable__ to describe a column can also be used more specifically to describe numerically continuous data. As a complement to this specific use of variables, __categories__ describe discrete or categorical data


		## Defining your research question for visualization

		Dr. Andrew Abela from Catholic University of America and 'Extreme Presentation'

Draft episode/lesson content #15

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brymz commented Jan 4, 2017