make title more generic

mjskay · Aug 17, 2018 · 292af3b · 292af3b
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Showing 7 changed files with 15 additions and 11 deletions.
diff --git a/.gitignore b/.gitignore
@@ -2,3 +2,4 @@
 .Rhistory
 .RData
 *.Rproj*
+*_cache/
diff --git a/hops_proportions_files/figure-gfm/quantile-dotplots-1.png b/hops_proportions_files/figure-gfm/quantile-dotplots-1.png
diff --git a/hops_proportions_files/figure-gfm/unnamed-chunk-4-1.png b/hops_proportions_files/figure-gfm/unnamed-chunk-4-1.png
diff --git a/hops_proportions.Rmd → proportions.Rmd b/hops_proportions.Rmd → proportions.Rmd
@@ -1,11 +1,11 @@
 ---
-title: "Hypothetical Outcome Plots (HOPs) for proportions"
+title: "Hypothetical outcome plots (HOPs) and quantile dotplots for proportions"
 output: github_document
 bibliography: references.bib
 link-citations: true
 ---
 
-Here is a quick example of hypothetical outcome plots (HOPs) for proportions
+Here is a quick example of two frequency-framing approaches to visualizing the uncertainty in a proportion: hypothetical outcome plots (HOPs), which are useful when you are using a medium that supports animation, and quantile dotplots, which are useful when you are using a medium that does not support animation.
 
 ## Setup
 
@@ -47,7 +47,7 @@ One *possible* model for this data is as follows (N.B. this makes some strong as
 m = stan_glm(count ~ group, family = poisson, data = df)
 ```
 
-## HOPs
+## Hypothetical outcome plots (HOPs)
 
 Given that model, we could construct a HOPs [@Hullman2015; @Kale2018] bar chart illustrating the posterior distribution for the proportion in each group:
 
@@ -73,7 +73,7 @@ p = df %>%
 animate(p, nframes = n_hops * 2, width = 600, height = 300)
 ```
 
-## Quantile dotplots (static alternative)
+## Quantile dotplots
 
 If animation were not available (e.g. in a print medium), an alternative might be a quantile dotplot [@Kay2016; @Fernandes2018]:
 

diff --git a/hops_proportions.md → proportions.md b/hops_proportions.md → proportions.md
@@ -1,8 +1,11 @@
-Hypothetical Outcome Plots (HOPs) for proportions
+Hypothetical outcome plots (HOPs) and quantile dotplots for proportions
 ================
 
-Here is a quick example of hypothetical outcome plots (HOPs) for
-proportions
+Here is a quick example of two frequency-framing approaches to
+visualizing the uncertainty in a proportion: hypothetical outcome plots
+(HOPs), which are useful when you are using a medium that supports
+animation, and quantile dotplots, which are useful when you are using a
+medium that does not support animation.
 
 ## Setup
 
@@ -53,7 +56,7 @@ an example, your mileage may vary\!):
 m = stan_glm(count ~ group, family = poisson, data = df)
 ```
 
-## HOPs
+## Hypothetical outcome plots (HOPs)
 
 Given that model, we could construct a HOPs (Hullman, Resnick, and Adar
 [2015](#ref-Hullman2015); Kale et al. [2019](#ref-Kale2018)) bar chart
@@ -82,9 +85,9 @@ p = df %>%
 animate(p, nframes = n_hops * 2, width = 600, height = 300)
 ```
 
-![](hops_proportions_files/figure-gfm/hops-1.gif)<!-- -->
+![](proportions_files/figure-gfm/hops-1.gif)<!-- -->
 
-## Quantile dotplots (static alternative)
+## Quantile dotplots
 
 If animation were not available (e.g. in a print medium), an alternative
 might be a quantile dotplot (Kay et al. [2016](#ref-Kay2016); Fernandes
@@ -125,7 +128,7 @@ df %>%
   scale_y_continuous(breaks = NULL)
 ```
 
-![](hops_proportions_files/figure-gfm/quantile-dotplots-1.png)<!-- -->
+![](proportions_files/figure-gfm/quantile-dotplots-1.png)<!-- -->
 
 ## References
 

diff --git a/hops_proportions_files/figure-gfm/hops-1.gif → proportions_files/figure-gfm/hops-1.gif b/hops_proportions_files/figure-gfm/hops-1.gif → proportions_files/figure-gfm/hops-1.gif
diff --git a/proportions_files/figure-gfm/quantile-dotplots-1.png b/proportions_files/figure-gfm/quantile-dotplots-1.png