diff --git a/R_examples/EDA.Rmd b/R_examples/EDA.Rmd
index ec597ab..0fae152 100644
--- a/R_examples/EDA.Rmd
+++ b/R_examples/EDA.Rmd
@@ -196,18 +196,13 @@ This examines the same data but with a relative ranking approach for quality. Ea
 ```{r H3descriptives}
 ##revision quality
 artDF$pct_revert <- (artDF$got_reverted / artDF$revid) * 100
-table(artDF$taboo)
+table(artDF$source)
 hist(artDF$got_reverted)
 hist(log(artDF$got_reverted))
 hist(artDF$revid)
 hist(log(artDF$revid))
-## facet these hists by source!!
-#cor.test(artDF$got_reverted, as.numeric(artDF$taboo))
-#cor.test(artDF$revid, as.numeric(artDF$taboo))
-#hist(log(artDF$got_reverted))
-#hist(log(artDF$revid))
 
-cor.test(artDF$pct_revert, as.numeric(artDF$taboo))
+cor.test(artDF$pct_revert, as.numeric(artDF$source))
 cor.test(artDF$revid, artDF$pct_revert)
 
 #drop Barack Obama
@@ -215,16 +210,16 @@ artDF <- subset(artDF, artDF$taboo!='0.5')
 table(artDF$taboo)
 artDF$taboo <- as.logical(artDF$taboo)
 
-g <- ggplot(artDF, aes(x=revid, y=pct_revert, color=taboo)) +
+g <- ggplot(artDF, aes(x=revid, y=pct_revert, color=source)) +
   geom_point() +
   labs(x='Number of Revisions', y='Percent Reverted')
 
 g
 
-ggplot(artDF, aes(x=got_reverted, color=taboo)) +
+ggplot(artDF, aes(x=got_reverted, color=source)) +
   geom_boxplot()
 
-g <- ggplot(artDF, aes(group=as.factor(taboo), x=revid, y=got_reverted, color=taboo)) +
+g <- ggplot(artDF, aes(group=as.factor(taboo), x=revid, y=got_reverted, color=source)) +
   geom_point(alpha=.2) +
   geom_smooth() +
   geom_rug(alpha=.2)+
@@ -234,7 +229,7 @@ g <- ggplot(artDF, aes(group=as.factor(taboo), x=revid, y=got_reverted, color=ta
 
 g
 
-g <- ggplot(artDF, aes(group=as.factor(taboo), x=revid, y=pct_revert, color=taboo)) +
+g <- ggplot(artDF, aes(group=as.factor(taboo), x=revid, y=pct_revert, color=source)) +
   geom_point(alpha=.2) +
   geom_smooth() +
   geom_rug(alpha=.2)+
@@ -281,7 +276,7 @@ xTabAnon <- xtabs(~source+revert+anon,data=revDF.clean.norev)
 ftable(xTabAnon)
 prop.table(ftable(xTabAnon), 1)
 
-ggplot(revDF.clean.norev, aes(x=anon, color=taboo)) +
+ggplot(revDF.clean.norev, aes(x=anon, color=source)) +
   geom_boxplot()
 ```
 
@@ -326,13 +321,13 @@ g
 ```{r}
 summary(revDF.clean$userpage_text_chars)
 
-g <- ggplot(revDF.clean, aes(x=log1p(userpage_text_chars), group=taboo)) +
+g <- ggplot(revDF.clean, aes(x=log1p(userpage_text_chars), group=source)) +
   geom_histogram(binwidth = .5) +
   facet_grid(source~., scales='free_y')
 
 g
 
-g <- ggplot(subset(revDF.clean, revDF.clean$userpage_text_chars < exp(4)), aes(x=log1p(userpage_text_chars), group=taboo)) +
+g <- ggplot(subset(revDF.clean, revDF.clean$userpage_text_chars < exp(4)), aes(x=log1p(userpage_text_chars), group=source)) +
   geom_histogram(binwidth = .5) +
   facet_grid(source~., scales='free_y')
 
@@ -380,8 +375,6 @@ prop.table(table(gaveGenderDF$source, gaveGenderDF$gender), margin = 1)
 
 table(revDF.clean$emailable)
 
-table(userDF$emailable)
-
 prop.table(table(revDF.clean$source, revDF.clean$emailable), margin = 1)
 
 ```
@@ -390,19 +383,16 @@ prop.table(table(revDF.clean$source, revDF.clean$emailable), margin = 1)
 
 ```{r protection}
 
-artDF.prot.only <- subset(artDF.prot, artDF.prot$pct.prot > 0)
-artDF.prot.only <- subset(artDF.prot.only, artDF.prot.only$taboo != 0.5)
 
-
-g <- ggplot(artDF.prot.only, aes(x=pct.prot, group=taboo)) +
+g <- ggplot(artDF, aes(x=pct.prot, group=source)) +
   geom_boxplot() + 
   labs(x='Protection Proportion')
 
 g
 
-t.artDF <- subset(artDF.prot.only, artDF.prot.only$pct.prot > 0)
+artDF.prot <- subset(artDF, artDF$pct.prot > 0)
 
-g <- ggplot(t.artDF, aes(x=pct.prot, group=taboo)) +
+g <- ggplot(artDF.prot, aes(x=pct.prot, group=source)) +
   geom_boxplot() + 
   labs(x='Protection Proportion (non-zero only)')