index bugfixes

Author: trevorcampbell

source/clustering.Rmd

@@ -295,7 +295,7 @@ improves it by making adjustments to the assignment of data
 to clusters until it cannot improve any further. But how do we measure
 the "quality" of a clustering, and what does it mean to improve it?
 In K-means clustering, we measure the quality of a cluster
-by its\index{within-cluster sum-of-squared-distances|see{WSSD}}\index{WSSD} *within-cluster sum-of-squared-distances* (WSSD).
+by its\index{within-cluster sum of squared distances|see{WSSD}}\index{WSSD} *within-cluster sum-of-squared-distances* (WSSD).
 Computing this involves two steps.
 First, we find the cluster centers by computing the mean of each variable
 over data points in the cluster. For example, suppose we have a

source/intro.Rmd

@@ -388,7 +388,7 @@ filtering the rows. A logical statement evaluates to either `TRUE` or `FALSE`;
 `filter` keeps only those rows for which the logical statement evaluates to `TRUE`.
 For example, in our analysis, we are interested in keeping only languages in the
 "Aboriginal languages" higher-level category. We can use
-the *equivalency operator* `==` \index{logical statement!equivalency operator} to compare the values
+the *equivalency operator* `==` \index{logical operator!equivalency} to compare the values
 of the `category` column with the value `"Aboriginal languages"`; you will learn about
 many other kinds of logical statements in Chapter \@ref(wrangling).  Similar to
 when we loaded the data file and put quotes around the file name, here we need

source/reading.Rmd

@@ -78,7 +78,7 @@ into R, but before we can talk about *how* we read the data into R with these
 functions, we first need to talk about *where* the data lives. When you load a
 data set into R, you first need to tell R where those files live. The file
 could live on your  computer (*local*)
-\index{location|see{path}} \index{path!local, remote, relative, absolute}
+\index{location|see{path}} \index{path!local}\index{path!remote}\index{path!relative}\index{path!absolute}
 or somewhere on the internet (*remote*).
 
 The place where the file lives on your computer is referred to as its "path". You can

source/regression1.Rmd

@@ -303,8 +303,8 @@ Note that for the remainder of the chapter
 we'll be working with the entire Sacramento data set,
 as opposed to the smaller sample of 30 points
 that we used earlier in the chapter (Figure \@ref(fig:07-small-eda-regr)).
-\index{training data}
-\index{test data}
+\index{training set}
+\index{test set}
 
 ```{r 07-sacramento-seed-before-train-test-split, echo = FALSE, message = FALSE, warning = FALSE}
 # hidden seed -- make sure this is the same as what appears in reg2 right before train/test split

source/version-control.Rmd

@@ -204,7 +204,7 @@ Once you reach a point that you want Git to keep a record
 of the current version of your work, you need to **commit** \index{git!commit}
 (i.e., snapshot) your changes. A prerequisite to this is telling Git which
 files should be included in that snapshot. We call this step **adding** the
-files to the **staging area**. \index{git!add, staging area}\index{staging area|see{git}}
+files to the **staging area**. \index{git!add}\index{git!staging area}\index{staging area|see{git}}
 Note that the staging area is not a real physical location on your computer;
 it is instead a conceptual placeholder for these files until they are committed.
 The benefit of the Git version control system using a staging area is that you

source/viz.Rmd

@@ -356,7 +356,7 @@ visual noise to remove. But there are a few things we must do to improve
 clarity, such as adding informative axis labels and making the font a more
 readable size.  To add axis labels, we use the `xlab` and `ylab` functions. To
 change the font size, we use the `theme` function with the `text` argument:
-\index{ggplot!xlab,ylab}
+\index{ggplot!xlab}\index{ggplot!ylab}
 \index{ggplot!theme}
 
 ```{r 03-data-co2-line-2, warning=FALSE, message=FALSE, fig.height = 3.1, fig.width = 4.5, fig.align = "center",  fig.cap = "Line plot of atmospheric concentration of CO$_{2}$ over time with clearer axes and labels."}
@@ -675,11 +675,11 @@ to assess a few key characteristics of the data:
 
 - **Direction:** if the y variable tends to increase when the x variable increases, then y has a **positive** relationship with x. If
   y tends to decrease when x increases, then y has a **negative** relationship with x. If y does not meaningfully increase or decrease
-  as x increases, then y has **little or no** relationship with x. \index{relationship!positive, negative, none}
+  as x increases, then y has **little or no** relationship with x. \index{relationship!positive}\index{relationship!negative}\index{relationship!none}
 - **Strength:** if the y variable *reliably* increases, decreases, or stays flat as x increases,
-  then the relationship is **strong**. Otherwise, the relationship is **weak**. Intuitively, \index{relationship!strong, weak}
+  then the relationship is **strong**. Otherwise, the relationship is **weak**. Intuitively, \index{relationship!strong}\index{relationship!weak}
   the relationship is strong when the scatter points are close together and look more like a "line" or "curve" than a "cloud."
-- **Shape:** if you can draw a straight line roughly through the data points, the relationship is **linear**. Otherwise, it is **nonlinear**. \index{relationship!linear, nonlinear}
+- **Shape:** if you can draw a straight line roughly through the data points, the relationship is **linear**. Otherwise, it is **nonlinear**. \index{relationship!linear}\index{relationship!nonlinear}
 
 In Figure \@ref(fig:03-mother-tongue-vs-most-at-home-scale-props), we see that
 as the percentage of people who have a language as their mother tongue increases,