Fix a batch of older typos reported

ch_inference_for_means/TeX/comparing_many_means_with_anova.tex

@@ -300,7 +300,10 @@
 
 % 45
 
-\eoce{\qt{Prison isolation experiment, Part II\label{prison_isolation_anova}} Exercise~\ref{prison_isolation_T} introduced an experiment that was conducted with the goal of identifying a treatment that reduces subjects' psychopathic deviant T scores, where this score measures a person's need for control or his rebellion against control. In Exercise~\ref{prison_isolation_T} you evaluated the success of each treatment individually. An alternative analysis involves comparing the success of treatments. The relevant ANOVA output is given below.
+\eoce{\qt{Prison isolation experiment, Part II\label{prison_isolation_anova}} Exercise~\ref{prison_isolation_T} introduced an experiment that was conducted with the goal of identifying a treatment that reduces subjects' psychopathic deviant T scores, where this score measures a person's need for control or his rebellion against control. In Exercise~\ref{prison_isolation_T} you evaluated the success of each treatment individually. An alternative analysis involves comparing the success of treatments.
+The relevant ANOVA output is given below,
+and we have checked for you that there are no meaningful
+differences in variability across the groups.
 \begin{center}
 \begin{tabular}{lrrrrr}
   \hline
@@ -326,7 +329,7 @@
     If you did not reject the null hypothesis in
     part~(\ref{prison_isolation_anova_test_conclusion}),
     recheck your answer.
-    Summary statistics for each group are provided below
+    Summary statistics for each group are provided below.
 \begin{center}
 \begin{tabular}{l  r  r  r  r  }
 \hline

ch_probability/figures/eoce/cat_weights/cat_weights.R

@@ -13,5 +13,5 @@ hist(cats$Bwt, breaks = seq(2, 4, 0.25), ylim = c(0, 35),
      xlab = "Body weight", col = COL[1], main = "", 
      axes = FALSE)
 axis(1)
-axis(2, at = seq(5,35,10))
+axis(2, at = seq(0,40,10))
 dev.off()

ch_regr_simple_linear/TeX/line_fitting_residuals_and_correlation.tex

@@ -196,9 +196,11 @@
 \item Describe the relationship between distance and travel time.
 \item How would the relationship change if travel time was instead measured 
 in hours, and distance was instead measured in kilometers?
-\item Correlation between travel time (in miles) and distance (in minutes) 
-is $r = 0.636$. What is the correlation between travel time (in kilometers) 
-and distance (in hours)?
+\item The correlation between travel time (in miles) and distance (in minutes) 
+is $r = 0.636$.
+Suppose we had instead measured travel time in hours
+and measured distance in kilometers (km).
+What would be the correlation in these different units?
 \end{parts}\vspace{7mm}}
 \end{minipage}
 \begin{minipage}[c]{0.1\textwidth}

ch_summarizing_data/figures/eoce/county_hispanic_pop/county_hispanic_pop.R

@@ -13,8 +13,10 @@ pdf("county_hispanic_pop_hist.pdf", 7.5, 4)
 par(mar = c(3.8, 3.5, 0.5, 0.5), las = 1, mgp = c(2.5, 0.7, 0), 
     cex.lab = 1.5, cex.axis = 1.5)
 histPlot(county_complete$hispanic_2010, breaks = 25, 
-         xlab = "Hispanic %", ylab = "", 
-         col = COL[1])
+         xlab = "Percent Hispanic", ylab = "", 
+         col = COL[1], axes = FALSE)
+AxisInPercent(1, at = seq(0, 100, 20))
+axis(2)
 
 dev.off()
 
@@ -24,7 +26,7 @@ pdf("county_hispanic_pop_log_hist.pdf", 7.5, 4)
 par(mar = c(3.8, 3.5, 0.5, 0.5), las = 1, mgp = c(2.5, 0.7, 0), 
     cex.lab = 1.5, cex.axis = 1.5)
 histPlot(log(county_complete$hispanic_2010), breaks = 25, 
-         xlab = "log(% Hispanic)", ylab = "", 
+         xlab = "log(Percent Hispanic)", ylab = "", 
          col = COL[1])
 
 dev.off()

extraTeX/eoceSolutions/eoceSolutions.tex

@@ -218,8 +218,7 @@ \chapter{Exercise solutions}
 
 % 43
 
-\eocesol{(a)~County, state, driver's race, whether the car was searched or not,
-    and whether the driver was arrested or not.
+\eocesol{(a)~Categorical, non-ordinal: County, State, Driver's race. Numerical, discrete: No. of stops per year. Numerical, continuous: \% searched, \% drivers arrested.
 (b)~All categorical, non-ordinal.
 (c)~Response: whether the car was searched or not.
     Explanatory: race of the driver.}
@@ -952,7 +951,9 @@ \chapter{Exercise solutions}
 sometimes the truth is missed. A 95\% confidence interval ``misses'' about 5\% 
 of the time.
 (b)~True. Notice that the description focuses on the true population value.
-(c)~True. If we examine the 95\% confidence interval computed in Exercise~\ref{chronic_illness_tf}, we can see that 50\% is not included in this interval. This 
+(c)~True. If we examine the 95\% confidence interval computed in
+Exercise~\ref{chronic_illness_intro}, we can see that 50\% is not included in this interval.
+This 
 means that in a hypothesis test, we would reject the null hypothesis that the 
 proportion is~0.5.
 (d)~False. The standard error describes the uncertainty in the overall estimate