Working through proofread to end of introduction.

source/index.Rmd

@@ -16,12 +16,10 @@ under the [Creative Commons Attribution / No Derivatives
 a physical copy of the book, you should be able to order it from Sage, when it
 is published.
 
-We wrote this book in
-[RMarkdown](https://rmarkdown.rstudio.com) with
-[Quarto](https://quarto.org). It is automatically rebuilt
-from
-[source](https://github.com/resampling-stats/resampling-with) by
-[Github ](http://github.com)
+We wrote this book in [RMarkdown](https://rmarkdown.rstudio.com) with
+[Quarto](https://quarto.org).  We configured [Github ](http://github.com) to
+rebuild the textbook HTML and PDF files from [the RMarkdown
+source](https://github.com/resampling-stats/resampling-with).
 
 <!---
 Links that we may use in several chapters.

source/intro.Rmd

@@ -50,7 +50,7 @@ whether to buy insurance.
 These are some examples of the kinds of problems that we can handle with the
 methods described in this book:
 
-1. *You are a doctor* trying to develop a treatment for COVID19. Currently you
+1. *You are a doctor* trying to develop a treatment for Covid. Currently you
    are working on a medicine labeled AntiAnyVir. You have data from patients to
    whom medicine AntiAnyVir was given. You want to judge on the basis of those
    results whether AntiAnyVir really improves survival or whether it is no
@@ -70,9 +70,8 @@ methods described in this book:
 2. *You are an environmental scientist* monitoring levels of phosphorus
    pollution in a lake.  The phosphorus levels have been fluctuated around a
    relatively low level until recently, but they have been higher in the last
-   few years. Does these recent higher levels indicate some important change or
-   can we put them down to some chance and ordinary variation from year to
-   year?
+   few years. Do these recent higher levels indicate some important change or
+   can we put them down to ordinary variation from year to year?
 
 The core of all these problems, and of the others that we will deal with in
 this book, is that you want to know the "chance" or "probability" — different
@@ -90,14 +89,14 @@ decisions, related to the questions about probability stated above, that
 ultimately we would like to make:
 
 1. *Should you (the researcher) advise doctors to prescribe medicine
-   AntiAnyVir* for COVID19 patients, or, should you (the researcher) continue
+   AntiAnyVir* for Covid patients, or, should you (the researcher) continue
    to study AntiAnyVir before releasing it for use? A related matter: should
    you and other research workers feel sufficiently encouraged by the results
    of medicine AntiAnyVir so that you should continue research in this general
    direction rather than turning to some other promising line of research?
    These are just two of the possible decisions that might be influenced by
    the answer to the question about the probability that medicine AntiAnyVir
-   is effective in treating COVID19.
+   is effective in treating Covid.
 
 2. *Should you advise the Republicrat presidential candidate to go to New
    Hampshire* to campaign? If the poll tells you conclusively that she or he
@@ -158,7 +157,8 @@ add up all the SRP values to give the *total*.  We could also divide the total
 by the number of measurements, to give the *average*.  Or we could measure the
 spread of the values by finding the *minimum* and the *maximum* — see table
 @tbl-srp-stats). All these numbers are *descriptive statistics*, because
-they are summaries that *describe* the collection of SRP measurements.
+they are numbers that summarize and therefore *describe* the collection of SRP
+measurements.
 
 
 ```{python, eval=TRUE, echo=FALSE}
@@ -240,7 +240,7 @@ time and that of other people to research in other directions, with some chance
 that the other research will produce a less-general but nevertheless useful
 treatment for some relatively infrequent viral infections. Those three
 possibilities have different social benefits. The probability that medicine
-AntiAnyVir really has some benefit in treating COVID19, as judged by your prior
+AntiAnyVir really has some benefit in treating Covid, as judged by your prior
 research, obviously will influence your decision on whether or not to do more
 research on medicine AntiAnyVir. But that judgment about the probability is
 only one part of the overall web of consequences and evaluations that must be
@@ -292,9 +292,9 @@ research thinking. Alfred Kinsey long ago put it this way:
 > ... no statistical treatment can put validity into generalizations which are
 > based on data that were not reasonably accurate and complete to begin with.
 > It is unfortunate that academic departments so often offer courses on the
-> statistical manipulation of human material to students who have little
-> understanding of the problems involved in securing the original data. ...
-> When training in these things replaces or at least precedes some of the
+> statistical manipulation of [data from human behavior] to students who have
+> little understanding of the problems involved in securing the original data.
+> ... When training in these things replaces or at least precedes some of the
 > college courses on the mathematical treatment of data, we shall come nearer
 > to having a science of human behavior. [@kinsey1948sexual, p 35].
 
@@ -345,10 +345,10 @@ Scan this book and you will find almost no formal mathematics. Yet
 nearly every student finds the subject very difficult —  as difficult as
 anything taught at universities. The root of the difficulty is that the
 *subject matter* is extremely difficult. Let's find out *why*.
-It is easy to find out with high precision which movie is playing
-tonight at the local cinema; you can look it up on the web or call the cinema
-and ask. But consider by contrast how difficult it is to determine with
-accuracy:
+
+It is easy to find out with high precision which movie is playing tonight at
+the local cinema; you can look it up on the web or call the cinema and ask. But
+consider by contrast how difficult it is to determine with accuracy:
 
 1. Whether we will save lives by recommending vitamin D supplements for the
    whole population as protection against viral infections.  Some evidence

source/preface_second.Rmd

@@ -104,7 +104,7 @@ this success.
 
 The method was first presented at some length in the 1969 edition of my book
 *Basic Research Methods in Social Science* [@simon1969basic] (third edition
-with Paul Burstein -@simon1985basic).
+with Paul Burstein [-@simon1985basic]).
 
 For some years, the resampling method failed to ignite interest among
 statisticians. While many factors (including the accumulated
@@ -184,7 +184,7 @@ separate publication where it might be overlooked.
 
 In ancient times, mathematics developed from the needs of governments
 and rich men to number armies, flocks, and especially to count the
-taxpayers and their possessions. Up until the beginning of the 20th
+taxpayers and their possessions. Up until the beginning of the 20^th^
 century, the term *statistic* meant the number of something — soldiers,
 births, taxes, or what-have-you. In many cases, the term *statistic* still
 means the number of something; the most important statistics for the United
@@ -194,12 +194,14 @@ the making or interpretation of descriptive statistics, because the topic is
 handled very well in most conventional statistics texts.
 
 Another stream of thought entered the field of probability and statistics in
-the 17th century by way of gambling in France. Throughout history people had
+the 17^th^ century by way of gambling in France. Throughout history people had
 learned about the odds in gambling games by repeated plays of the game. But in
-the year 1654, the French nobleman Chevalier de Mere asked the great
+the year 1654, the French nobleman Chevalier de Méré asked the great
 mathematician and philosopher Pascal to help him develop correct odds for some
-gambling games. Pascal, the famous Fermat, and others went on to develop
-modern probability theory.
+gambling games[^problem-points]. Pascal, the famous Fermat, and others went on
+to develop modern probability theory.
+
+[^problem-points]: <https://en.wikipedia.org/wiki/Problem_of_points>
 
 Later these two streams of thought came together. Researchers wanted to
 know how accurate their descriptive statistics were — not only the
@@ -208,9 +210,10 @@ numbers arising from experiments. Statisticians began to apply the
 theory of probability to the accuracy of the data arising from sample
 surveys and experiments, and that became the theory of *inferential
 statistics*.
+
 Here we find a guidepost: probability theory and statistics are relevant
-whenever there is uncertainty about events occurring in the world, or in
-the numbers describing those events.
+whenever there is uncertainty about events occurring in the world, or in the
+numbers describing those events.
 
 Later, probability theory was also applied to another context in which
 there is uncertainty — decision-making situations. Descriptive