Small edits for clarity.

01_the_r_environment.qmd

@@ -8,7 +8,7 @@ our specific needs.
 
 ## Why becoming a useR?
 
-**R** is gratis and it runs on Windows, MacOS, and several Unix platforms. With **R** you can start with a data set like this:
+**R** is gratis and runs on Windows, MacOS, and several Unix platforms. With **R** you can start with a data set like this:
 ```{r loading messy flower data}
 #| echo: false
 flower_df <- read.table("data_files/flower.csv", header = TRUE, sep = ",")
@@ -34,22 +34,35 @@ You can also find many powerful tools to fit statistical models
 - Generalized linear models (including linear regression)
 - Survival analysis
 - Time series analysis
-- Random and Mixed effects models (aka hierarchical models, aka multilevel
+- Multilevel models (aka hierarchical models, aka Random and Mixed effects 
     models)
 - Classification and clustering
 - Sample size and power calculations
-- Multivariable analysis (e.g., factor analysis, principal component analysis, and structural equations modeling)
-
-Even better, new tools become available in **R** all the time. As with other open source programming languages, everyone can examine and contribute to **R**'s code. Users constantly publish their own code packages to expand **R**'s capabilities. As of March 2019, users have contributed over 13,700 packages to Comprehensive **R** Archive Network (CRAN), many of which perform complex statistical routines that are not (and may never be) available in other statistical software systems.
-
-In Windows, there are several ways to use **R**. The standard **R** graphical unit interface (GUI) allows you to point and click to do many basic tasks. Another GUI is [**R** Commander](https://socialsciences.mcmaster.ca/jfox/Misc/Rcmdr/), developed by 
-John Fox at McMaster University. **R** Commander displays the underlying **R** code for each analysis to help the user learn the programming language. [Tinn-**R**](http://sourceforge.net/projects/tinn-r/)  is another GUI from Jose Claudio Faria. 
-
-These GUIs are friendly and easy to grasp if you're a beginner. But to use all of **R**'s capabilities you will need to do more than point and click. 
-
-A more complete way of using **R** is through an integrated development environment (IDE), which, in short, helps you code. The most popular IDE for **R** is [**R**Studio](https://www.posit.com), which organizes the
-user's screen into panes that display scripts, objects, graphics, and
-the **R** console.
+- Multivariable analysis (e.g., factor analysis, principal component analysis, 
+    and structural equations modeling)
+
+Even better, new tools become available in **R** all the time. As with other open
+source programming languages, everyone can examine and contribute to **R**'s
+code. Users constantly publish their own code packages to expand **R**'s
+capabilities. As of March 2019, users have contributed over 13,700 packages to
+Comprehensive **R** Archive Network (CRAN), many of which perform complex
+statistical routines that are not (and may never be) available in other
+statistical software systems.
+
+In Windows, there are several ways to use **R**. The standard **R** graphical
+unit interface (GUI) allows you to point and click to do many basic tasks.
+Another GUI is [**R** Commander](https://socialsciences.mcmaster.ca/jfox/Misc/Rcmdr/), developed by 
+John Fox at McMaster University. **R** Commander displays the underlying **R**
+code for each analysis to help the user learn the programming language.
+[Tinn-**R**](http://sourceforge.net/projects/tinn-r/)  is another GUI from Jose
+Claudio Faria. 
+
+These GUIs are friendly and easy to grasp if you're a beginner. But to use all of
+**R**'s capabilities you will need to do more than point and click. A more
+complete way of using **R** is through an integrated development environment 
+IDE), which, in short, helps you code. The most popular IDE for **R** is
+[**R**Studio](https://www.posit.com), which organizes the user's screen into
+panes that display scripts, objects, graphics, and the **R** console.
 
 In these notes, we will use **R**Studio a lot. The goal is for you to start taking full advantage of **R**'s capabilities.
 
@@ -65,25 +78,21 @@ original analysis and to investigate other approaches.
 
 ## Why Isn't Everyone a Use**R**?
 
-Many users of statistics only learn how to use one statistical software, often the one taught in their first statistics course. In the past, **R** rarely was this first language, but nowadays more schools are teaching how to use it.
+Many users of statistics don't use **R** because they only know how to use one statistical software, often the one taught in their first statistics course. In the past, **R** rarely was this first language, but nowadays more schools are teaching how to use it.
 
-Some people have used **R**, but struggles to get comfortable 
-and productive with it, especially if they had little coding experience. Typing 
-commands explicitly is more difficult than pointing and clicking. Also, each 
-package has its own rules to learn. You can find a lot of good help for popular 
-packages written by professional developers, but not so much for smaller 
-packages written by other common users. Worst of all, some of the messages **R** 
-displays if you make a mistake are uninformative, so fixing the problem can be difficult. 
+Some people have used **R**, but struggle to get comfortable and productive with
+it, especially if they had little coding experience. Typing commands explicitly is more difficult than pointing and clicking. Also, each package has its own rules to learn. We can find a lot of good help for popular packages written by professional developers, but not so much for smaller packages written by other common users. Worst of all, some of the messages **R** displays if we make a mistake are uninformative, so fixing the problem can be difficult.
 
 Don't get frustrated! You don't have to be an expert programmer to use
 **R**. The benefits are worth spending some time up front.
 
 ## Suggestions for Learning **R**
 
-- Learn interactively! Retype and experiment with lots of sample code; you won't   break it. These notes contain many code examples and you can find many more   online.
-- Don't worry about getting errors. Even experienced **R** users
-  make mistakes all the time. And you can learn a lot from error
-  messages.
+- Learn interactively! Retype and experiment with lots of sample code; you won't
+    break it. These notes contain many code examples and you can find many more
+    online.
+- Don't worry about getting errors. Even experienced **R** users make mistakes
+    all the time. And you can learn a lot from error messages.
 - Ask other **R** users for help.
 - Some useful links are:
     -   <https://www.r-project.org>: The **R** Home page, the

docs/01_the_r_environment.html

@@ -186,7 +186,7 @@ <h1 class="title"><span class="chapter-number">1</span>&nbsp; <span class="chapt
 <p><strong>R</strong> is an environment for statistical modeling and graphics. That it is an <em>environment</em> instead of a <em>package</em> is one of the main reasons why <strong>R</strong> is distinct from other statistical programs. A package only gives us a fixed set of tools. An environment allows us to modify, combine and even create tools to suit our specific needs.</p>
 <section id="why-becoming-a-user" class="level2" data-number="1.1">
 <h2 data-number="1.1" class="anchored" data-anchor-id="why-becoming-a-user"><span class="header-section-number">1.1</span> Why becoming a useR?</h2>
-<p><strong>R</strong> is gratis and it runs on Windows, MacOS, and several Unix platforms. With <strong>R</strong> you can start with a data set like this:</p>
+<p><strong>R</strong> is gratis and runs on Windows, MacOS, and several Unix platforms. With <strong>R</strong> you can start with a data set like this:</p>
 <div class="cell">
 <div class="cell-output cell-output-stdout">
 <pre><code>  treat nitrogen block height weight leafarea shootarea flowers
@@ -212,15 +212,14 @@ <h2 data-number="1.1" class="anchored" data-anchor-id="why-becoming-a-user"><spa
 <li>Generalized linear models (including linear regression)</li>
 <li>Survival analysis</li>
 <li>Time series analysis</li>
-<li>Random and Mixed effects models (aka hierarchical models, aka multilevel models)</li>
+<li>Multilevel models (aka hierarchical models, aka Random and Mixed effects models)</li>
 <li>Classification and clustering</li>
 <li>Sample size and power calculations</li>
 <li>Multivariable analysis (e.g., factor analysis, principal component analysis, and structural equations modeling)</li>
 </ul>
 <p>Even better, new tools become available in <strong>R</strong> all the time. As with other open source programming languages, everyone can examine and contribute to <strong>R</strong>’s code. Users constantly publish their own code packages to expand <strong>R</strong>’s capabilities. As of March 2019, users have contributed over 13,700 packages to Comprehensive <strong>R</strong> Archive Network (CRAN), many of which perform complex statistical routines that are not (and may never be) available in other statistical software systems.</p>
 <p>In Windows, there are several ways to use <strong>R</strong>. The standard <strong>R</strong> graphical unit interface (GUI) allows you to point and click to do many basic tasks. Another GUI is <a href="https://socialsciences.mcmaster.ca/jfox/Misc/Rcmdr/"><strong>R</strong> Commander</a>, developed by John Fox at McMaster University. <strong>R</strong> Commander displays the underlying <strong>R</strong> code for each analysis to help the user learn the programming language. <a href="http://sourceforge.net/projects/tinn-r/">Tinn-<strong>R</strong></a> is another GUI from Jose Claudio Faria.</p>
-<p>These GUIs are friendly and easy to grasp if you’re a beginner. But to use all of <strong>R</strong>’s capabilities you will need to do more than point and click.</p>
-<p>A more complete way of using <strong>R</strong> is through an integrated development environment (IDE), which, in short, helps you code. The most popular IDE for <strong>R</strong> is <a href="https://www.posit.com"><strong>R</strong>Studio</a>, which organizes the user’s screen into panes that display scripts, objects, graphics, and the <strong>R</strong> console.</p>
+<p>These GUIs are friendly and easy to grasp if you’re a beginner. But to use all of <strong>R</strong>’s capabilities you will need to do more than point and click. A more complete way of using <strong>R</strong> is through an integrated development environment IDE), which, in short, helps you code. The most popular IDE for <strong>R</strong> is <a href="https://www.posit.com"><strong>R</strong>Studio</a>, which organizes the user’s screen into panes that display scripts, objects, graphics, and the <strong>R</strong> console.</p>
 <p>In these notes, we will use <strong>R</strong>Studio a lot. The goal is for you to start taking full advantage of <strong>R</strong>’s capabilities.</p>
 <!--
 
@@ -233,8 +232,8 @@ <h2 data-number="1.1" class="anchored" data-anchor-id="why-becoming-a-user"><spa
 </section>
 <section id="why-isnt-everyone-a-user" class="level2" data-number="1.2">
 <h2 data-number="1.2" class="anchored" data-anchor-id="why-isnt-everyone-a-user"><span class="header-section-number">1.2</span> Why Isn’t Everyone a Use<strong>R</strong>?</h2>
-<p>Many users of statistics only learn how to use one statistical software, often the one taught in their first statistics course. In the past, <strong>R</strong> rarely was this first language, but nowadays more schools are teaching how to use it.</p>
-<p>Some people have used <strong>R</strong>, but struggles to get comfortable and productive with it, especially if they had little coding experience. Typing commands explicitly is more difficult than pointing and clicking. Also, each package has its own rules to learn. You can find a lot of good help for popular packages written by professional developers, but not so much for smaller packages written by other common users. Worst of all, some of the messages <strong>R</strong> displays if you make a mistake are uninformative, so fixing the problem can be difficult.</p>
+<p>Many users of statistics don’t use <strong>R</strong> because they only know how to use one statistical software, often the one taught in their first statistics course. In the past, <strong>R</strong> rarely was this first language, but nowadays more schools are teaching how to use it.</p>
+<p>Some people have used <strong>R</strong>, but struggle to get comfortable and productive with it, especially if they had little coding experience. Typing commands explicitly is more difficult than pointing and clicking. Also, each package has its own rules to learn. You can find a lot of good help for popular packages written by professional developers, but not so much for smaller packages written by other common users. Worst of all, some of the messages <strong>R</strong> displays if you make a mistake are uninformative, so fixing the problem can be difficult.</p>
 <p>Don’t get frustrated! You don’t have to be an expert programmer to use <strong>R</strong>. The benefits are worth spending some time up front.</p>
 </section>
 <section id="suggestions-for-learning-r" class="level2" data-number="1.3">