Merge pull request #529 from moderndive/crc-copyedits

Crc copyedits

00-preface.Rmd

@@ -3,7 +3,7 @@
 \vspace{0.1in}
 
 <center>
-`r include_image("images/logos/Rlogo.png", html_opts = "height=100px", latex_opts = "height=10%")` \hfill &emsp; &emsp; &emsp; `r include_image("images/logos/RStudio-Logo-Blue-Gradient.png", html_opts = "height=100px", latex_opts = "height=10%")`
+`r include_image("images/logos/Rlogo.png", html_opts = "height=100px", latex_opts = "height=12%")` \hfill &emsp; &emsp; &emsp; `r include_image("images/logos/RStudio-Logo-Blue-Gradient.png", html_opts = "height=100px", latex_opts = "height=12%")`
 </center>
 
 **Help! I'm completely new to coding and I need to learn R and RStudio! What do I do?** 
@@ -18,7 +18,7 @@ If you're asking yourself this question, then you've come to the right place! St
 
 ```{r results="asis", echo=FALSE, purl=FALSE}
 if (is_html_output()) {
-  cat(glue::glue('This is version {version} of *ModernDive* published on {date}. For previous versions of *ModernDive*, see the "About this book" section below.'))
+  cat(glue::glue('This is version {version} of *ModernDive* published on {date}. For previous versions of *ModernDive*, see the "About this book" section.'))
 }
 ```
 
@@ -34,7 +34,7 @@ We present a map of your upcoming journey in Figure \@ref(fig:moderndive-figure)
 
 (ref:flowchart) *ModernDive* flowchart.
 
-```{r moderndive-figure, fig.align="center", fig.cap="(ref:flowchart)", echo=FALSE, purl=FALSE, out.width=if(!knitr::is_latex_output()) "100%"}
+```{r moderndive-figure, fig.align="center", fig.cap="(ref:flowchart)", echo=FALSE, purl=FALSE, out.width="100%"}
 include_graphics("images/flowcharts/flowchart/flowchart.002.png")
 ```
 
@@ -101,7 +101,7 @@ You'll commonly hear the phrase "statistically significant" thrown around in the
 
 These sub-fields are summarized in what Garrett Grolemund \index{Grolemund, Garrett} and Hadley Wickham \index{Wickham, Hadley} have previously termed the ["data/science pipeline"](http://r4ds.had.co.nz/explore-intro.html) in Figure \@ref(fig:pipeline-figure).
 
-```{r pipeline-figure, fig.align="center", fig.cap="Data/science pipeline.", echo=FALSE, purl=FALSE, out.height="100%", out.width="100%"}
+```{r pipeline-figure, fig.align="center", fig.cap="Data/science pipeline.", echo=FALSE, purl=FALSE, out.width="100%"}
 include_graphics("images/r4ds/data_science_pipeline.png")
 ```
 
@@ -188,7 +188,7 @@ Here are some principles and beliefs we kept in mind while writing this text. If
     + Computing skills are essential to working with data in the 21st century. Given this fact, we feel that to shield students from computing is to ultimately do them a disservice.
     + We are not teaching a course on coding/programming per se, but rather just enough of the computational and algorithmic thinking necessary for data analysis.
 1. **Complete reproducibility and customizability**
-    + We are frustrated when textbooks give examples, but not the source code and the data itself. We give you the source code for all examples as well as the whole book! While we have made choices to occasionally hide the code that produces more complicated figures, reviewing the book's GitHub repository will provide you with all the code (see below).
+    + We are frustrated when textbooks give examples, but not the source code and the data itself. We give you the source code for all examples as well as the whole book! While we have made choices to occasionally hide the code that produces more complicated figures, reviewing the book's GitHub repository will provide you with all the code (see in "About this book").
     + Ultimately the best textbook is one you've written yourself. You know best your audience, their background, and their priorities. You know best your own style and the types of examples and problems you like best. Customization is the ultimate end. We encourage you to take what we've provided and make it work for your own needs. For more about how to make this book your own, see "About this book" later in this Preface.
 
 
@@ -221,7 +221,7 @@ Lastly, a special shout out to any student who has ever taken a class with us at
 
 ## About this book {#about-the-book .unnumbered}
 
-This book was written using RStudio's [bookdown](https://bookdown.org/) package\index{R packages!bookdown} by \index{Xie, Yihui}Yihui Xie[@R-bookdown]. This package simplifies the publishing of books by having all content written in \index{R Markdown} [R Markdown](http://rmarkdown.rstudio.com/html_document_format.html). The bookdown/R Markdown source code for all versions of ModernDive is available on GitHub:
+This book was written using the [bookdown](https://bookdown.org/) package\index{R packages!bookdown} by \index{Xie, Yihui}Yihui Xie[@R-bookdown]. This package simplifies book publishing by having all content written in \index{R Markdown} [R Markdown](http://rmarkdown.rstudio.com/html_document_format.html). The R Markdown source code of ModernDive is available on GitHub:
 
 * **Latest online version** The most up-to-date release:
     + Version `r latest_release_version` released on `r latest_release_date` ([source code](https://github.com/moderndive/moderndive_book/releases/tag/v`r latest_release_version`))
@@ -230,7 +230,7 @@ This book was written using RStudio's [bookdown](https://bookdown.org/) package\
     - **Updated Datasets and Code:** Replaced datasets (`promotions`, `evals`, and `pennies`) with new ones (`un_member_states_2024`, `spotify_sample`, and `almonds_bowl`). Adopted the `nycflights23` package instead of `nycflights13` and introduced the base R pipe (`|>`) instead of the tidyverse pipe (`%>%`). Also incorporated `envoy_flights` and `early_january_2023_weather` in the `moderndive` package.
     - **Content Reorganization:** Restructured sections in Chapters 7 and 10 for improved readability. Moved "Model Selection" from Chapter 6 to Chapter 10 and split it into two new subsections as per suggestions.
     - **Enhanced Theoretical Discussions:** Improved theory-based discussions in Chapters 7, 8, 10, and 11, and added sections to better connect statistical inference based on reviewer feedback.
-    - **New Examples and Functions:** Introduced `coffee_quality` and `old_faithful_2024` datasets with examples in Chapter 10, added use of the `fit()` function from the `infer` package for simulation-based inference with multiple linear regression, and incorporated the `infer` package into Chapter 11.
+    - **New Examples and Functions:** Introduced `coffee_quality` and `old_faithful_2024` datasets with examples in Chapter 10, added use of the `fit()` function from the `infer` package for simulation-based inference with multiple linear regression, and added `infer` coverage into Chapter 11.
   - **Code Enhancements and Clarifications:** Standardized code to use `|>`, addressed warnings for `group_by()`, and added `relocate()` to Chapter 3.
   - **Revamped Learning Checks:**: Updated and designed new Learning checks throughout the book to better assess student understanding.
 * **Print first edition** The CRC Press [print edition](https://www.routledge.com/Statistical-Inference-via-Data-Science-A-ModernDive-into-R-and-the-Tidyverse/Ismay-Kim/p/book/9780367409821) of *ModernDive* corresponds to Version 1.1.0 (with some typos fixed). Available at <https://moderndive.com/>.
@@ -253,7 +253,7 @@ Finally, since this book is under a [Creative Commons Attribution - NonCommercia
 
 ## Versions of R packages used {-}
 
-If you'd like your output on your computer to match up exactly with the output presented throughout the book, you may want to use the exact versions of the packages that we used. You can find a full listing of these packages and their versions below. This likely won't be relevant for novices, but we included it for reproducibility.
+If you'd like your output on your computer to match up exactly with the output presented throughout the book, you may want to use the exact versions of the packages that we used. You can find a full listing of these packages and their versions here. This likely won't be relevant for novices, but we included it for reproducibility.
 
 ```{r message=FALSE, echo=FALSE, purl=FALSE}
 # Packages needed internally, but not in text.
@@ -285,7 +285,7 @@ readr::read_rds("rds/package_versions.rds") |>
 
 Chester Ismay           |  Albert Y. Kim | Arturo Valdivia
 :-------------------------:|:-------------------------:|:-------------------------:
-`r include_image(path = "images/ismay2024.jpg", html_opts = "height=220px", latex_opts = "width=33%")` | `r include_image(path = "images/kim.png", html_opts = "height=220px", latex_opts = "width=33%")` | `r include_image(path = "images/valdivia.png", html_opts = "height=220px", latex_opts = "width=33%")`
+`r include_image(path = "images/ismay2024.jpg", html_opts = "height=220px", latex_opts = "width=100%")` | `r include_image(path = "images/kim.png", html_opts = "height=220px", latex_opts = "width=100%")` | `r include_image(path = "images/valdivia.png", html_opts = "height=220px", latex_opts = "width=100%")`
 
 **Chester Ismay** is Vice President of Data and Automation at MATE Seminars and is a freelance data science consultant and instructor. He also teaches in the Center for Executive and Professional Education at Portland State University. He completed his PhD in statistics from Arizona State University in 2013. He has previously worked in a variety of roles including as an actuary at Scottsdale Insurance Company (now Nationwide E&S/Specialty) and at Ripon College, Reed College, and Pacific University. He has experience working in online education and was previously a Data Science Evangelist at DataRobot, where he led data science, machine learning, and data engineering in-person and virtual workshops for DataRobot University. In addition to his work for *ModernDive*, he also contributed as initial developer of the [`infer`](https://cran.r-project.org/package=infer) R package and is author and maintainer of the [`thesisdown`](https://github.com/ismayc/thesisdown) R package.