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diff --git a/bib/packages.bib b/bib/packages.bib
@@ -115,9 +115,9 @@ @Manual{R-rmarkdown
 @Manual{R-skimr,
   title = {skimr: Compact and Flexible Summaries of Data},
   author = {Michael Quinn and Amelia McNamara and Eduardo {Arino de la Rubia} and Hao Zhu and Shannon Ellis},
-  year = {2019},
   note = {R package version 1.0.6},
-  url = {https://CRAN.R-project.org/package=skimr},
+  url = {https://github.com/ropenscilabs/skimr},
+  year = {2019},
 }
 @Manual{R-tibble,
   title = {tibble: Simple Data Frames},

diff --git a/docs/1-getting-started.html b/docs/1-getting-started.html
@@ -147,7 +147,7 @@
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+<li class="chapter" data-level="" data-path="index.html"><a href="index.html"><i class="fa fa-check"></i>Welcome to ModernDive</a></li>
 <li class="chapter" data-level="" data-path="foreword.html"><a href="foreword.html"><i class="fa fa-check"></i>Foreword</a></li>
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@@ -1008,7 +1008,7 @@ <h3><span class="header-section-number">1.5.2</span> What’s to come?</h3>
 <h3>References</h3>
 <div id="refs" class="references">
 <div id="ref-R-infer">
-<p>Bray, Andrew, Chester Ismay, Evgeni Chasnovski, Ben Baumer, and Mine Cetinkaya-Rundel. 2019. <em>Infer: Tidy Statistical Inference</em>.</p>
+<p>Bray, Andrew, Chester Ismay, Evgeni Chasnovski, Ben Baumer, and Mine Cetinkaya-Rundel. 2019. <em>Infer: Tidy Statistical Inference</em>. <a href="https://CRAN.R-project.org/package=infer">https://CRAN.R-project.org/package=infer</a>.</p>
 </div>
 <div id="ref-rds2016">
 <p>Grolemund, Garrett, and Hadley Wickham. 2017. <em>R for Data Science</em>. First. Sebastopol, CA: O’Reilly Media. <a href="https://r4ds.had.co.nz/">https://r4ds.had.co.nz/</a>.</p>

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diff --git a/docs/index.html b/docs/index.html
@@ -147,7 +147,7 @@
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-<li class="chapter" data-level="" data-path="index.html"><a href="index.html"><i class="fa fa-check"></i>Special Announcement</a></li>
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@@ -587,17 +587,13 @@ <h2 class="subtitle"><em>A ModernDive into R and the tidyverse</em></h2>
 <p class="author"><em>Chester Ismay and Albert Y. Kim <br> Foreword by Kelly S. McConville</em></p>
 <p class="date"><em>November 25, 2019</em></p>
 </div>
-<div id="special-announcement" class="section level1 unnumbered">
-<h1>Special Announcement</h1>
+<div id="welcome-to-moderndive" class="section level1 unnumbered">
+<h1>Welcome to ModernDive</h1>
+<p><img src="images/logos/book_cover.png" width="350" />
+</br>
 <!-- include=FALSE for PDF sending to CRC -->
-<div class="announcement">
-<p>
-<strong>We’re excited to announce that we’ve signed a book deal with CRC Press! We will be publishing our first fully complete online version of ModernDive in November 2019, with a corresponding print edition to follow in December 2019. Don’t worry though, our content will remain freely available on <a href="https://moderndive.com/">ModernDive.com</a>.</strong>
-</p>
-</div>
-<center>
-<img src="images/logos/crc_press.jpg" height="150" />
-</center>
+This is the <a href="https://moderndive.com/">website</a> for <em>Statistical Inference via Data Science: A ModernDive into R and the tidyverse</em>! Visit the <a href="https://github.com/moderndive/ModernDive_book">GitHub repository for this site</a>, find the book at <a href="https://www.crcpress.com/Statistical-Inference-via-Data-Science-A-ModernDive-into-R-and-the-Tidyverse/Ismay-Kim/p/book/9780367409821">CRC Press</a>, or <a href="https://www.amazon.com/Statistical-Inference-via-Data-Science/dp/0367409828/">buy it on Amazon</a>.</p>
+<p><a rel="license" href="http://creativecommons.org/licenses/by-nc-sa/4.0/"><img alt="Creative Commons License" style="border-width:0" src="https://i.creativecommons.org/l/by-nc-sa/4.0/88x31.png" /></a><br />This work by <a href="https://chester.rbind.io/">Chester Ismay</a> and <a href="https://rudeboybert.rbind.io/">Albert Y. Kim</a> is licensed under a <a rel="license" href="http://creativecommons.org/licenses/by-nc-sa/4.0/">Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License</a>.</p>
 <!--
 <div class="announcement">
 <p><strong>This is a previous version (v<code>r version</code>) of <em>ModernDive</em> and may be out of date. For the current version of <em>ModernDive</em>, please go to <a href="https://moderndive.com/">ModernDive.com</a>.</strong></p>

diff --git a/docs/previous_versions/v0.6.0/index.html b/docs/previous_versions/v0.6.0/index.html
@@ -17,7 +17,6 @@
 
   <meta name="twitter:card" content="summary" />
   <meta name="twitter:title" content="Statistical Inference via Data Science" />
-
   <meta name="twitter:description" content="An open-source and fully-reproducible electronic textbook for teaching statistical inference using tidyverse data science tools." />
   <meta name="twitter:image" content="https://moderndive.com/images/logos/book_cover.png" />
 
@@ -588,7 +587,7 @@ <h1>
 <hr />
 <div class="announcement">
 <p>
-<strong>This is a previous version (v<code>r version</code>) of ModernDive and may be out of date. For the current version of ModernDive, please go to <a href="https://moderndive.com/">ModernDive.com</a>.</strong>
+<strong>This is a previous version (v0.6.0) of ModernDive and may be out of date. For the current version of ModernDive, please go to <a href="https://moderndive.com/">ModernDive.com</a>.</strong>
 </p>
 </div>
 <hr />
@@ -714,7 +713,7 @@ <h3><span class="header-section-number">1.1.3</span> Reproducible research</h3>
 <p></p>
 <p>Reproducibility means a lot of things in terms of different scientific fields. Are experiments conducted in a way that another researcher could follow the steps and get similar results? In this book, we will focus on what is known as <strong>computational reproducibility</strong>.  This refers to being able to pass all of one’s data analysis, data-sets, and conclusions to someone else and have them get exactly the same results on their machine. This allows for time to be spent interpreting results and considering assumptions instead of the more error prone way of starting from scratch or following a list of steps that may be different from machine to machine.</p>
 <!--
-Additionally, this book will focus on computational thinking, data thinking, and inferential thinking. We'll see throughout the book how these three modes of thinking can build effective ways to work with, to describe, and to convey statistical knowledge.  
+Additionally, this book will focus on computational thinking, data thinking, and inferential thinking. We'll see throughout the book how these three modes of thinking can build effective ways to work with, to describe, and to convey statistical knowledge.
 -->
 </div>
 <div id="final-note-for-students" class="section level3">
@@ -856,7 +855,7 @@ <h2><span class="header-section-number">1.5</span> About the authors</h2>
 </tbody>
 </table>
 <!--
-### Colophon 
+### Colophon
 
 * ModernDive is written using the CC0 1.0 Universal License; more information on this license is available [here](https://creativecommons.org/publicdomain/zero/1.0/).
 * ModernDive uses the following versions of R packages (and their dependent packages):