Merge branch 'main' into 824-bullet-formatting

00-before-we-start.Rmd

@@ -33,20 +33,18 @@ source("setup.R")
 The term "`R`" is used to refer to both the programming language and the
 software that interprets the scripts written using it.
 
-[RStudio](https://rstudio.com) is currently a very popular way to not only write
-your R scripts but also to interact with the R software. To function correctly,
-RStudio needs R and therefore both need to be installed on your computer.
+[RStudio](https://rstudio.com) is a popular way to write R scripts and interact with the R software.
+To function correctly, RStudio needs R and therefore both need to be installed on your computer.
 
 ## Why learn R?
 
 ### R does not involve lots of pointing and clicking, and that's a good thing
 
-The learning curve might be steeper than with other software, but with R, the
-results of your analysis do not rely on remembering a succession of pointing and
-clicking, but instead on a series of written commands, and that's a good thing!
+In R, the results of your analysis rely on a series of written commands, and not 
+on remembering a succession of pointing and clicking. That is a good thing!
 So, if you want to redo your analysis because you collected more data, you don't
 have to remember which button you clicked in which order to obtain your results.
-With a stored series of commands (this is your script), you can repeat running them and
+With a stored series of commands in an R script, you can repeat running them and
 R will process the new dataset exactly the same way as before.
 
 Working with scripts makes the steps you used in your analysis clear, and the
@@ -58,15 +56,16 @@ doing, and facilitates your learning and comprehension of the methods you use.
 
 ### R code is great for reproducibility
 
-Reproducibility is when someone else (including your future self) can obtain the
+Reproducibility is when someone else, including your future self, can obtain the
 same results from the same dataset when using the same analysis.
 
 R integrates with other tools to generate manuscripts from your code. If you
 collect more data, or fix a mistake in your dataset, the figures and the
 statistical tests in your manuscript are updated automatically.
 
-An increasing number of journals and funding agencies expect analyses to be
-reproducible, so knowing R will give you an edge with these requirements.
+R is widely used in academia and in industries such as pharma and biotech.
+These organisations expect analyses to be reproducible, so knowing R will give you an 
+edge with these requirements.
 
 ### R is interdisciplinary and extensible
 
@@ -90,14 +89,18 @@ computer or on the web.
 
 ### R produces high-quality graphics
 
-The plotting functionalities in R are endless, and allow you to adjust any
-aspect of your graph to convey most effectively the message from your data.
+The plotting functionalities in R are endless, and allow you to adjust any 
+aspect of your graph to visualize your data more effectively.
+
 
 ### R has a large and welcoming community
 
 Thousands of people use R daily. Many of them are willing to help you through
 mailing lists and websites such as [Stack Overflow](https://stackoverflow.com/),
-or on the [RStudio community](https://community.rstudio.com/).
+[RStudio community](https://community.rstudio.com/), and Slack channels such as  
+the R for Data Science online community (https://www.rfordatasci.com/). In addition, 
+there are numerous online and in person meetups organised globally through organisations
+such as R Ladies Global (https://rladies.org/). 
 
 ### Not only is R free, but it is also open-source and cross-platform
 

03-dplyr.Rmd

@@ -408,7 +408,7 @@ The `count()` function is shorthand for something we've already seen: grouping b
 ```{r, purl = FALSE}
 surveys %>%
     group_by(sex) %>%
-    summarise(count = n())
+    summarize(count = n())
 ```
 
 For convenience, `count()` provides the `sort` argument:  
@@ -543,7 +543,7 @@ the value provided.
 
 Let's use `pivot_wider()` to transform surveys to find the mean weight of each
 genus in each plot over the entire survey period. We use `filter()`,
-`group_by()` and `summarise()` to filter our observations and variables of
+`group_by()` and `summarize()` to filter our observations and variables of
 interest, and create a new variable for the `mean_weight`.
 
 ```{r, purl=FALSE}

04-visualization-ggplot2.Rmd

@@ -267,11 +267,14 @@ ggplot(data = surveys_complete, mapping = aes(x = species_id, y = weight)) +
 ```
 
 By adding points to the boxplot, we can have a better idea of the number of
-measurements and of their distribution:
+measurements and of their distribution. Because the boxplot will show the outliers
+ by default these points will be plotted twice -- by `geom_boxplot` and 
+ `geom_jitter`. To avoid this we must specify that no outliers should be added 
+ to the boxplot by specifying `outlier.shape = NA`.
 
 ```{r boxplot-with-points, purl=FALSE}
 ggplot(data = surveys_complete, mapping = aes(x = species_id, y = weight)) +
-    geom_boxplot(alpha = 0) +
+    geom_boxplot(outlier.shape = NA) +
     geom_jitter(alpha = 0.3, color = "tomato")
 ```
 
@@ -596,7 +599,7 @@ ggplot(surveys_complete, aes(x = species_id, y = hindfoot_length)) +
 > * See if you can change the thickness of the lines.
 > * Can you find a way to change the name of the legend? What about its labels?
 > * Try using a different color palette (see
->   <https://www.cookbook-r.com/Graphs/Colors_(ggplot2)/>).
+>   <https://r-graphics.org/chapter-colors>).
 
 ## Arranging plots
 
@@ -677,7 +680,7 @@ saved plot.
 ##  minutes to either improve one of the plots generated in this
 ##  exercise or create a beautiful graph of your own. Use the RStudio
 ##  ggplot2 cheat sheet for inspiration:
-##  https://www.rstudio.com/wp-content/uploads/2015/08/ggplot2-cheatsheet.pdf
+##  https://posit.co/wp-content/uploads/2022/10/data-visualization-1.pdf
 ```
 
 ```{r, child="_page_built_on.Rmd"}

before_body.html

@@ -3,7 +3,7 @@
   <a href='https://carpentries.github.io/workbench'>The Carpentries Workbench</a>:
   <a href="https://preview.carpentries.org/R-ecology-lesson">https://preview.carpentries.org/R-ecology-lesson</a>.
   <br>
-  <b>The Workbench version of this lesson will become default on 2023-01-23</b>.
+  <b>The Workbench version of this lesson will become default on 2023-05-01</b>.
   <button type="button" style="border: true; position: absolute; top: 0px; right: 50px; color: #383838;" class="close" data-dismiss="alert" aria-label="Close">
     <span aria-hidden="true" style='font-size:34pt'>&times;</span>
   </button>