Some minor tweaks and typo fixes

Author: ricky-lv426

_episodes/01_intro.md

@@ -10,12 +10,12 @@ adapted: false
 
 ## Welcome
 
-Welcome to **R: from Beginner to Intermediate**. Our aim is to provide you with a comprehensive overview of the R programming language assuming no prior knowledge of R or programming. While the commands may be specific to R, many of the concepts are also applicable to other programming languages. Over the course of these three sessions will gain many transferable skills and knowledge that will establish the foundations of a programmer.
+Welcome to **R: from Beginner to Intermediate**. Our aim is to provide you with a comprehensive overview of the R programming language assuming no prior knowledge of R or programming. While the commands may be specific to R, many of the concepts are also applicable to other programming languages. Over the course of these three sessions you will gain many transferable skills and knowledge that will establish the foundations of a programmer.
 
 ## Introduction to Coding For Reproducible Research
 
 This workshop is offered as part of the [Coding For Reproducible Research Intiative](https://uniexeterrse.github.io/workshop-homepage/). 
-Our ambition is to offer a recurring annual series of workshops open to all staff and students, with opportunities for novices through to more experienced users, to expand their skillsets and position them to confidently perform the informatics research projects in an efficient and reproducible way. A key objective is that the framework we put in place ensures that the workshops delivered are fit for purpose, of a consistent high standard, that delivery is sustainable in the longer term, minimises the workload burden on those who facilitate them and can adapt and expand as new training needs are identified.
+Our ambition is to offer a recurring annual series of workshops open to all staff and students, with opportunities for novices through to more experienced users, to expand their skillsets and position them to confidently perform their research projects in an efficient and reproducible way. A key objective is that the framework we put in place ensures that the workshops delivered are fit for purpose, of a consistent high standard, that delivery is sustainable in the longer term, minimises the workload burden on those who facilitate them and can adapt and expand as new training needs are identified.
 
 Championed by and in partnership with
 
@@ -31,11 +31,11 @@ This workshop, and the others in the series, were put together by a series of wo
 
 ## Workshop format
 
-Today's workshop is led by XX and supported by XX. We are all here because we are passionate about sharing our knowledge and supporting the development of our colleagues. For most of us, this is not a requirement of our current position and we are doing this at the margins of our time.
+We are all here because we are passionate about sharing our knowledge and supporting the development of our colleagues. For most of us, this is not a requirement of our current position and we are doing this at the margins of our time.
 
 As this is a beginner's workshop, we will be doing live demonstrations where we encourage you to type along with us - this is called live coding. We will pause for a break every 60-90 minutes, but there will also be periods in-between demonstrations where you are free to take additional comfort breaks if required.  This is a hybrid workshop, please be aware of this, online participants we find that engagement is higher if you are willing to turn your cameras on. There will be a dedicated helper for online participants please, either raise your hand or type any questions into the chat. In person participants you are also able to use the Teams link to join the chat. 
 
-Our aim is to be responsive to the needs of the group, both in person and virtual. Therefore, think of the schedule as a guide rather than a strict timetable. We welcome questions and queries as we go along, there are helpers in the room so raise your hand if you need assistance. There is also a dedicated helper for the virtual participants so please raise your virtual hand to attract their attention. In person participants you are welcome to post questions in the Teams chat,if you find this easier than putting your hand up. This will be saved and distributed at the end of the workshop.  
+Our aim is to be responsive to the needs of the group, both in person and virtual. Therefore, think of the schedule as a guide rather than a strict timetable. We welcome questions and queries as we go along, there are helpers in the room so raise your hand if you need assistance. There is also a dedicated helper for the virtual participants so please raise your virtual hand to attract their attention. In person participants you are welcome to post questions in the Teams chat, if you find this easier than putting your hand up. This will be saved and distributed at the end of the workshop.  
 
 We would like to highlight that we have a [code of conduct](https://uniexeterrse.github.io/intro-to-r/code.html) and by attending this workshop you are agreeing to abide by it. 
 

_episodes/02_gettingstarted.md

@@ -48,7 +48,7 @@ We should also note that, the two most important reasons for choosing a language
 
 [RStudio](https://www.rstudio.com/), is an Integrated Development Environment (IDE) that provides an interface designed to improve the experience of programming with R, and to facilitate more efficient and reproducible code development. It is designed so you can have multiple elements visible at the same time within a single programme. For example plots, tables and code, rather than juggle different programmes or windows. 
 
-We will use RStudio IDE to write code, navigate the files found on our computer, inspect the variables we are going to create, and visualize the plots we will generate. RStudio can also be used for other things (e.g., version control, developing packages, writing Shiny apps, creating documents and slides) that we will not cover during the workshop. It can be a very powerful tool for managing how you develop code, software or programmes. 
+We will use the RStudio IDE to write code, navigate the files found on our computer, inspect the variables we are going to create, and visualize the plots we will generate. RStudio can also be used for other things (e.g., version control, developing packages, writing Shiny apps, creating documents and slides) that we will not cover during the workshop. It can be a very powerful tool for managing how you develop code, software or programmes. 
 
 
 # Navigating RStudio

_episodes/03_basic_commands.md

@@ -51,7 +51,7 @@ There are two main ways of interacting with R: using the console or by using
 a script. A script is a text file that contains your code. R scripts are often saved with the file extension .r or .R.
 
 We want our code and workflow to be reproducible. In other words, we want to write code in a way that
-anyone (including ou future selves) can easily replicate, such they will obtain the same results from our code
+anyone (including our future selves) can easily replicate, such they will obtain the same results from our code
 on their computer. If we type our commands directly into the Console, they will be forgotten when you close the session. 
 It is preferable to type the commands you want to run directly into the script editor, so that you can save the script. This way, 
 you have a complete record of what you did, 

_episodes/04_data_types.md

@@ -16,7 +16,7 @@ attrib_license_link: https://creativecommons.org/licenses/by/4.0/
 
 
 
-# Inbuilt Datasets
+# Inbuilt datasets
 
 R has a number of datasets included for you to practice with. 
 We can get a list of these by running the command ```data()```
@@ -28,8 +28,6 @@ data()
 
 This command won't produce any output but open a file in the scripts pane that lists the available datasets.
 
-(Alt text!)["../images/r_data.png"]
-
 In this session, we will be using the built-in R data sets stored in the variables ```iris``` & ```mtcars```. 
 By having our data stored in a variable means we can easily use it with R functions and start to
 manipulate or process it. Note that we are using the word data very loosely, it can refer to any form of 
@@ -85,7 +83,7 @@ To explore data frames, there are a number of relevant functions:
 
 
 
-# Subsetting Data
+# Subsetting data
 
 There are many occasions we want to "look" at some part of the data. Extract a subset is known as slicing.
 If we want to get a single value from the data frame, we can index a specific position using square brackets.
@@ -223,7 +221,7 @@ iris[, 2]
 
 
 
-# Data Types 
+# Data types 
 
 One key feature of a data frame is each column is classed as a specific data type. 
 
@@ -311,7 +309,7 @@ length(y)
 {% endhighlight %}
 
 
-# Converting Between Datatypes
+# Converting between data types
 
 It can be critical that R has correctly assigned the right data type to your variable. If it has not you may run into 
 errors when processing it. You therefore may want to convert between different data types. This can be done with the 
@@ -331,15 +329,15 @@ typeof(y)
 ## [1] "character"
 {% endhighlight %}
 
-## Activity: Determining Data Yypes
+## Activity: Determining data types
 
 Create a variable with the numbers 9,2,200, and 14.
 What class do you predict this variable to be? Use an R function to confirm your answer.
 If it is not the data type you expected, can you force R to convert it to an integer?
 Divide each element of the variable in half. Does this change the type of variable?
 
 
-# Data Structures
+# Data structures
 
 R has a number of inbuilt structures that can be used to store datasets. We have encountered one of these already 
 the data.frame. Other include: 

_episodes/05_load_data.md

@@ -29,15 +29,13 @@ Assuming you have downloaded the file into your current working directory, you c
 read.csv(file = "worms.csv", header = TRUE)
 {% endhighlight %}
 
-
+Some errors you might come across:
 
 {% highlight text %}
 ## Warning in file(file, "rt"): cannot open file 'worms.csv': No such file or
 ## directory
 {% endhighlight %}
 
-
-
 {% highlight text %}
 ## Error in file(file, "rt"): cannot open the connection
 {% endhighlight %}

_episodes/06_manipulating_data.md

@@ -17,7 +17,7 @@ Often we need to manipulate or extract parts of our dataset prior to doing any a
 
 
 
-# Conditional Subsetting
+# Conditional subsetting
 
 We have already looked at slicing subsets, where we knew the indexs of the rows or columns of the entries we wanted. 
 There may be times when, instead we want to select rows based on a specific condition. This would require a conditional