More block 1

Author: dzchilds

1_01_R_and_RStudio.Rmd

@@ -8,9 +8,9 @@ R is a dialect of the S language, which was developed by John Chambers and colle
 
 We could go on and on about the various features that R possesses. R is a functional programming language, it supports object orientation, etc etc... but these kinds of explanations are only helpful to someone who already knows about computer languages. It is useful to understand why so many people have turned to R to meet their data analysis needs. When a typical R user talks about "R" they are often referring to two things at once, the GNU R language and the ecosystem that exists around the language:
 
-* R is all about data analysis. We can carry out any standard statistical analysis in R, as well as access a huge array of more sophisticated tools with impressive names like "structural equation model", "random forests" and "penalized regression". These days, when statisticians and computer scientists develop a new analysis tool, they often implement it in R first. This means a competant R user can always access the latest, cutting edge analysis tools. R also has the best graphics and plotting facilities of any platform. With sufficient expertise, we can make pretty much any type of figure we need (e.g. scatter plots, phylogenetic trees, spatial maps, or even [volcanoes](http://www.r-project.org/screenshots/volcano-image.jpg)). In short, R is a very productive environment for doing data analysis.
+* R is all about data analysis. We can carry out any standard statistical analysis in R, as well as access a huge array of more sophisticated tools with impressive names like "structural equation model", "random forests" and "penalized regression". These days, when statisticians and computer scientists develop a new analysis tool, they often implement it in R first. This means a competent R user can always access the latest, cutting edge analysis tools. R also has the best graphics and plotting facilities of any platform. With sufficient expertise, we can make pretty much any type of figure we need (e.g. scatter plots, phylogenetic trees, spatial maps, or even [volcanoes](http://www.r-project.org/screenshots/volcano-image.jpg)). In short, R is a very productive environment for doing data analysis.
 
-* Because R is such a good environment for data analysis, a very large community of users has grown up around it. The size of this community has increased steadily since R was created, but this growth has really ramped up in the last 5-10 years or so. In the early 2000s there were very few books about R and the main way to access help online was through the widely-feared R mailing lists. Now, there are probably hundreds of books about different aspects of R, online tutorials written by enthusiasts, and many websites that exist solely to help people learn R. The resulting ecosystem is vast, and though it can be difficult to navigate at times, when we run into an R-related problem the chances are that the answer is already written down somewhere^[The other big change is that R is finally starting to become part of the commercial landscape---learning how to use it can only improve your job prospects.].
+* Because R is such a good environment for data analysis, a very large community of users has grown up around it. The size of this community has increased steadily since R was created, but this growth has really increased up in the last 5-10 years or so. In the early 2000s there were very few books about R and the main way to access help online was through the widely-feared R mailing lists. Now, there are probably hundreds of books about different aspects of R, online tutorials written by enthusiasts, and many websites that exist solely to help people learn R. The resulting ecosystem is vast, and though it can be difficult to navigate at times, when we run into an R-related problem the chances are that the answer is already written down somewhere^[The other big change is that R is finally starting to become part of the commercial landscape---learning how to use it can only improve your job prospects.].
 
 R is not just about data analysis---though we will mostly use it this way. It is a fully-fledged programming language, meaning that once you become moderately proficient with it you can do things such as construct numerical simulation models, solve equations, query websites, send emails, [access the foaas web service](http://cran.r-project.org/web/packages/rfoaas/), and carry out many other tasks we don't have time to write down. We won't do any of this year or next but it is worth noting that R can do much more than just analyse data if we need it to.
 
@@ -54,7 +54,7 @@ We're only going to scratch the surface of what RStudio can do and there are cer
 
 ### Getting and installing RStudio
 
-RStudio is developed and maintained by a for-profit company called... RStudio. They make their money by selling software tools and services related to R and RStudio. The basic desktop version of RStudio is free to download and use though. It can be downloaded from the Rstudio [download page](http://www.rstudio.com/products/RStudio/#Desk). The one to go for is the Open Source Edition of RStudio Desktop, __not__ the commercial version of RStudio Desktop. RStudio installs like any other piece of software, so there's nothing to configure after installation.
+RStudio is developed and maintained by a for-profit company called... RStudio. They make their money by selling software tools and services related to R and RStudio. The basic desktop version of RStudio is free to download and use though. It can be downloaded from the RStudio [download page](http://www.rstudio.com/products/RStudio/#Desk). The one to go for is the Open Source Edition of RStudio Desktop, __not__ the commercial version of RStudio Desktop. RStudio installs like any other piece of software, so there's nothing to configure after installation.
 
 ```{block, type="action"}
 If you haven't already done it, go ahead and install RStudio Desktop on your own computer. You are going to need it.
@@ -92,7 +92,7 @@ Let's briefly see what all this means by doing something very simple with R. Typ
 ```
 The first line above just reminds us what we typed into the Console. The line after that beginning with `## ` shows us what R printed to the Console after reading and evaluating our instructions. 
 
-What just happened? We can ignore the `[1]` bit for now (the meaning of this will become clear later in the course). What are we left with -- the number 2. The instruction we gave R was in effect "evaluate the expression `1 + 3`". R read this in, decided it was a valid R expression, evaluated the expression, and then printed the result to the Console for us. Unsurisingly, the expression `1 + 3` is a request to add the numbers 1 and 3, and so R prints the number 4 to the Console.
+What just happened? We can ignore the `[1]` bit for now (the meaning of this will become clear later in the course). What are we left with -- the number 2. The instruction we gave R was in effect "evaluate the expression `1 + 3`". R read this in, decided it was a valid R expression, evaluated the expression, and then printed the result to the Console for us. Unsurprisingly, the expression `1 + 3` is a request to add the numbers 1 and 3, and so R prints the number 4 to the Console.
 
 OK, that was not very exciting. In the next chapter we will start learning to use R to carry out more useful calculations. The important take-away from this is that this sequence of events---reading instructions, evaluating those instructions and printing their output---happens every time we type or paste something into the Console and hit Enter. The printing bit is optional by the way. Whether or not it happens depends on whether you decide to capture the output or not. Just remember, if R does not print anything to the Console it does not necessarily mean nothing has happened.