If you aren’t familiar with matrix algebra (or with matrix algebra in R), you might want to practice with a couple of tutorials before the course starts on June 4th. Go to the Schedule and click on Exercise 1.2. The first part of this exercise is two matrix algebra tutorials. You could work through those tutorials before you arrive. That will make doing this exercise a little easier on the first day of the course. Have fun!
Our five day course at Friday Harbor will be fast-paced, so here are some points to keep in mind in getting ready for Monday, June 4th. As you can see from the Schedule, we generally have a lecture on a topic, followed by some discussion, then (but not always) a computer exercise on that topic and then finally some more discussion. Before the start of the week, you may want to look over the Schedule and do a little background reading for the lectures that interest you the most. The problem that you will now confront is that all the material for the lectures of interest may not be posted and will not be posted until the day of the lecture. No worries! Go to the Schedule for last year’s version of the course (click Previous years in the top ribbon) and find the most relevant lecture. There which will often be very similar to the one in this year’s schedule. On the 2017 Schedule you will find powerpoints/pdfs for lectures, videos of lectures and audio recordings, as well as suggested readings. You can use all of those to prepare for the lectures of special interest to you.
To prepare for the computer exercises, it is important to realize that the exercises are of two types. Some of exercises use special websites and software (e.g., see the exercise on estimating G-matrices or the one on G-matrix evolution). Using the instruction documents from 2017, you could try doing those exercises beforehand if you want. Other exercises are tutorials in R, in which you will follow along as the instructor guides you through the tutorial. You will not need much knowledge to follow along, but you will need to execute commands in R and look at and possibly save graphical output. Often the instructor will use R Studio and so it will be useful for you to have R Studio installed on your laptop so you can more easily follow along. R Studio is a user-friendly front end for R. Free downloads are available at https://www.rstudio.com/products/rstudio/download2/ After you have successfully downloaded R Studio you might practice with it by loading R script and running it. You can find instructional videos on YouTube that may help you get acquainted with R Studiio. -SJA
Here is a list of R packages that will be used during the course. Please download them and their dependencies to your computer before you arrive at Friday Harbor. We may add to this list during the course.
Some of the programs we will be using have been compiled for Windows. To get them to work on Unix machines (e.g., Macs and Linux distributions) you need to use wine, an open source application. Information about wine can be found here. It can take about 30-45 minutes for wine to install, depending on your internet connection, so be sure to have it installed and ready to go before the first day.
In Exercise 1.2 we provide tips for downloading wine for both Mac OS X and Ubuntu.
Write a comment below if you are having trouble downloading and installing wine on your machine.
I have attached some files below which may help if you are new to R. The first two files are from a past workshop run by Marguerite Butler; you should start with these. Other files show you how to install packages into R on your laptop (read them before the course) and provide general reference information. A general way to get help in R when you are stuck is to enter a query in Google. For example, if you can’t figure out how to do labels on plots, type something like ‘Adding labels in R’. You can also get help within R by typing a ? followed by a noun that is the name of an object in R. In general, if you are writing a program, the simplest way forward is to find a program that does something close to what you want. Modify that program in small steps, testing after each change, until you get to where you need to be.-SJA
R is a free statistical computing program that will be used throughout the course. If you haven’t done so already, please download R and install it on your computer from this site before June 5th. If you already use R you might want to install the most up-to-date version so that new package installations are easier. -SJA