How to get ready for the course!

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 10th.  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 2018 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 2018 and ones already posted for 2019, 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  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

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