Update Information for Stats Camp
Welcome Stats Camp Participant:
We are looking forward to having you next week for Week 1: R on the University of Kansas campus. There are some important information and computer needs in this notification.
Room Change for R Week – Please meet in Wescoe Hall Room 4066, the Fred Bangs Memorial Active Learning Classroom. The room is a specialized educational training facility available through EGARC (Ermal Granger Academic Resource Center). I'd like to extend a special word of thanks to Jonathan Perkins, the director of EGARC, for making this possible. Sessions will begin at 9:00 a.m. each morning.
Refreshments: Lunch and breaks will be on your own. However, we will provide coffee in the morning, but no snacks. Soda machines are located fairly close to your classroom.
There is no cafeteria located in Wescoe Hall. Lunch locations on campus include The Market and Panda Express in the KS Memorial Union. The DeBruce Center and KS Union have Roasteries (snacks, fruit, sandwiches, baked goods). The KS Union has the Hawk Shop, which offers convenience store type options. You are also welcome to leave campus at lunch. There will be an extended lunch hour to allow ample time.
Parking: If you will be parking on campus, you need a parking permit. Daily and Weekly temporary visitor permits are available for all lots. We have arranged for reduced prices of $6/day or $21/week. The Parking Office recommends visitors phone ahead (785-864-7275) to do paperwork/payment ahead of time. Tell them you are attending the CRMDA Statistical Institute to receive the reduced price. You can also get your permit at the KU Parking Department located at 1501 Irving Hill Road, Lawrence, KS 66045.
Often during the summer months there will be construction and closed streets on campus: please view the KU Summer Construction & Street Closures. Plan to allow adequate time to park and walk to your class. Buildings used during camp classes are Wescoe Hall and Watson Library. A campus map can be viewed at: Campus & Parking Map.
Suggested parking locations include:
R Week – either Lot 54 or Lot 15. During Weeks 2 & 3, Lot 15 or 61 would be closest.
Directions to Lot 15
- If you are coming from the South, travel on Kentucky St (one-way northbound traffic) and turn West/Left on 14th Street. Turn South / Left on Jayhawk Blvd and take first Left on Lilac Lane. Go straight back, past the circle drive, to the parking Lot 15.
- If coming from the North, travel on Tennessee (one-way southbound traffic) and turn West/ West/Right on 14th Street. Turn South / Left on Jayhawk Blvd and take first Left on Lilac Lane. Go straight back, past the circle drive, to the parking Lot 15.
Directions to Lot 54
- If coming either North or South on Iowa St (Hwy 59) turn East onto 15th St (which takes you onto campus). Travel up/down the hill until you reach Naismith Drive. Turn Right and then take first Right and Right into parking Lot 54. (The parking garage is on the opposite side of the street and is more expensive and not associate with the CRMDA parking permit).
Directions to Lot 61
- If coming either North or South on Iowa St (Hwy 59) turn East onto 15th St (which takes you onto campus). Travel up/down the hill until you reach Naismith Drive. Turn Right and continue down Naismith, until you reach the “Y”. Go straight onto Sunnyside Ave and turn Right on Illinois and left into Lot 61.
Your Computers: Please bring a computer on which you have administrative access (so software can be installed if necessary). Things will move along more smoothly if you have R installed before the workshop starts, but we can help with that if you have trouble. We expect that most Linux users will be able to install R via the package manager provided with the OS.
On Windows and Macintosh computers, the install may be a little more involved. The CRMDA has online help-sheets that describe the way we set up computers.
1. Windows https://crmda.ku.edu/windows-admin-tips
If you have set up Windows differently, I'm fairly sure we can adjust to make it work. To interact gracefully with other addon editors, it is often convenient to add the R installed bin folder to the system path.
We can discuss that.
2. Macintosh https://crmda.ku.edu/mac-admin-tips
If you are using a Macintosh, it is especially important to install XCode and XQuartz before installing R. Those prerequisite installs may take some time.
If your computer is broken, we have a few laptops that you can borrow. If you expect to do that, please notify firstname.lastname@example.org. Before the sessions begin, it will be necessary for you to come to our office, Watson 470, to sign an equipment checkout sheet.
The R program for Macintosh is delivered with a nice editor, R.app.
There are editors that can be installed that have some additional features. A popular editor, especially for R beginners, is called RStudio (http://www.rstudio.com). More experienced R users may prefer alternatives like Emacs (http://vgoulet.act.ulaval.ca/en/home) or Notepad++ (https://notepad-plus-plus.org/) with NPPTOR
(https://sourceforge.net/projects/npptor). The choice among these is a matter of taste and we will illustrate these as the week progresses. All of these offer the ability to write an R script file and run it "line-by-line" into an R session.
On each morning, we will upload the instructional materials for the session to our password-protected web page, which will be https://crmda.dept.ku.edu/StatsCamp2017. The material for the first day will become available on Friday, May 19. To download, you will need to enter the user name and password given to you. If you need the user name and password please call 785-864-3353 or email email@example.com.
Let us know if you have questions. As a reminder, cancellation with refund eligibility must be made by email to firstname.lastname@example.org by May 15 at 5:00 pm for Week 1 and May 22 for Week 2 & 3. If after this date, you have the option of sending a substitute in your place. Looking forward to seeing you at the 2017 Summer Statistical Institute.
Paul Johnson, Ph.D.
Director, KU Center for Research Methods & Data Analysis