Statistical Methods I
Richard Single
306 Mansfield House
6568631
Richard.Single(at)uvm(dot)edu
Prerequisites: Minimum Junior standing or (STAT 141/143 AND instructor permission)
Text: "OpenIntro Statistics" (3rd Edition) by Diez, Barr, and CetinkayaRundel
 The textbook is available for free as a PDF, or a paper copy can be purchased for under $25 at Amazon.

If you are using the PDF, please download it from
this link.
since I have fixed some issues.
Errata: Most of the corrections involve the following change from "Standard Error" to "Standard Deviation of the Mean" in sections 4.1.3  4.4.
Using SD(Xbar) instead of SE(Xbar) allows us to use the Normal Distribution in Chapter 4. Chapter 5 will use the Standard Error.
Software: R Statistical Software
 R is a language and provides a flexible and extendable environment for statistical computing and graphics.
It is available as Free Software under the terms of the Free Software Foundation's GNU General Public License (GPL). It is similar in many ways to the S language which was developed at Bell Laboratories. There is a commercial version based on the S language known as SPLUS.
Getting Started with R
 Downloading and installing R (a two page summary)
 The main webpage for the project is http://www.rproject.org/index.html. You will find a link there to download it from the Comprehensive R Archive Network (CRAN).
R Studio
 R Studio download page. You will probably want to select the "Windows 7/8/10" or "Mac OS X 10.6+" platform.
 a short video to convince you that R Studio is a useful tool.
 R Studio overview.
Assignments / R Labs
 Due 1/19: Lab 0 Introduction to R (You can use Rstudio or R for the lab)
Turn in at most one page (you can use both sides if needed) with your answers to the "On Your Own" section. For the plot, you can rightclick & copy and then paste into Word.  Due 1/26: 1.23, 1.36, 1.46c (compute Median & IQR for both), 1.48 (*compute mean & SD and make a stem&leaf plot), 1.50, 1.66
*feel free to check your work in R, but be sure that you can compute these by hand [ stem(data) will give you a stem&leaf plot in R ]
Notes
 Overheads from chapter 1