Curtis Grant Miller

Associate Instructor

Office: JWB 121
Dept. Phone: (801) 581-6851
Dept. Fax: (801) 581-4148

University of Utah
Department of Mathematics
155 S. 1400 E. JWB 233
Salt Lake City, UT
84112-0090 USA

MATH 3070

Lecture Syllabus

Lab Syllabus


Lecture Notes

These are half-filled notes for Chapters 1-9 of Probability and Statistics for Engineering and the Sciences (9th ed.) by Jay L. Devore. These are the notes I use for my lectures, written by me; you are welcome to follow along with these, or use your own.

R Lab Lecture Notes

Below are lecture notes from the times I have taught the lab, intended to accompany Chapters 1-9 of John Verzani's book Using R for Introductory Statistics (2nd ed.). They come in two versions. One version (which was the original version) was written for teaching the lab during an eight-week summer semester, and thus comes in eight lectures; when this version was written, I taught both the lab and the lecture sections of this class. The second version was written when I taught only the lab section in a regular semester, and thus consists of fourteen lectures. I split the original summer lectures for the fourteen-week schedule, then added more lectures to further slow myself down. I believe that a version of these notes (adapted by other lab instructors in response to more student feedback than I have received) are still being used by the lab instructors. In short, the second version for regular semesters has more content than the first version.

The notes are available both online and as PDFs below.

R Lab Summer Lecture Notes

R Lab Lecture Notes

Lecture Videos

These are .mp4 files and if you are in need of a viewer I recommend the VLC media player. Most of these videos are also on YouTube. Here is the playlist for main lectures, the playlist for video asides, and the playlist for R coding


Chapter 1

Chapter 2

Chapter 3

Chapter 4

Chapter 5

Chapter 6

Chapter 7

Chapter 8

R Programming



I wrote an app that generates random hypothesis testing problems, which I call StatTrainer. You can download StatTrainer.R, then make the script executable using the following command (on a UNIX/LINUX/*NIX system):

chmod +x StatTrainer.R

StatTrainer can then be started with the following:


This should work on the University of Utah Mathematics Departments computers. In general, you may need to install some packages, such as shiny, to make the app work.

This app was originally written to generate problems for MATH 1070, but MATH 3070 students may get some use out of it too.

Other Resources

Prof. Andrejs Treibergs has taught MATH 3070 multiple times and has many R scripts and old exams, useful both for learning R and for preparing for quizzes/tests. Here is the material.

Dr. Hadley Wickham is one of the leading authorities in the R community, having authored many of the best R packages and writing some of the best R books. (RStudio is also a Hadley Wickham project.) You can read many of Dr. Wickham's books online for free. Two books you may want to look at are R for Data Science (a more introductory book with an emphasis on tidyverse packages) and Advanced R (obviously a more advanced book).

I blog about R and statistics regularly on my website. You can follow the R and Statistics and Data Science feeds for that material. I've also described techniques and resources for learning more about programming in this blog post.

All of the notes made available on this page were written using R Markdown and bookdown. The source documents for these materials are available in this archive.

Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.