Math 321-03 (spring 2019)
Statistics for Experimentalists, spring 2019, math 321-03
You will want to check back here regularly as I may post a variety of course materials or links to various resources.
Here is the Course Syllabus.
Review Materials:
Here are the quiz 1 review problems with the set of poker-chip-like tokens we didn't get to in class. The questions are on the first page, and the solutions start on the second page. Here is a token drawing R simulation file to simulate making many draws of 3 tokens from such a set.
Here are some quiz 2 and exam 1 review problems, mostly covering conditional probability, independence, and Baye's theorem.
Exam 2 review (*updated 10:27pm Sunay 4/6/2019, one typo on the last problem fixed, it should be 478.95.)
Solutions
Formulas that will be given to you for exam 2.
Here is the final exam formula sheet. Please let me know if you see any typos or have any questions.
Here is Quiz 5 and 6 combined.
Q5/6 solutions
Here is a fun low-resolution game to test your ability to guess the correlation!
Some additional review for exam 3.
Exam 3 solutions. There were two versions, but they were mostly similar.
Hers is some additional final exam review.
Course Notes:
Here is a first draft of some course notes. I will update and edit these as we go.
Ch. 1 - Introduction and basic statistics (*updated 4:30pm 4/17/2019)
Water well depth data from chapter 1.
Chapter 2 notes (*updated 3:20pm 2/5/2019)
This is a fairly large html file (just over 1 MB), and it may take a while to load as it needs to process some graphics and mathematics typesetting on the fly.
Ch. 3 - Random variables and distributions (*updated 4:30pm 4/17/2019)
Ch. 4 - Central limit theorem (*updated 4:30pm 4/17/2019)
This is a short chapter.
Here are some additional notes on the CLT with embedded R code for you to explore via simulation. This also includes an introduction to Student's t-distribution, which we will discuss soon.
Ch. 5 - Confidence intervals (*updated 4:30pm 4/17/2019)
Ch. 6 - Hypothesis testing (*updated 5:42pm 4/24/2019, goodness of fit added)
Ch. 7 - Linear regression (*updated 5:50, 4/24/2019)
R Activities:
Here is your first R activity and data set.
Here is a pdf of the names of Rcolors.
R Activity 2.
Here is a website where you can evaluate R code online from your web browser from any device: https://rdrr.io/snippets/
R Activity 3.
Coin flipping simulation code.
Poker simulation code.
R Activity 4.
R statistical software:
You will need access to R statistical software. Here are instructions for getting R statistical software up and running on your computer. It should already be installed in all computer labs in Herak as well. If you find a computer where it is not installed, you can use these instructions to install it, or report it to me, and I will have IT install it.
Another option for having quick access to R (and this is useful for a smartphone) is SageCell at: https://sagecell.sagemath.org/. This website can be used to evaluate commands from a variety of programming languages (including MATLAB and Python). Just select R from the language tab at the lower right of the textbox. If you are familiar with MATLAB, choose the option "Octave". Octave is basically an open source version of MATLAB and you can run MATLAB code using the Octave language option on SageCell.
Here is another website where you can evaluate R code online from your web browser from any device: https://rdrr.io/snippets/
Course Plan:
Here is a weekly outline of the course and material covered. This is a tentative plan, but we will likely not vary from this by more than a few days.
| Week | Tentative course plan | Holidays | Chapters |
| 1/14 to 1/19 | Descriptive Statistics | no class on Monday | 1 |
| 1/21 to 1/26 | Descriptive Statistics | no class on Monday | 1 |
| 1/28 to 2/2 | Probability | 2 | |
| 2/4 to 2/9 | Probability | 2 | |
| 2/11 to 2/16 | Random variables and distributions | 3 | |
| 2/18 to 2/23 | Random variables and distributions | no class on Monday | 3 |
| 2/25 to 3/2 | Random variables and distributions | 3 | |
| 3/4 to 3/9 | Confidence intervals | 7 | |
| 3/11 to 3/16 | Spring Break, no classes | ||
| 3/18 to 3/23 | Confidence intervals | 7 | |
| 3/25 to 3/30 | Hypothesis testing | 8 | |
| 4/1 to 4/6 | Hypothesis testing | 8 | |
| 4/8 to 4/13 | Hypothesis testing | 9 | |
| 4/15 to 4/20 | Hypothesis testing | no class Friday | 9 |
| 4/22 to 4/27 | Linear regression | no class Monday | 4,6,7 |
| 4/29 to 5/4 | Linear regression | 4,6,7 | |
| 5/6 to 5/11 | Final Exam |
A Note about the quizzes, exams, and material coverage:
Quizzes cover only the material learned in the previous week or two. Each quiz is worth 25 points, and this can be thought of symbolizing that it is roughly one quarter of a regular exam in length. Normally quizzes are from 1-2 pages in length. They are timed for 15 to 25 minutes. The actual content may vary from 1-2 longer problems (i.e. longer more involved calculations) or 6-8 short problems (e.g. quick calculations, short answer, checking basic concepts, or multiple choice).
Regular exams only cover the new material since the last regular exam. Each regular exam is worth 100 points. Regular exams are normally 4-6 pages long and are timed for 50 minutes. You can use the quizzes as a rough guide for the exams, i.e. a regular exam will be roughly equivalent to four quizzes.
The Final Exam will cover any new material since the last regular exam and additionally will be comprehensive over the entire course. It is timed to 120 minutes, and thus can hypothetically be 2.4x the length of a regular exam. As a general guideline, you can expect it to be roughly equivalent to two complete exams.
These are only general guidelines and are meant to help you prepare for the quizzes and exams.