Math 321 Statistics for Experimentalists Spring 2024: Syllabus

Textbook

Additional resources

Description:

An applied statistics course for those with calculus preparation. Topics include descriptive statistics, probability theory, discrete and continuous random variables, and methods of inferential statistics including interval estimation, hypothesis testing, and regression.

Outcomes:

Students will learn the language and basic techniques of probability and statistics. They will apply these techniques to calculate probabilities and perform statistical tests. They will also clearly communicate and interpret their solutions. Students will also learn to use the basics of the statistical program R.

Grades:

Grades will be based on scores on exams, WeBWorK, and worksheets/R projects. There will be 3 exams during the semester, each worth 13% of the final grade. In addition, a cumulative final exam will count for 25% of the grade. The remaining 36% of the grade will come from scores on WeBWorK assignments (18%) and worksheets/R projects (18%). An approximate schedule for the semester is on the home page for the course. No extra credit will be given. Final grades will be assigned using the following scale (with + or - for the top and bottom scores within appropriate ranges):
Score Grade
90-100 A
80-90 B
70-80 C
60-70 D
0-60 F

Homework:

You will have about one WeBWorK assignment each week. These assignments comprise your homework score for the final grade and should be done outside of class on a computer (the usual deadline will be 10:00 PM). Solutions are automatically and instantaneously checked for accuracy. You are allowed (and encouraged) to retry each problem until you get it right.

A list of additional suggested exercises from the textbook is posted on the course web page. These problems will not be collected or graded, however it is nearly impossible to learn without practice. Additional practice problems may be found in many of the additional class resources, but I won't usually post specific recommendations. You are encouraged to bring questions about the homework and practice problems to office hours and class. You are also welcome to use Kahn Academy or other on-line instructional material; I am happy to look at whatever you find and tell you if it seems reasonable.

In general, I try to make the WeBWorK assignments short (in terms of number of problems) but challenging. This means I avoid the routine problems that are important for building skills when you first learn a technique. Instead, those problems are in the suggested exercises. I expect you to do enough of those problems to feel comfortable solving the more difficult problems on the WeBWorK. It is up to you to determine how much practice is enough (I think more is always better, but you're the expert on how you learn, so I'm leaving it up to you to decide).

Worksheets/ R projects:

You will have a worksheet or R project about once a week. These are meant to be worked on in small groups in class (and sometimes finished at home and turned in the following class). Worksheets guide you in building skills, developing techniques, using R, etc. They are meant to encourage you to think about what you know and how to use that knowledge. Usually this leads to some confusion, which is good, but the goal is for everything to eventually make sense (after you've asked questions, done some homework, and thought about it on your own). Worksheets and R projects are graded on completion, so don't be afraid to make guesses or try things you're not totally sure of.

Exams:

Exams encourage you to review, practice, and refine your skills. My goal is to make exams long enough to cover the relevant material, but short enough that everyone has time to finish. Examples of past exams can be found on the old editions of the course web page.

Math Learning Center (MLC):

Help on the homework or any other class material may be available in the Math Learning Center, which is located in Bollier 218. A schedule of tutors and their hours will be posted in the MLC and online. This class is advanced enough that not all tutors may be able to help with all your questions.

Gonzaga policies

This course also follows Gonzaga'a policies on academic integrity, religious accommodations, title IX, harassment and discrimination, and access/accommodation for those with disabilities. Those policies can be found here (myGU link, login required).

Course pages

Links

Office hours

Logan Axon
Department of Mathematics
MSC 2615
Gonzaga University
Spokane, WA 99258
Office: Herak 307A
Phone: 509.313.3897
Email: axon@gonzaga.edu

Last updated 1/15/2024