Statistical Methods

Math 222 - Spring 2026

Instructor: Brian Lins
Office Hours: See my weekly schedule, and by appointment
Office Location: Pauley 301
Free Textbook: OpenIntro Statistics, 4th edition
Course Syllabus: syllabus.pdf

Announcements

No announcements yet.

Tentative Schedule

Week	Topic	Notes	Projects
1	Intro to R, sampling and experiments	Week 01
2	Exploratory data analysis	Week 02
3	Probability and random variables	Week 03	Project 1
4	Probability distributions	Week 04
5	Inference for proportions, Midterm 1	Week 05
6	Comparing proportions	Week 06
7	Inference about means	Week 07
8	Analysis of variance	Week 08
9	More ANOVA, Midterm 2	Week 09
10	Least squares regression	Week 10
11	Logistic regression	Week 11
12	Simulation methods	Week 12
13	Bayesian statistics, Midterm 3	Week 13
14	Bayesian methods	Week 14

The schedule above is tentative, and may be subject to change. Changes will be announced in class, and you are responsible for knowing about any changes even if you miss the class when they are announced.

Attendance Policy

Attendance in this class is required. Repeated absences may result in a forced withdrawal from the course. You are responsible for any material you miss due to absence. Please let me know ahead of time if you know that you will not be able to attend class.

Grading Policy

The term grade will be based on the following factors.

Component	Proportion
Projects	25%
Midterms	45%
Final Exam	30%

Projects

There will be homework projects due about once every other week. These projects will require the use of the R programming language. Solutions will be graded on a holistic 4 point scale, with a 4 roughly corresponding to an A, 3 to a B, 2 to a C, 1 to a D, and 0 to an F. Here are the criteria that will be used to judge problems.

Score 4: This solution is exceptional. The math is correct, the writing is clear, and the analysis goes beyond the basics and includes additional details beyond the minimum described in the problem. All necessary figures and diagrams have been included, and are well laid out and explained by the surrounding text.
Score 3: This solution is good. The math is mostly correct, the writing is clear, and the analysis covers all of the main points that need to be addressed. All important diagrams are included and clear.
Score 2: This solution is on the right track. There may be some mathematical mistakes, or the writing is not as clear as it should be. Most of the necessary figures are present, but the layout or explanation may be a little off.
Score 1: This solution is deficient. The math may be completely wrong, or there may be serious errors present in the exposition. Figures used to support the solution may be flawed or missing.
Score 0: There is no solution. This is the default grade for any problem that has not been submitted.

Midterm Exams

There will be three midterm examinations during the semester. The exams will focus more on the concepts covered in class than on performing detailed calculations, although some calculations may be required.

Final Exam

There will be a cumulative final exam. It will include questions similar to the ones on the midterms.

Office Hours

My office hours are shown on my weekly schedule. I am also available by appointment. If you can’t stop by during my regular office hours, just ask me after class or by e-mail, and I’ll be happy to make an appointment that works for both of us.

Special Accommodations

Students who think they may need accommodations in this course because of the impact of a disability are encouraged to meet with me privately at the beginning of the semester. Students also should contact Melissa Wood, Title IX/504 Coordinator (mwood@hsc.edu, 434-223-6061) to verify their eligibility for reasonable accommodations. Early contact will help to avoid unnecessary inconvenience and delays.