Statistics 511

Statistical Methods

Fall 2026, Section 7

Course outline

This course is an introductory statistics course for the science and engineering majors. The topics to be covered include data summaries, elementary probability theory, basic statistical inference, and selected simple statistical methods in a variety of settings.

The course had been designed to be based on pencil-paper-calculator, but to facilitate the use in your future work of the techniques learned in the course, I will also introduce some simple utilities in R, an open-source programming environment for data analysis and graphics. You may consider the R materials somewhat optional as those will not appear in the quizzes and the exams, but in a long run those could be the most valuable tools you pick up in this course.

Textbook

• Probability and Statistics for Engineering and the Sciences (8th ed), by Devore.

References

• An Introduction to R, by the R Development Core Team.
• Data Analysis and Graphics Using R, by Maindonald, used to be freely downloadable.

Course Work

There will be two midterms and a comprehensive final. There will also be some in-class quizzes mostly on Mondays, and weekly homeworks. The quizzes are open-book open-notes, the exams are closed-book but you are allowed 4 pages of letter-size double-sided crib sheets; you do need to bring your own tables and a working calculator.

Grading Policy

The letter grade will be decided on the basis of homeworks (10%), quizzes (10%), midterms (2 x 25%), and the final (30%).

Calendar

Click here for the due dates of homework assignments and the schedules of quizzes and exams.

Homework assignments

Click here for the homework assignments and related information.

Late Homework Policy

Late homework will not be accepted under any circumstances at any time for any reason except in the case of documented medical emergency. Proof of medical emergency will be required at the time late homework is turned in. If late homework is turned in without talking to the instructor, it will be returned ungraded.

AI Policy

You are encouraged to use all available resources, such as peer discussions and online information, AI tools included, to study the course materials. You should independently finish homeworks, possibly with assistance. You will not have access to AI tools for quizzes and exams.

Lecture Slides

Click here for the slides I will be using in the lectures. The slides are very sketchy. These can be good review materials afterwards, but not so much as learning materials without the verbal explanations to be delivered in the lectures.