Subject: Statistics
Credit units: 3
Offered: Either Term 1 or Term 2
Weekly hours: 3 Lecture hours
College: Graduate and Postdoc Studies
Department: Mathematics and Statistics

Based on a mathematical and statistical theory foundation, the course introduces statistical methods for supervised and unsupervised learning, focusing on hands-on skills with statistical software, R, and applications to real data.

Prerequisite(s): STAT 344.3 or STAT 345.3.
Note: This course is a hybrid course with STAT 447, and this course cannot be taken for credit after previously taking STAT 447.

For full details about upcoming courses, refer to the class search tool or, if you are a current student, the registration channel in PAWS.

• Class search
• Registration channel

The syllabus is a public document that provides detail about a class, such as the schedule of activities, learning outcomes, and weighting of assignments and examinations.

Once an instructor has made their syllabus publicly available on USask’s Learning Management System, it will appear below. Please note that the examples provided below do not represent a complete set of current or previous syllabus material. Rather, they are presented solely for the purpose of indicating what may be required for a given class. Unless otherwise specifically stated on the content, the copyright for all materials in each course belongs to the instructor whose name is associated with that course. The syllabus is the intellectual property of instructors or the university.

For more information, visit the Academic Courses Policy , the Syllabus page for instructors , or for students your Academic Advising office.

• Bookstore Textbook Search
• Library Reserves Search
• USask Tutoring Network