NEW 15.02.2019 List of recommended exercies updated
This is a webpage for a 7.5 hp undergraduate statistical course starting on Monday 21/1, 2019.
Course syllabus is here.
This is a second course in mathematical statistics suitable for students with different backgrounds. It builds upon an introductory course in probability and statistics to give a deeper understanding of some traditional topics in mathematical statistics such as methods based on likelihood, topics in descriptive statistics and data analysis with special attention to graphical displays, aspects of experimental design.
The course introduces a number of standard tools of statistical inference including
bootstrap, parametric and non-parametric testing, analysis of variance, and basics of Bayesian inference.
Textbook and course material
Mathematical statistics and data analysis, 3rd edition, by John Rice
Lecture notes including exercises with solutions: click here to download (constantly updated)
Lectures and Exercises (for the schedule of classes click here)
Mondays at 13.15-15.00, room Pascal
Tuesdays at 13.15-15.00, room Pascal (no class on 5/2)
Wednesdays at 13.15-15.00, room Pascal (no class on 6/2)
Fridays at 13.15-15.00, room KA (no class on 25/1, room KB on 8/2, no class on 1/3)
March 19, 2019, 14.00-18.00 (deadline for the registration February 28)
June 11, 2019, 08.30-12.30, 1st resit exam
August xx, 2nd resit exam
Grading system and Bonus points
If you have a question on the course content so far that you want me to address once again, please send an email to serik at chalmers.se. I will answer during the nearest lecture to those questions that repeatedly appear in students’ emails.
Student representatives (first meeting after the class on Friday 15/2)
MPBME emeljo at student.chalmers.se Emelie Johansson
MPCAS toddie1992 at hotmail.com Tommy Phung
MPENM felmatt at student.chalmers.se Felix Mattsson
MPBME yang_peizheng at outlook.com Peizheng Yang
Lists of students: if registered for the course, please send email to “serik at chalmers.se” with (your study program, last name, first name)
Old exams with answers