NEW 1st resit
exam with solutions
This is a webpage for a 7.5 hp undergraduate
statistical course starting on Monday 21/1, 2019.
Instructors: Serik Sagitov
(lectures, exercises) and Olof Zetterqvist (responsible for bonus assignments)
Course syllabus is here.
Course description
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.
Course
material
Lecture
notes
including exercises with solutions: click here to download (constantly updated)
Recommended textbook:
Mathematical statistics and data analysis, 3rd edition, by John Rice
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 and 15/3)
Final exam 2019
March 19,
14.00-18.00 (register before February 28)
June 11, 08.30-12.30, 1st
resit exam (register before May 22) SB Multisal
August 29, 14.00-18.00, 2nd
resit exam (register before July 31) SB Multisal
Grading system and Bonus points
click
here
Students feedback
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.
Old exams with answers
June 2019, 2019, 2018, 2017, 2016, 2014, 2013, 2012, 2011, 2010, 2009, 2008,
2007, 2006, 2005
Useful links
MIT
lecture videos (a more mathematically advanced course)