Overview
MATH5905 is a honours and postgraduate coursework mathematics course.
Units of credit: 6
Prerequisites: MATH2801, MATH2901 or MATH5846 and MATH5856, or admitted to the postgraduate program of the School of Mathematics and Statistics
Excluded: MATH3811, MATH3911
Cycle of offering: Term 1
Graduate attributes: The course will enhance your research, inquiry and analytical thinking abilities.
More information: The Course outline will be made available closer to the start of term - please visit this website: www.unsw.edu.au/course-outlines, opens in a new window
The course outline contains information about course objectives, assessments, course materials and the syllabus.
Important additional information as of 2023
UNSW Plagiarism Policy
The University requires all students to be aware of its policy on plagiarism.
For courses convened by the School of Mathematics and Statistics no assistance using generative AI software is allowed unless specifically referred to in the individual assessment tasks.
If its use is detected in the no assistance case, it will be regarded as serious academic misconduct and subject to the standard penalties, which may include 00FL, suspension and exclusion.
The online handbook entry, opens in a new window contains up-to-date timetabling information.
If you are currently enrolled in MATH5905, you can log into UNSW Moodle, opens in a new window for this course.
Course overview
This course provides a theoretical foundation for statistical inference. The three main goals in inference (estimation, confidence set construction and hypothesis testing) are discussed in decision theoretic framework. Emphasis is put on frequentist and Bayesian approaches.
Parametric, nonparametric and robust procedures are compared and contrasted. Optimality of inference is discussed for fixed sample size and in asymptotic sense. Higher order asymptotic methods are also introduced.
Computationally intensive procedures such as the bootstrap are illustrated theoretically and numerically. Many illustrative examples and practical applications will be discussed.