University of Queensland
Area of Study
Taught In English
(STAT2004 + MATH2000)
Course Level Recommendations
ISA offers course level recommendations in an effort to facilitate the determination of course levels by credential evaluators.We advice each institution to have their own credentials evaluator make the final decision regrading course levels.
Host University Units2
Recommended U.S. Semester Credits4
Recommended U.S. Quarter Units6
Hours & Credits
OverviewCourse DescriptionLikelihood theory: maximum likelihood, asymptotic theory, nuisance parameters, applications, likelihood ratio test, score tests, Wald tests, exponential family (properties: sufficiency, completeness). Confidence intervals, hypothesis tests. Baysian inference. Multivariate normal distribution & quadratic forms. Distributional results & inference for general linear model.Course IntroductionStatistics provides the mathematical language and techniques necessary for understanding and dealing with chance, uncertainty and variability in Nature. In this course you will learn how to use probability and other branches of mathematics to extract patterns and other useful information from numerical data in a careful and precise manner. The course has three main parts:
Learning ObjectivesAfter successfully completing this course you should be able to:
- Classical Mathematical Statistics. Here you will learn the powerful classical mathematical techniques for efficient data analysis.
- Computational Methods. Here you will learn how modern computational techniques can be used to implement the relevant statistical methodology.
- Bayesian Statistics. Here you will learn how to use the Bayesian approach to statistics.
Class Contact3 Lecture hours, 1 Tutorial hourAssessment SummaryProblem Set(s): 40%Final Exam: 60%
- Understand of the main concepts of mathematical statistics, and use this understanding to solve a range of practical and theoretical problems in statistics.
- Recognise the role of Monte Carlo methods in modern statistics, and apply Monte Carlo techniques to simple problems.
- Apply the Bayesian approach to statistical inference, and understand its significance.
Courses and course hours of instruction are subject to change.
Eligibility for courses may be subject to a placement exam and/or pre-requisites.
Some courses may require additional fees.
Credits earned vary according to the policies of the students' home institutions. According to ISA policy and possible visa requirements, students must maintain full-time enrollment status, as determined by their home institutions, for the duration of the program.