Department of Statistics

STATS 310 Introduction to Statistical Inference

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Below description edited in year: 2018

Points: 15

Prereqs: STATS 210 and 15 points from MATHS 208, MATHS 250 or equivalent

Credit: Final exam 70%; mid-term test 15%; assignments 15%. Must obtain at least 50% in the final exam to pass

Textbooks: J.A. Rice, Mathematical Statistics and Data Analysis, 3rd edition, Duxberry Press, available from the University Bookshop.

For Advice: Yong Wang (Email: | extn: 84700)

Taught: First Semester City

Website: STATS 310 website

This course follows on from course Stats 210 and provides the theory underlying the statistical methods used in Stages 2 and 3. Many BSc (Hons) Statistics courses use this course as a prerequisite. It is a good course for students with interests in Mathematics, Econometrics or Finance, as well as those who consider their main interest to be Statistics.

Topics studied include: Maximum likelihood estimation, likelihood and score functions, maximum likelihood estimates, Cramér-Rao lower bound, asymptotic optimality of maximum likelihood estimates, construction of confidence intervals. Multivariate Distributions, joint, marginal, and conditional distributions, vector random variables, variances and covariances, conditional means and variances, maximum likelihood estimates for multivariate parameters. Hypothesis testing, power and size of hypothesis tests, Neyman-Pearson lemma, link between hypothesis tests and confidence intervals. General linear models, least squares estimates, theory of estimation and testing for linear models.

Although every reasonable effort is made to ensure accuracy, this information for the course year (2018) is provided as a general guide only for students and is subject to alteration. All students enrolling at the University of Auckland must consult its official document, the University of Auckland Calendar, to ensure that they are aware of and comply with all regulations, requirements and policies.

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