400 level (postgraduate)Not all papers shown here will be available in any one year. Additional papers may be offered. Check with the Director of Studies for a confirmed list of modules that are running, their prerequisites and semester.
INFO420 Statistical Techniques for Data Science 20 points Second Semester
This paper is compulsory for the Master of Business Data Science.
An introduction to statistical modelling and multivariate analysis that includes generalised linear models and procedures for analysing patterns in multiple quantitative measurements. The paper combines background theory with practice in applying the methods to real datasets.
QGEN401 Quantitative Genetics and Improvement 20 points Second Semester
This paper is compulsory for the Masters of Applied Sciences (Quantitative Genetics).
Quantitative genetics is a suite of statistical methods used to understand the basis of complex genetic inheritance. It is used extensively in primary sector breeding and research, and increasingly in both medical research and endangered species recovery programmes. This paper provides an introduction in commonly-used methods including both the underpinning theory, and application to real life datasets. Topics include genetic parameter estimation, prediction of breeding values, breeding programme design, and analyses of genomic data. The paper also includes an introduction into NZ-specific applications in primary, health and environmental sectors.
STAT411 Probability and Inference 3 20 points First Semester
An overview of Bayesian and classical theory of statistical inference
STAT412 Generalised Linear Models 20 points Second Semester
We consider the theory and use of generalized linear models beyond what is covered in Stat 310. This paper will include theory, but primarily emphasize application with a focus on parametrization, interpretation, and hypothesis testing of regression parameters in generalized linear models. R is used to illustrate applications in real data analysis.
STAT435 Data Analysis for Bioinformatics 20 points First Semester
The analysis of large data sets is becoming increasingly important in many areas. The techniques covered in this course will be applicable to a wide range of data types, including non-biological data. Exposure to other disciplines (in this case biomedical science) is a must for any applied statistician. Interacting with students from other fields is simulating, and will help you appreciate your statistical skills.
STAT440 Longitudinal Data Analysis 20 points Second Semester
Mixed models are a powerful class of models used for the analysis of correlated data. Examples of correlated data include, but are not limited to, clustered data, repeated observations, longitudinal data, multiple dependent variables, spatial data or data from population pharmacokinetic/pharmacodynamic studies. A key feature of mixed models is that, by introducing random effects in addition to fixed effects, they allow you to address multiple source of variation, e.g. in the longitudinal study they allow you to take into account both within- and between- subject variation.
STAT441 Official Statistics 20 points Second Semester
This course provides an overview of the key areas of Official Statistics. Topics covered include data sources for both sample surveys and administrative data; Census data; the legal and ethical framework of official statistics; an introduction to demography; the collection and analysis of health, social and economic data; data visualisation including presentation of spatial data; confidentiality, data matching and integration; time series; GIS; the system of National Accounts.
The paper is particularly useful for a minor in Statistics, a Diploma for Graduates Endorsed in Statistics or as a paper for the major in Statistics.
Current details can be found at the following link. Note that lectures start on Wednesday 21 July (4:10 to 6pm). The link takes you to the equivalent paper at the University of Auckland as the course is being offerred at several universities using Zoom.
STAT442 Big Data 20 points First Semester
This paper provides an overview of the ideas and methods that are useful when analysing massive datasets. Beginning with regression, this paper introduces penalized methods for regression and then neural networks. Support vector machines are added as a final topic.
STAT443 Bayesian Statistics 20 points First Semester
A course that introduces the Bayesian approach to statistical inference. A theoretical basis is developed while computational issues are addressed using Monte Carlo Markov chain methods.
STAT444 Stochastic Processes 20 points First Semester
An introduction to stochastic processes and stochastic calculus, emphasizing both theory and practical application.
STAT481 Statistical Practice 20 points Full year
This is a six-week placement working as a statistician in a company or government organisation. The choice as to where the work takes place is decided between the student and the Director of Studies. The work can be carried out at any time before April of the year after enrolling for the Postgraduate Diploma in Applied Statistics.
STAT490 Honours Project 40 points First Semester, Full year
A 40-point project in an agreed topic, supervised by one or more staff.
STAT499 Special Topic - Clinical Trials 20 points
Statistical, scientific, ethical, and practical issues in designing, conducting, and reporting randomised trials in humans.