Statistics
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Department of Mathematics & Statistics

Papers


Download the flowchart for 2017


Struggling to decide which 100-level Mathematics paper to take first? Our placement tools can help you.

The Department offers 13 Statistics undergraduate papers at 100, 200 and 300-level (as well as a selection of 400-level postgraduate papers). This section includes short descriptions of these papers, together with links to individual illustrated paper pages which feature information about the subject, the paper and assessment procedures.

See the flowchart of available papers for 2017, their prerequisites and semesters.


Click the paper name below for complete details.

Jump to 200 level, 300 level, 400 level


100 level

STAT110 Statistical Methods     18 points   First Semester, Summer School

Introduction


STAT115 Introduction to Biostatistics     18 points   Second Semester

A paper for students in the health sciences covering an introduction to the research process and study design, measures for describing data, the binomial and normal distributions, estimation and inference for continuous data, estimation and inference for categorical data, regression procedures and statistical issues in study design. The statistical software R will be used throughout the paper to assist with data analysis.


200 level

STAT210 Statistical Methods 2     18 points   Second Semester

A service course in Statistics that builds on the introduction that many students receive in either STAT 110 Statistical Methods or STAT 115 Introduction to Biostatistics. Note that this course is intended for students not taking statistics as a major. As such, it cannot be credited to a major or minor in statistics if STAT241, STAT242, STAT251, STAT342, ECON210, FINC203 or FINC308 has been passed previously or is being taken concurrently.


STAT241 Regression & Modelling 1     18 points   First Semester

This central paper in applied statistics develops regression models for analysing variability in data. It is the first in a modelling sequence required for a statistics minor, a statistics major or a Diploma for Graduates endorsed in Statistics. It is also useful as a service subject for students majoring in any subject involving the analysis of data. Topics include simple and multiple linear regression, residual analysis and inflence, methods for finding the best model, the importance of qualitative predictors using dummy variables, covariance analysis and experiments involving one and two factors; logistic regression and the comparison of models using deviance differences and AIC; adjusted odds ratios and probability calculations using the chosen best model. Binomial data and overdispersion are discussed. SPSS 22 and R are used.


STAT242 Multivariate Methods     18 points   Second Semester

This paper looks at procedures for the analysis and interpretation of data involving several response variables, and has wide application in research methodology in the biological, health and social sciences. The following procedures are all taught: tests of significance for multivariate data, principal component analysis, exploratory and confirmatory factor analysis, methods of discrimination including Fisher discrimination analysis, quadratic discrimination, and the analysis and use of multinomial logistic regression models for discrimination when appropriate, cluster analysis, canonical correlation analysis, multivariate distance measures, multidimensional scaling, correspondence analysis and methods of ordination. SPSS 23 and its add-on AMOS23 are used throughout the paper although some use may be made of R.


STAT251 Design of Research Studies     18 points   First Semester

An overview of design principles for scientific research. The topics covered include types of research study, random and systematic sampling, stratified sampling, basic experimental designs, replication, error degrees of freedom, defining sampling and experimental units, blocking, factorial experiments and repeated nested designs.


STAT261 Probability and Inference 1     18 points   First Semester

A introduction to mathematical statistics and probability theory. Probability and random variables, simulation, sampling distributions, statistical modelling and estimators, hypothesis testing.


300 level

STAT341 Regression and Modelling 2     18 points   First Semester

An introduction to generalised linear models, nonlinear regression models, and mixed effects models, with a mixture of background theory and practice in applying the methods to real datasets.


STAT342 Multivariate Methods     18 points   Second Semester

This paper looks at procedures for the analysis and interpretation of data involving several response variables, and has wide application in research methodology of the biological, health and social sciences. Tests of significance for multivariate data, principal component analysis, exploratory and confirmatory factor analysis, methods of discrimination including the use of multinomial logistic regression models, canonical correlation analysis, cluster analysis, multivariate distance measures, multidimensional scaling, correspondence analysis and methods of ordination. SPSS 23 and its add-on AMOS23 are used throughout the paper although some use may be made of R.

Note that this paper is restricted against STAT 242 which has the same lectures but different assessment involving a project.


STAT350 Introduction to Bayesian Modelling     18 points   Second Semester
Not available in 2017

An introduction to the theory and application of Bayesian inference with an emphasis on applications. Bayesian methods for fitting standard statistical models will be considered, as well as hierarchical models and models that account for data collection. Models will be fitted using modern Bayesian software including WinBUGS/JAGS and R.


STAT352 Applied Time Series     18 points   Second Semester

An introduction to the practical aspects of the statistical analysis of time series and its application to the physical sciences and econometrics. Topics include seasonal decomposition, identification and estimation of ARIMA models, seasonal ARIMA models, and forecasting. Time series analysis is the statistical analysis of ordered sequences of data. The distinguishing feature is that these data are correlated. Such data arise in a bewildering range of application areas that include:

* Climatology: Estimation long term changes of climate

* Economics: Analysis of quarterly or monthly CPI, unemployment rates

* Finance: Estimating volatility of stock market returns

* Dendrochronology: Paleoclimate reconstruction based on series of tree ring widths

* Sonar: Detection of underwater signals

as well as communications, speech compression, seismology, control theory, and many many more.


STAT362 Probability and Inference 2     18 points   Second Semester

Theory of ordinary least squares, maximum likelihood estimation and inference, hypothesis testing, Bayesian statistics.


STAT380 Statistical Computing     18 points   First Semester

A paper that introduces students to computational methods in statistics.