- Total units 48 Units
- Major code APST-MAJ
- Academic career Undergraduate
As John Naisbett said of modern society, “we are drowning in information but starved for knowledge”. One of the most in-demand roles these days is that of applied statistician – the key person essential for decision-making and for understanding our data-driven world. In this major, you will learn to understand and use a wide array of statistical modelling techniques that will empower you to make sense of data and offer insights to a wide variety of disciplines, from archaeology to zoology and almost everything in between. If there are data, there is a need for applied statistics.
1. Exhibit a working knowledge of the statistical computing package R.
2. Apply statistical survey sampling techniques to design a routine sample survey.
3. Apply basic principles in the design of simple experiments.
4. Fit simple and multiple linear regression models and interpret model parameters.
5. Carry out model selection in a multiple linear regression modelling context.
6. Communicate the role of generalized linear modelling techniques (GLMs) in modern applied statistics and implement GLM methodology.
7. Effectively communicate statistical analyses graphically, numerically and in written reports
8. Understand basic multivariate analyses techniques and the bootstrap.
9. Understand and describe statistical models of transfer between multiple states, including processes with single or multiple decrements, and derive relationships between probabilities of transfer and transition intensities
10. Run and interpret time-series models and regression models for time series.
11. Use multivariate time-series models such as vector autoregression (VAR) to analyse multidimensional time series data.
12. Interpret the results of a Bayesian analysis and perform Bayesian model evaluation and assessment.
13. Formulate a Bayesian solution to real-data problems.
This major requires the completion of 48 units, which much consist of:
24 units from completion of the following compulsory courses:
STAT3011 Graphical Data Analysis
STAT3012 Design of Experiments and Surveys
STAT3015 Generalised Linear Modelling
STAT3032 Survival Models
6 units from completion of courses from the following list:
STAT3008 Applied Statistics
STAT3016 Introduction to Bayesian Data Analysis
6 units from completion of courses from the subject area EMET Econometrics
12 units from completion of further courses from the subject area STAT StatisticsBack to the top