Statistics 3008/7001 (Applied Statistics) is a course designed for senior undergraduate and research students who need to design experiments and carry out statistical analysis of their data. Emphasis will be placed on the development of statistical concepts and statistical computing, rather than mathematical details. The content covered will be motivated by problem-solving in many diverse areas of application. The topics covered will include regression modelling with emphasis on model formulation, understanding the implication of model assumptions, diagnostic methods for model checking and interpretation, logistic regression for binary variables and binomial counts, log-linear regression for Poisson counts, and exploratory tools for summarising multivariate responses.

Upon successful completion of the requirements for this course, students will be able to:

·         Working knowledge of the statistical computing package R.

·         Fit simple and multiple linear regression models and interpret model parameters.

·         Summarise and analyse relationships between a response variable and a covariate or covariates.

·         Assess and refine simple and multiple linear regression models based on diagnostic measures.

·         Carry out model selection in a multiple linear regression modelling context.

·         The above outcomes for logistic and Poisson log-linear regression models.

·         To understand basic multivariate analyses techniques and the bootstrap.

• Assignments, 30%
• Final Exam 70%

10 hours / week

At least an average of 65% (or equivalent) in the final two years of an Australian undergraduate degree with at least two years of university level statistical and mathematical study including calculus and linear algebra, as well as mathematical statistics and linear regression theory.

Please refer to Course Website