MATH30520: Statistical Methods

• Statistical Concepts

• None

• None

• To provide a working knowledge of the theory, computation and practice of multivariate statistical methods, with focus on the linear model.

• Introduction to statistical software for data analysis.
• Multivariate normal distribution.
• Multivariate analysis, including principal component analysis.
• Regression: linear model, inference, variable selection, analysis of variance, factorial experiments, diagnostics, influence, weighted least squares, transformations.

Subject-specific Knowledge:

• By the end of the module students will:
• be able to solve novel and/or complex problems in Statistical Methods.
• have a systematic and coherent understanding of the theory and mathematics underlying the statistical methods studied.
• be able to formulate a given problem in terms of the linear model and use the acquired skills to solve it.
• have acquired a coherent body of knowledge on regression methodology, based on which extensions of the linear model such as generalized or nonparametric regression models can be easily learnt and understood.

Subject-specific Skills:

• In addition students will have specialised mathematical skills in the following areas which can be used with minimal guidance: Modelling, Computation.

Key Skills:

• Synthesis of data, critical and analytical thinking, computer skills

• Lectures demonstrate what is required to be learned and the application of the theory to practical examples.
• Computer practicals consolidate the studied material and enhance practical understanding.
• Assignments for self-study develop problem-solving skills and enable students to test and develop their knowledge and understanding.
• Formatively assessed assignments provide practice in the application of logic and high level of rigour as well as feedback for the students and the lecturer on students' progress.
• The two end-of-term computer-based examination components assess the ability to use statistical software and basic programming to solve predictable and unpredictable problems.
• The end-of-year written examination assesses the acquired knowledge from a more conceptual viewpoint, including mastery of theoretical aspects underpinning the studied methodology.

Eight written or electronic assignments to be assessed and returned. Other assignments are set for self-study and complete solutions are made available to students.

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