F79PS - Further Statistical Methods

Course leader(s):

• Panagiota Birmpa (Edinburgh, September)
• Haslifah Hasim (Dubai, September)
• Ong Kai Lin (Malaysia, September)

Syllabus

1. Confidence intervals and hypothesis tests using parametric and non-parametric methods (1.1 1. Solution of problems using software, 1.2 2. Small and large sample situations involving one or two populations, 1.3 3. Introduction to various non-parametric tests, 1.4 4. Choosing the most appropriate test by comparing different possibilities)

2. Analysis of variance for several populations (2.1 1. Construction of ANOVA table manually and by software, 2.2 2. Analysis of results from ANOVA table including the follow-up, 2.3 3. Contrasts, post-hoc tests and factorial ANOVA, 2.4 4. Hotelling's T-test)

3. Introduction to Generalised Additive Models (3.1 1.Non-Parametric Regression - GAMS, Bin Smoothing, 3.2 2. Loess/ Variance Bias Trade-off, 3.3 3. Kernel Smoothing/Splines)

4. Multivariate Data Analysis (4.1 1. Principal Component Analysis PCA Introduction, 4.2 2. Factor analysis, 4.3 3. Cluster analysis/ k means)

Learning outcomes

By the end of the course, students should be able to do the following:

• analyse the statistical theory of linear, nonlinear, and multivariate methods.
• apply these methods to investigate practical problems in various contexts.
• employ statistical software competently to perform the analysis of experimental data.
• compose a well-structured report to effectively summarise and communicate the results from a statistical analysis.
• justify the application of statistical methods in solving scientific problems within the social sciences.

Further details

Curriculum explorer: Click here

SCQF Level: 9

Credits: 15