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Advanced Quantitative Methods


Module description

On this module you will become familiar with a wide range of univariate and multivariate statistical techniques, with particular emphasis on evolving and advanced techniques that are not normally covered at undergraduate level.

Indicative module content

  • Descriptive statistics (including skew and kurtosis), distributions (including binomial and Poisson) and transformations
  • Hypothesis testing and univariate statistical techniques
  • Factorial analysis of variance
  • Analysis of co-variance and multiple analysis of variance
  • Advanced correlation techniques
  • Linear regression and logistic regression
  • The General Linear Model
  • Principal components/factor analysis
  • Power, effect size and meta-analysis
  • Re-sampling methods

Learning objectives

By the end of this module, you should be able to:

    • present data in a meaningful way, and to transform it into different presentational formats
    • display knowledge of a wide range of parametric and non-parametric univariate and multivariate statistical procedures
    • display knowledge of the conditions under which the above procedures may reasonably be applied
    • demonstrate an understanding of how to interpret the results of the above statistical procedures.