Advanced Research Methods (MSci) - PSY00034H

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  • Department: Psychology
  • Module co-ordinator: Dr. Daniel Baker
  • Credit value: 20 credits
  • Credit level: H
  • Academic year of delivery: 2019-20

Module will run

Occurrence Teaching cycle
A Summer Term 2019-20

Module aims

Numerical and analytic skills are highly prized by employers, and provide graduates with a competitive edge in the job market, or when applying for future courses of study. This module will introduce a range of modern analysis techniques used in both academic and commercial domains. Concepts will be taught with reference to real examples and controversies, and practical sessions will give students hands on experience of implementing the techniques. Former students have gone on to varied and interesting careers in analytical roles, including working for the Government Statistical Service and the Joseph Rowntree Foundation.

Module learning outcomes

  • Give an overview of each data analysis method, including the key underlying theoretical assumptions
  • Compare analysis techniques and select an appropriate method for a given data set or experimental design
  • Design studies to take advantage of advanced analysis techniques
  • Implement some data analysis techniques in R (a software environment used for statistics)

Module content

  • Introduction to R
  • Meta-analysis and systematic reviews
  • Stochastic methods (bootstrapping)
  • Nonlinear curve fitting and optimization
  • Structural equation modelling
  • Multivariate Pattern Analysis
  • Fourier analysis
  • Bayesian statistics

Assessment

Task Length % of module mark
Essay/coursework
VLE-based homework assignments
N/A 40
University - closed examination
Advanced Research Methods
1.5 hours 60

Special assessment rules

None

Reassessment

Task Length % of module mark
Essay/coursework
VLE-based homework assignments
N/A 40
University - closed examination
Advanced Research Methods
1.5 hours 60

Module feedback

Correct answers to (formative) homework assignments will be provided on the VLE following submission.

Feedback on presentations will be provided by email following each presentation.

Indicative reading

There are no key texts for this module.



The information on this page is indicative of the module that is currently on offer. The University is constantly exploring ways to enhance and improve its degree programmes and therefore reserves the right to make variations to the content and method of delivery of modules, and to discontinue modules, if such action is reasonably considered to be necessary by the University. Where appropriate, the University will notify and consult with affected students in advance about any changes that are required in line with the University's policy on the Approval of Modifications to Existing Taught Programmes of Study.