Research Design and Advanced Analytical Methods - SACO8120

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Module delivery information

This module is not currently running in 2024 to 2025.


This module will introduce students to research design and hypothesis testing, drawing upon the different scientific approaches used in biological and forensic anthropology. Core statistical components, such as inference for parametric statistical testing, will be covered. This module will have an extensive, computer practical-based component that will enable students to run advanced statistical tests (univariate and multivariate), which will be supported by lectures. Upon completion students will understand the principle qualitative and quantitative analytical approaches to research, and the best ways of presenting results.


Contact hours

Total contact hours: 20
Private study hours: 130
Total study hours: 150


MSc Forensic Osteology and Field Recovery Methods

Method of assessment

Report (3000 words) (80%)*
Project Proposal (20%)
* This element is pass compulsory and must be passed to achieve the learning outcomes of the module.

Reassessment methods: Like for Like

Indicative reading

Reading list (Indicative list, current at time of publication. Reading lists will be published annually)

Lasker, G.L. and Gastel, B. (2005) Research strategies in human biology. Cambridge University Press.

Day , R.A. ad Gastel, B. (2011) How to write and publish a scientific paper. (7th edition) Greenwood press.

Field, A. (2013) Discovering Statistics Using IBM SPSS Statistics 4th edition SAGE Publications Ltd

Tabachnick BG, Fidell LS. 2013. Using multivariate statistics (6th ed). Allyn and Bacon

See the library reading list for this module (Canterbury)

Learning outcomes

The intended subject specific learning outcomes. On successfully completing the module students will be able to:

8.1 evaluate methodologies and develop critiques of them and, where appropriate, to propose new hypotheses and construct a research project with testable hypotheses.

8.2 develop different research strategies and designs for projects using quantitative statistical methods.

8.3. analyze data with univariate and multivariate statistical techniques, using associated computer software and evaluate critically current research and advanced scholarship in the discipline

8.4. present results suitable for a scientific report.

The intended generic learning outcomes. On successfully completing the module students will be able to:

9.1. critically evaluate and problem solve.

9.2 independently learn and time manage

9.3. organise and present information in a clear and concise manner.

9.4. demonstrate development of advanced computing practical skills.

9.5. demonstrate further development of communication in writing.


  1. ECTS credits are recognised throughout the EU and allow you to transfer credit easily from one university to another.
  2. The named convenor is the convenor for the current academic session.
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