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Durham University

Postgraduate Module Handbook 2021/2022

Archive Module Description

This page is for the academic year 2021-22. The current handbook year is 2022-23

Department: Anthropology

ANTH40415: Statistical Analysis in Anthropology

Type Open Level 4 Credits 15 Availability Not available in 2021/22

Prerequisites

  • None.

Corequisites

  • For the MSc in Development - Computational Methods in Social Sciences; For the MSc in Evolutionary Anthropology and MSc Medical Anthropology - Research Skills II

Excluded Combination of Modules

  • None.

Aims

  • Continuing from Research Skills I, this module aims to provide students with further, quantitative research skills. It will develop students' skills in statistical analysis using datasets from anthropological research. Students will learn a range of statistical techniques for use in their research. In addition, they will become proficient in the use of SPSS for statistical methods.

Content

  • Dealing with quantitative data.
  • Organising data for analysis.
  • Selecting an appropriate statistical test.
  • Running statistical tests using SPSS.
  • Interpreting and reporting statistical results

Learning Outcomes

Subject-specific Knowledge:
  • Students should understand a range of subject-specific quantitative methods used in Anthropology.
Subject-specific Skills:
  • Students should be able to analyse, and present the results from, complex data.
  • Students should be able to express themselves in writing clearly and concisely on technical topics.
  • Students should be able to use computer software for analysis and presentation of data.
  • Students should be able to carry out basic quantitative analysis and to represent data effectively.
Key Skills:
  • Communication: Students should be able to express themselves in writing clearly and concisely on technical topics, and become fluent at reading and understanding statistical reports.
  • Statistical analysis: Students should be able to set out data for analysis and select appropriate statistical tests for testing their own, specific hypotheses.
  • Information technology: Students should be able to use computer software (SPSS) for analysis and presentation of data.
  • Data analysis: Students should be able to carry out qualitative analysis, and to represent data effectively.

Modes of Teaching, Learning and Assessment and how these contribute to the learning outcomes of the module

  • Combined lectures and practicals (1.5 hours):
  • Lectures provide students with a coherent review of the research skills and the relevant background to the datasets they will be asked to analyse. Practical elements offer students the opportunity to implement specific quantitative methods under the supervision of a tutor. Students will be given guided step-by-step instruction in carrying out tasks on a computer; this will be followed by less guided, but still supervised, tasks which help consolidate students understanding of the skills and the relevance to anthropological research.
  • Modes of Assessment:
  • Feedback during practical sessions (formative)
  • Will provide students with immediate feedback on their progress and provide the opportunity for individual interaction with tutor.
  • Exam (summative):
  • 1.5 hour unseen exam.

Teaching Methods and Learning Hours

Activity Number Frequency Duration Total/Hours
Practicals 9 Weekly 1.5 hours 13.5
Preparation and reading 136.5
Total 150

Summative Assessment

Component: Project Component Weighting: 100%
Element Length / duration Element Weighting Resit Opportunity
3000 word project 3000 word 100%

Formative Assessment:

Feedback oin practical sessions


Attendance at all activities marked with this symbol will be monitored. Students who fail to attend these activities, or to complete the summative or formative assessment specified above, will be subject to the procedures defined in the University's General Regulation V, and may be required to leave the University