ARMSAS-Statistical Approaches: Making sense of your data

Module Provider: Archaeology
Number of credits: 10 [5 ECTS credits]
Terms in which taught: Autumn term module
Non-modular pre-requisites:
Modules excluded:
Current from: 2018/9

Module Convenor: Dr Rob Hosfield


Type of module:

Summary module description:

This module teaches quantitative analytical methods appropriate to archaeological data, techniques and approaches. The module aims to familiarise you with statistical techniques and principles applicable to both single and multiple variable data-sets. The module will familiarise you with standard statistical packages, and data management and presentation techniques. The module is team-taught, using a mixture of lectures and practicals, with in-class problems and exercises. The module is fully coursework assessed. 


This module aims to give you an understanding of key quantitative analytical methods and approaches appropriate to archaeological data. Specifically, it aims to familiarise you with univariate and multivariate statistical principles (e.g. single variables such as the length of leg bones, and multiple variables such as those describing the 3D shape of a skull) and a range of core statistical methods, prior to undertaking your Masters degree-level dissertation work. The practical sessions will introduce you to standard statistical software packages (e.g. Microsoft Excel and SPSS). In addition you will learn how to prepare archaeological statistical data-sets for analysis and presentation/ publication, primarily through the assessed project.

Core Reading:

Shennan, S.J. 1997. Quantifying Archaeology. Edinburgh: Edinburgh University Press.

Field, A. 2009. Discovering Statistics Using SPSS (3rd Edition). London: Sage Publications Limited. Chapters 1-2, 4-7, 9-10, 15.

VanPool, T. & Leonard, R.D. 2011. Quantitative Analysis in Archaeology. Chichester: Wiley-Blackwell. 

Assessable learning outcomes:

Students will be expected to:

  • Demonstrate understanding of the statistical principles and methods for a range of univariate and multivariate statistical techniques appropriate to archaeological investigations;

  • Appropriately apply statistical techniques to quantitative archaeological data sets (e.g. assessing the data requirements of parametric tests; conducting pre-analysis manipulation of quantitative data sets);

  • Demonstrate professional data management practices, including preparing quantitative data sets for analysis and presentation;

  • Demonstrate technical competency in IT skills appropriate to the specific software packages used during the module (e.g. Microsoft Excel, SPSS and/or PAST; although the exact range of software may vary);

  • Use appropriate professional and environmental archaeological standards at all stages of the quantitative data investigation. 

Additional outcomes:

Students’ presentation skills and use of IT will be enhanced through the practical sessions and the in-class exercises and the final project report. Their team working skills will also be developed through participation in discussions within the lectures and practical sessions, and through the completion of the in-class practical exercises. 

Outline content:

The weekly sessions (1 hour lecture + 2 hour practical) will be taught around topics such as the following (although the exact range of topics may vary slightly depending on SAGES staff involvement): basic data types; visual summaries (basic and advanced); descriptive statistics; the normal distribution; samples and sampling; standard non-parametric tests (e.g. Chi-Squared, Kolmogorov-Smirnov, Mann-Whitney); standard parametric tests (e.g. T-test, ANOVA, correlation, and regression); and multivariate statistics (drawing upon examples from selected methods, e.g. Principle Component Analysis (PCA), cluster analysis; and/or discriminant function analysis). The module will finish with a surgery class based around the project assessment. Throughout the module attention will be paid to appropriate methods/techniques of presentation/publication of quantitative data relevant to archaeology. 

Brief description of teaching and learning methods:

The module will be taught using a series of lectures and practical sessions (based around set exercises in statistical theories and methods), combined with the final project report (requiring the use of multiple statistical methods and techniques in the analysis and presentation of a supplied data set). The module will be team-taught by Archaeology Dept. staff.

As a 10 credit module, Statistical Approaches: Making sense of your data should involve 100 hours of study time: attending lectures and practicals, general background reading, and data analysis and writing your report. You should therefore expect the following sort of workload:

- 30 hours: Contact hours in formal teaching sessions (lectures & practicals);

- 20 hours: General background reading and note-taking from key texts for each week’s topic(s) - i.e. 2 hours per week;

- 50 hours: Data analysis for, and writing, the project report. 

Reading List:

Shennan, S.J. 1997. Quantifying Archaeology. Edinburgh: Edinburgh University Press. R

Field, A. 2009. Discovering Statistics Using SPSS (3rd Edition). London: Sage Publications Limited. Chapters 1-2, 4-7, 9-10, 15. R

VanPool, T. & Leonard, R.D. 2011. Quantitative Analysis in Archaeology. Chichester: Wiley-Blackwell. R 


Contact hours:
  Autumn Spring Summer
Lectures 9
Project Supervision 3
Practicals classes and workshops 18
Guided independent study 70
Total hours by term 100.00
Total hours for module 100.00

Summative Assessment Methods:
Method Percentage
Report 100

Summative assessment- Examinations:

Summative assessment- Coursework and in-class tests:

One 3,000 word project report (100%), to be submitted on dates to be set by the Department. Individual written feedback will be provided. 

Formative assessment methods:

Formative feedback will be provided during practical classes. 

Penalties for late submission:
Penalties for late submission on this module are in accordance with the University policy. Please refer to page 5 of the Postgraduate Guide to Assessment for further information:

Assessment requirements for a pass:

A mark of 50%. 

Reassessment arrangements:

Resubmission of coursework during August, but it cannot carry forward more than a pass mark. 

Additional Costs (specified where applicable):

Last updated: 3 May 2018


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