Module overview
Archaeology is an immensely data-rich activity that records the characteristics of sites, landscapes and artefacts, sometimes in great detail. Making sense of that data often relies on quantitative or statistical methods to identify patterns, associations and relationships. This module aims to provide students (who do not necessarily have a recent background in maths or statistics) with some statistical concepts and methods, and the knowledge to apply them using readily available software (spreadsheets). It aims to deliver understanding of a range of ideas about quantitative approaches to archaeology from how to make better graphs to how we can phrase archaeological questions in a range of quantitative ways.
During the module, you will learn about graphical representations of numerical data, descriptive statistics and summaries of single variables; the normal distribution; statistical inference; some measures of association between two variables and ways to explore relationships between numeric variables using correlation and regression.
Aims and Objectives
Learning Outcomes
Transferable and Generic Skills
Having successfully completed this module you will be able to:
- Work effectively with functions and expressions in spreadsheets
- Use a computer to undertake numerical analysis
- Perform simple standard statistical tests for association and significance
- Describe archaeological quantitative data using graphs
- Perform correlation and regression analyses
Subject Specific Intellectual and Research Skills
Having successfully completed this module you will be able to:
- Evaluate, describe and analyse archaeological datasets
- Understand some key statistical concepts
- Express archaeological questions in quantitative ways
Knowledge and Understanding
Having successfully completed this module, you will be able to demonstrate knowledge and understanding of:
- Statistical inference and significance
- Correlation and regression
- Numerical and statistical description of single variables
- The normal distribution and sampling
Syllabus
The syllabus introduces a range of basic quantitative and statistical methods including:
- Measurement levels and graphical summaries of numerical variables
- Descriptive statistics and numerical summaries of single variables
- Statistical inference, measures of association, the chi-squared and Kolmogorov-Smirnov tests
- Normal and t distributions, confidence intervals and sampling
- Studying relationships between numeric variables using correlation and regression
- Statistical inference and some simple measures of association between two variables
- Introduction to multiple regression and other multivariate methods
Learning and Teaching
Teaching and learning methods
Numerical and statistical concepts and methods are introduced in lectures, which are supported by computer- based practical classes to reinforce learning. Short statistical exercises are set to be undertaken outside of contact hours.
The module also expects students to develop skills in spreadsheets (formulae, functions, numerical data processing). Because of the different level of students’ skills on entry to the module, students are guided to self-led online resources for this purpose.
Teaching methods include
- Online and offline courses and resources (for spreadsheet skills)
- Lectures
- Computer-based practical classes
- Project surgeries
Learning activities include
- Set reading and statistical exercises
- Independent work in preparation for data analysis project
- Exam preparation
| Type | Hours |
|---|---|
| Wider reading or practice | 10 |
| Project supervision | 4 |
| Practical classes and workshops | 24 |
| Completion of assessment task | 20 |
| Preparation for scheduled sessions | 30 |
| Revision | 20 |
| Lecture | 12 |
| Follow-up work | 30 |
| Total study time | 150 |
Resources & Reading list
Textbooks
Tufte ER (1983). The visual display of quantitative information. Cheshire, Connecticut: Graphics Press.
Orton, C (2000). Sampling in Archaeology. Cambridge: Cambridge University Press.
Baxter MJ (2003). Statistics in archaeology. London: Arnold.
Thomas, DH (1986). Refiguring Anthropology. Illinois: Waveland Press.
Shennan, SJ (1997). Quantifying Archaeology. Edinburgh: Edinburgh University Press.
Fletcher, M and Lock GR (1991). Digging numbers. Oxford: Oxford University Committee for Archaeology.
Drennan RD (1996). Statistics for archaeologists: a commonsense approach. New York: Plenum.
Assessment
Formative
This is how we’ll give you feedback as you are learning. It is not a formal test or exam.
Exercise
- Assessment Type: Formative
- Feedback:
- Final Assessment: No
- Group Work: No
Summative
This is how we’ll formally assess what you have learned in this module.
| Method | Percentage contribution |
|---|---|
| Test | 30% |
| Data analysis project | 70% |
Referral
This is how we’ll assess you if you don’t meet the criteria to pass this module.
| Method | Percentage contribution |
|---|---|
| Data analysis project | 100% |
Repeat
An internal repeat is where you take all of your modules again, including any you passed. An external repeat is where you only re-take the modules you failed.
| Method | Percentage contribution |
|---|---|
| Data analysis project | 70% |
| Mid-term test | 30% |
Repeat Information
Repeat type: Internal & External