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DRPS : Course Catalogue : School of History, Classics and Archaeology : Postgraduate (History, Classics and Archaeology)

Postgraduate Course: Quantitative Methods and Reasoning in Archaeology (PGHC11462)

Course Outline
SchoolSchool of History, Classics and Archaeology CollegeCollege of Arts, Humanities and Social Sciences
Credit level (Normal year taken)SCQF Level 11 (Postgraduate) AvailabilityAvailable to all students
SCQF Credits20 ECTS Credits10
SummaryThis course introduces students to apply quantitative reasoning to archaeological case studies. It will provide a global perspective of current applications in the field covering descriptive statistics and hypothesis testing. Students will become proficient users of the open source platform R while developing critical skills on the use of statistics within archaeological projects.
Course description The course will explore the key theoretical, methodological and technical aspects of quantitative archaeology. Through a mixture of lectures, practicals, in-class discussions, and projects the students will learn to identify and interpret patterns found in the archaeological record within a diversity of fields and specializations. They will also become aware of the potentials and limitations of statistics specifically linked to the study of the past, including topics such as time and uncertainty.
Entry Requirements (not applicable to Visiting Students)
Pre-requisites Co-requisites
Prohibited Combinations Other requirements None
Information for Visiting Students
High Demand Course? Yes
Course Delivery Information
Academic year 2023/24, Available to all students (SV1) Quota:  24
Course Start Semester 1
Timetable Timetable
Learning and Teaching activities (Further Info) Total Hours: 200 ( Lecture Hours 11, Seminar/Tutorial Hours 11, Programme Level Learning and Teaching Hours 4, Directed Learning and Independent Learning Hours 174 )
Assessment (Further Info) Written Exam 0 %, Coursework 100 %, Practical Exam 0 %
Additional Information (Assessment) 2,500 word Research Project (70%)
3 x Practical assessment (10% each)
Feedback Students will receive verbal feedback during each practical and written feedback for the assessments following standard Learn procedure. They will also have the opportunity to discuss that feedback further with the Course Organiser during his published office hours or by appointment.
No Exam Information
Learning Outcomes
On completion of this course, the student will be able to:
  1. demonstrate the ability to test working hypotheses using statistics;
  2. demonstrate the ability to understand and critically analyse current applications of statistics in archaeology;
  3. demonstrate the ability to apply a wide range of methods to identify patterns in archaeological data;
  4. demonstrate critical understanding of the issues surrounding the investigation, interpretation and display of quantitative datasets and their links to social behavior;
  5. demonstrate independence of mind and initiative; intellectual integrity and maturity; an ability to evaluate the work of others, including peers.
Reading List
Drennan, R. D. (2010). Statistics for archaeologists: a commonsense approach (2nd ed). New York: Springer.

Epstein, J. M. (2008). Why model? Journal of Artificial Societies and Social Simulation, 11(4), 12.

Fletcher, M., & Lock, G. R. (2005). Digging numbers: elementary statistics for archaeologists (Vol. 33). Oxford Univ School of Archaeology.

Reinhart, A. (2015). Statistics Done Wrong: The Woefully Complete Guide. No Starch Press.

Shennan, S. (1997). Quantifying archaeology. University of Iowa Press.

Smith, M. E. (2015). How can archaeologists make better arguments? The SAA Archaeological Record, 18-23.

Verzani, J. (2014). Using R for introductory statistics. CRC Press.
Additional Information
Graduate Attributes and Skills On successful completion of the course, students should be able to:
- gather, integrate and critically assess relevant information
- extract key elements and meanings from complex data sets
- answer a research question by developing a reasoned argument based on quantitative analysis
- present their ideas and analyses in a coherent fashion
KeywordsNot entered
Course organiserDr Sophie Newman
Tel: (0131 6)50 4620
Course secretaryMiss Mel Baker
Tel: (0131 6)50 4030
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