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Quantitative Methods in Archaeology


Admission requirements

  • BA or BSc degree in Archaeology or a closely related discipline;

  • Admission to the MSc Archaeology programme Archaeological Science.


This course provides theoretical information and hands-on experience in statistics for archaeology.
In the lab sessions, you will acquire basic R skills. Furthermore, you will gain a critical understanding of statistics and how they may be used and misused in archaeological investigations.

The course will cover introductory topics, including differences in data types, descriptive statistics, basic data visualisation techniques, confidence intervals, hypothesis testing and other key statistical concepts.


  • Week 1: Introduction

  • Week 2: Data exploration

  • Week 3: Data visualisation

  • Week 4: Statistical inference – I

  • Week 5: Statistical inference – II

  • Week 6: Statistical inference – III

  • Week 7: Categorical data analysis

Course set-up

The lecturer will present the course material during the lectures. The lecturer will also provide students with R Notebook files for lab sessions. These files will be self-explanatory so that students can also work with them at their own pace.

Course objectives

  • Learn the necessary statistical terminology to understand and convey statistical concepts;

  • Acquire critical thinking on statistical methods employed in archaeology, and gain abilities to evaluate the reliability of statistical analyses and results in published reports, articles, and manuscripts;

  • Obtain substantial skills in building descriptive statistics and data representations;

  • Gain knowledge and expertise to conduct necessary statistical inference and basic modelling;

  • Acquire coding skills and perform statistical analyses using R;

  • Conduct a major statistical project using archaeological data;

  • Learn how to disseminate the results of a quantitative archaeology project effectively.


Course schedule details can be found in MyTimetable.
Log in with your ULCN account, and add this course using the 'Add timetable' button.

Mode of instruction

  • Lectures;

  • Laboratory work.

Course load

  • 7 x 2 hours of lectures (1 ec);

  • 7 x 2 hours of laboratory work (1 ec);

  • Final project (2 ec);

  • Assignments (1 ec).

Assessment method

  • Take-home exam (25%);

  • 3 assignments (10%+15%+15%) (all assignments need to be submitted);

  • Final project draft (10%);

  • Final project (25%)

There will be one final grade. Passing the average grade is sufficient.
Only the final project can be retaken.

Assessment deadlines

All assessment deadlines (exams, retakes, paper deadlines etc.) can be found in MyTimetable.
Log in with your ULCN account, and add this course using the 'Add timetable' button. To view the assessment deadline(s), make sure to select the course with a code ending in T and/or R.

Deadlines are as follows:

  • Assignment 1: week 2

  • Project draft: week 3

  • Take-home exam: week 4

  • Assignment 2: week 5

  • Assignment 3: week 7

  • Final project: week 8/reading week

All due dates are Sunday 23:30 hrs, students get -3 penalty for each day overdue.

Reading list

Not applicable.


Registration in uSis is mandatory. You can register for this course until 5 days before the first class.

Registration in uSis automatically leads to enrollment in the corresponding Brightspace module. Therefore you do not need to enroll in Brightspace, but make sure to register for this course in uSis.

You are required to register for all lectures and tutorials well in time. The Administration Office registers all students for their exams, you are not required to do this in uSis.

Exchange and Study Abroad students, please see the Prospective students website for information on how to apply.

All information (costs, registration, entry requirements, etc.) for those who are interested in taking this course as a Contractstudent is on the Contractonderwijs Archeologie webpage (in Dutch).


For more information about this course, please contact dr. T. (Tuna) Kalayci.


  • Attendance is not compulsory, but strongly recommended: preparing the final project (35%) and three assignments (40%) rely on in-person participation;

  • The mode of instruction may be adjusted depending on COVID-19 measures.