THREE-DIMENSIONAL MODELING

Course objectives

Objectives 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 an 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.

Channel 1
LUCA MALATESTA Lecturers' profile

Program - Frequency - Exams

Course program
- Descriptive Statistics 1: mean, mode and median. Calculation examples and differences between moments. Use of MS Excel spreadsheets for processing. - Descriptive Statistics 2: Analysis of data variability around the mean and median. Presentation and use of open source software for statistical analysis. - Descriptive statistics 3: Calculation of variance, standard deviation, standard error, coefficient of variation. Evaluation of the different fluctuations around the mean. - Introduction to the concept of data normality. Gaussian curve and its use in statistical analysis. Data normalization. Data transformation for normalization purposes. - One-way analysis of variance ANOVA. Comparison of averages. Introduction to the concepts and use of ANOVA. Examples of ANOVA calculation. - Introduction to two-way ANOVA and presentation of calculation examples. Neumann-Keuls, Bonferroni, and Tukey tests. - Correlation analysis. Meaning of r and of r^2. Statistical model concept. Introduction to linear regression. Calculation and meaning of linear regression coefficients. - Application of linear regression models for predictive purposes. Use of "large databases". Applying linear regression analysis using open source software. - Multiple linear regression analysis. Evaluation of the statistical significance of coefficients and statistical models. Applications. - Archaeological approaches to data. Spatial analysis, Seriation, Assemblage diversity.
Prerequisites
Basic usage of standard Operating Systems (Windows / MacOS / Linux) Use of spreadsheet software (Excel / OpenOffice Calc / LibreOffice Calc) Basic concepts of mathematics, algebra and calculus
Books
Reference text: Carlson, D.L. Quantitative methods in Archaeology using R. Cambridge University Press, 2017. 455 pp. Theory slides used by the teacher and provided to the students Resources for practical applications provided by the teacher
Frequency
It is necessary to attend the lessons in presence To carry out the practical activities a laptop running Windows, MacOS or Linux operating system will be required
Exam mode
The oral exam will consist of an assessment of the ability to analyze an example data set. The concepts taught during the course will be applied to a dataset provided by the teacher, and errors of analysis and evaluation will be corrected. In addition to the analysis of the dataset, some theoretical questions dealing with the concepts taught during the course may be asked.
Lesson mode
Classroom lessons will be complemented by practical activities, consisting of the statistical analysis of example data sets. For data processing the "JASP" software will be used (downloadable for free from the official website, or alternatively provided by the teacher).
  • Academic year2025/2026
  • CourseArchaeological Materials Science
  • CurriculumSingle curriculum
  • Year2nd year
  • Semester1st semester
  • SSDBIO/07
  • CFU3