2024
Statistical Methods for Bioarchaeology
Name: Statistical Methods for Bioarchaeology
Code: MAT14698M
3 ECTS
Duration: 15 weeks/78 hours
Scientific Area:
Mathematics
Teaching languages: Portuguese
Languages of tutoring support: Portuguese, English
Regime de Frequência: Presencial
Presentation
This CU aims to present some statistical methods necessary to study biological remains from archaeological contexts. Introduce students to R software and consolidate Excel, looking for correct data analysis, statistical modeling, and data visualization.
Sustainable Development Goals
Learning Goals
This CU aims to present some statistical methods necessary to study biological remains from archaeological contexts. Introduce students to R software and consolidate Excel, looking for correct data analysis, statistical modeling, and data visualization.
Skills and Competences:
Ability to organize, synthesize and visualize information, being able to describe a set of data through measures, tables, and graphs.
Ability to select and apply the appropriate statistical methods to data analysis objectives and, to interpret, critically, the results obtained.
Ability to use R and Excel correctly and rationally.
Ability to work in a team.
Skills and Competences:
Ability to organize, synthesize and visualize information, being able to describe a set of data through measures, tables, and graphs.
Ability to select and apply the appropriate statistical methods to data analysis objectives and, to interpret, critically, the results obtained.
Ability to use R and Excel correctly and rationally.
Ability to work in a team.
Contents
Introduction to R software and Excel.
Organization, synthesis, and visualization of data. Measurements of location, dispersion, asymmetry, and kurtosis.
Introduction to sampling.
Comparison of one group, two groups or more than to groups, independent and paired samples: parametric and non-parametric approaches.
Regression and correlation.
Homogeneity and independence tests. Conditional association.
Introduction to Logistic Regression.
Organization, synthesis, and visualization of data. Measurements of location, dispersion, asymmetry, and kurtosis.
Introduction to sampling.
Comparison of one group, two groups or more than to groups, independent and paired samples: parametric and non-parametric approaches.
Regression and correlation.
Homogeneity and independence tests. Conditional association.
Introduction to Logistic Regression.
Teaching Methods
The teaching sessions are theoretical-practical, combining concepts with their application to concrete cases. Sessions include data analysis with the help of statistical software, using real data, with students actively participating in their resolution and discussion. In addition to face-to-face sessions, students are encouraged to analyze various data to develop autonomy.
Assessment
Students carry out, in groups, two practical assignments, preparing a report that includes data analysis to achieve specific objectives. Continuous assessment consists of the two works, with equal weight in the final grade, with presentation and discussion.
Exam assessment consists of the two works with a weight of 25% and a written test with al weight of 75%.
Exam assessment consists of the two works with a weight of 25% and a written test with al weight of 75%.
Teaching Staff
- Maria Manuela Melo Oliveira [responsible]
Certificações
