Bi3434 Processing of research data in anthropology

Faculty of Science
Spring 2024
Extent and Intensity
0/2/0. 4 credit(s). Type of Completion: z (credit).
Teacher(s)
doc. RNDr. Miroslav Králík, Ph.D. (seminar tutor)
Mgr. Karolína Kupková (seminar tutor)
Guaranteed by
doc. RNDr. Miroslav Králík, Ph.D.
Department of Anthropology – Biology Section – Faculty of Science
Contact Person: doc. RNDr. Miroslav Králík, Ph.D.
Supplier department: Department of Anthropology – Biology Section – Faculty of Science
Timetable
Mon 19. 2. to Sun 26. 5. Mon 11:00–12:50 Bp1,01007
Course Enrolment Limitations
The course is only offered to the students of the study fields the course is directly associated with.

The capacity limit for the course is 35 student(s).
Current registration and enrolment status: enrolled: 32/35, only registered: 0/35
fields of study / plans the course is directly associated with
Course objectives
The course follows the previous courses Methods of anthropology I and II. The aim of the course is practical training of students in the preparation and processing of research data for various types of anthropological research. In the training software R (open source) is used.
Learning outcomes
Student will be able to:
- Design a data structure for selected anthropological research;
- Encode data for processing in the program R;
- Clean and transform raw data
- Manipulating data for various analysis and visualization purposes;
- Perform basic analytical calculations and generate secondary data (anthropological indices);
- Visualize and present data for professional outputs.
Syllabus
  • 1. R program, RStudio, data loading/imputing, data formats, variable types, variable names, structure of tables and arrays in anthropological applications
  • 2. Anthropological categories/factors and their data implementation; hierarchical data structures, intra-individual (side of the body, distal - proximal, radial - ulnar, etc.), intra-population categories (sex, class, etc.), and populations; combinations and selections by factors.
  • 3. Types of variables in R, their definition, assignment and use in anthropological research.
  • 4. Visualization e and cleaning raw data, storing and locking data.
  • 5. Morphometric data: points, angles and distances; 2D and 3D data arrays and their conversions.
  • 6. Basic calculations with morphometric data and their graphical representation, calculation of indexes from the distances, calculation of distances from landmark coordinates in 2D and 3D space.
  • 7. Spatial data from terrain and maps; acquiring spatial coordinates, visualizing points on maps and plans, assigning values to visual form of the points.
  • 8. Time data: date / time formats, time calculations (time intervals) and anthropological variables (date of birth, age, age of menarche, age cohorts vs. cross-sectional data).
  • 9. Paired data: body side differences (directional and fluctuation asymmetry), twins, siblings, partners (calculations of similarities and dissimilarities).
  • 10. Repeated measurements and calculation of measurement reliability for different types of variables, relation between measurement accuracy and measurement results.
  • 11. Multiple and longitudinal measurements (time series), arrangement and calculations with longitudinal data.
  • 12. Special types of data: meta-analytical data, genealogical data, etc.
  • 13. Presentation and formatting of tables and graphical outputs.
Literature
    required literature
  • Venables WN, Smith DM, R Core Team. 2017. An Introduction to R. Notes on R: A Programming Environment for Data Analysis and Graphics Version 3.4.2 (2017-09-28).
  • KATINA, Stanislav, Miroslav KRÁLÍK and Adéla HUPKOVÁ. Aplikovaná štatistická inferencia I. Biologická antropológia očami matematickej štatistiky (Applied statistical inference I). 1. vyd. Brno: Masarykova univerzita, 2015, 320 pp. ISBN 978-80-210-7752-2. info
  • Ulijaszek SJ, Kerr DA. 1999. Anthropometric measurement error and the assessment of nutritional status. British Journal of Nutrition 82:165–177.
  • Drozd P. 2007. Cvičení z biostatistiky. Základy práce se softwarem R. Ostrava: Ostravská univerzita, Přírodovědecká fakulta.
Teaching methods
Practical exercises with computer and real empirical data. Practicing data operations under the guidance of an instructor on the student´s own computer.
Assessment methods
Implementation of the given task with computer data and program R.
Language of instruction
Czech
Further comments (probably available only in Czech)
Study Materials
The course is taught annually.
Information on course enrolment limitations: Studenti 1. ročníku Bc studia antropologie
The course is also listed under the following terms spring 2018, Autumn 2018, Autumn 2019, Autumn 2020, autumn 2021, Autumn 2022, Spring 2023, Spring 2025.
  • Enrolment Statistics (recent)
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