FF:AES_701 Statistics for archaeologists - Course Information
AES_701 Statistics for archaeologistsFaculty of Arts
- Extent and Intensity
- 0/2/0. 3 credit(s). Recommended Type of Completion: k (colloquium). Other types of completion: z (credit).
- Mgr. Josef Wilczek, Ph.D. (lecturer)
Mgr. Petr Pajdla (seminar tutor)
- Guaranteed by
- Mgr. Josef Wilczek, Ph.D.
Department of Archaeology and Museology - Faculty of Arts
Contact Person: Jitka Šibíčková
Supplier department: Department of Archaeology and Museology - Faculty of Arts
- No prerequisites are required for the course.
- 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 16 student(s).
Current registration and enrolment status: enrolled: 0/16, only registered: 0/16
- fields of study / plans the course is directly associated with
- there are 11 fields of study the course is directly associated with, display
- Course objectives
- The purpose of the course is to familiarize the students with modern statistical methods applied in archaeology. The course develops in two stages. In the first instance, students should become familiar with basic statistical concepts (graph creation and interpretation, correlation, linear regression, parametric statistical tests, etc.). The second part of the course is targeted at traditional multidimensional statistical methods (Principal Component Analysis, Discriminant Analysis, Seriation, Cluster Analysis, etc.) to obtain objective and reproducible information on various archaeological issues, such as the dating of archaeological structures, comparison of artefact productions, their variability, etc.
- Learning outcomes
- At the end of this course, the student will be able:
to understand the basic statistical terms;
to calculate and interpret the values of the central tendency;
to create the basic graphs and interpret them;
to interpret distributions of variables;
to calculate and interpret the amount of correlation between variables;
to calculate the linear regression model and - on its basis - to predict values;
to define the null and the alternative hypothesis;
to understand the probability distribution, the meaning of statistical significance and the basics of the inferential statistics;
to use the basic parametrical tests (t-test for independent and dependent samples, t-test for correlation coefficients, and the analysis of variance) ;
to understand the basic data treatment in MS Excel and StatSoft Statistika
to apply multidimensional statistical methods (PCA, CA, DA)
- 1. Basic statistical terms.
- 2. Types of variables.
- 3. Descriptive and inferential statistics.
- 4. Descriptive statistics (frequency tables, graphs, characteristics of the central tendency, characteristics of the variability, distribution).
- 5. Correlation.
- 6. Linear regression.
- 7. The probability distribution.
- 8. Hypotheses and their testing.
- 9. One-dimensional statistical parametric tests (t-test for independent and dependent samples, t-test for correlation coefficients, ANOVA).
- 10. Multi-dimensional statistics (PCA, CA, DA).
- recommended literature
- HEBÁK, Petr. Statistické myšlení a nástroje analýzy dat. Vyd. 1. Praha: Informatorium, 2013. 877 s. ISBN 9788073331054. info
- MAREK, Luboš. Statistika v příkladech. První vydání. Praha: Kamil Mařík - Proffesional Publishing, 2013. 403 stran. ISBN 9788074311185. info
- MELOUN, Milan, Jiří MILITKÝ and Martin HILL. Počítačová analýza vícerozměrných dat v příkladech. Vyd. 1. Praha: Academia, 2005. 449 s. ISBN 8020013350. info
- Teaching methods
- Theory and practice (computation of practical examples, case studies), group-work, individual preparation (homework).
- Assessment methods
- homework consists of 9 topics (each of them having 2 to 19 questions); 50 % of correct answers are needed
- Language of instruction
- Further comments (probably available only in Czech)
- The course is taught once in two years.
The course is taught: every week.
General note: Předmět bude vyučován blokově v následujích termínech: 12.-14.5. (vždy od 9.00 do 12.00 a od 13.00 do 16.00) v prostorách Mečová 5.
- Permalink: https://is.muni.cz/course/phil/spring2022/AES_701