AEB_105 Statistics for archaeologists

Faculty of Arts
Spring 2021
Extent and Intensity
0/2. 3 credit(s). Recommended Type of Completion: k (colloquium). Other types of completion: z (credit).
Teacher(s)
Mgr. Josef Wilczek, Ph.D. (lecturer)
Mgr. Petr Pajdla (seminar tutor)
Guaranteed by
prof. Mgr. Jiří Macháček, Ph.D.
Department of Archaeology and Museology - Faculty of Arts
Contact Person: Jitka Šibíčková
Supplier department: Department of Archaeology and Museology - Faculty of Arts
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 6 fields of study the course is directly associated with, display
Course objectives
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
Syllabus
• 1. The 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).
Literature
recommended literature
• 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, casestudies), group-work, individual preparation (homeworks).
Assessment methods
homework consist of 9 topics (each of them having 2 to 19 questions); 50 % of correct answers is needed
Language of instruction
Czech
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 ve čtyřhodinových blocích dle rozvrhu v týdnu od 12. do 16. 3. 2018.
The course is also listed under the following terms Spring 2007, Spring 2009, Spring 2014, Spring 2016, Spring 2018.
• Enrolment Statistics (Spring 2021, recent)