## MAS10c Applied statistics I - exercises

Faculty of Science
Autumn 2023
Extent and Intensity
0/2/0. 2 credit(s) (příf plus uk k 1 zk 2 plus 1 > 4). Type of Completion: z (credit).
Taught in person.
Teacher(s)
Mgr. Jan Ševčík (seminar tutor)
Guaranteed by
doc. PaedDr. RNDr. Stanislav Katina, Ph.D.
Department of Mathematics and Statistics - Departments - Faculty of Science
Supplier department: Department of Mathematics and Statistics - Departments - Faculty of Science
Prerequisites (in Czech)
NOW ( MAS01 Applied statistics I )
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 20 student(s).
Current registration and enrolment status: enrolled: 0/20, only registered: 4/20
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
Statistical evaluation of results is an essential part of many anthropological researches. In the exercises the principles of basic statistical methods will be explained using examples from common practice. Students will be able to recognize situations where individual statistical methods can be used in practice, and to choose the most appropriate method under specific circumstances. They will exercise their computational skills necessary for statistical testing of hypotheses and simplifying the data file. Students will also learn to perform these basic statistical tests in R software.
Learning outcomes
After completing this course:
- student is able to perform exploratory data analysis;
- student controls simpler methods of inductive statistics;
- student can interpret outputs from statistical software.
Syllabus
• 1) Introduction to software R
• 2) Descriptive statistics, absolute frequency, relative frequency, conditional relative frequency
• 3) Numerical characteristics: sample mean, variance, standard deviation, median, quantiles, skewness, kurtosis, correlation coefficients
• 4) Discrete random variables, alternative distribution, binomial distribution, Poisson distribution
• 5) Continuous random variables, normal distribution, two-dimensional normal distribution
• 6) Estimation of parameter mu, sigma and p, confidence intervals
• 7) Introduction to hypotheses testing, normality tests, two-dimensional normality test, test of symmetry
• 8) One sample tests: t-test, F-test, test of parameter p, test of correlation coefficient
• 9) Two sample tests: two sample t-test, F-test, proportion test, test of two correlation coefficients
• 10) Nonparametric tests: sign test, Wilcoxon rank test, Spearman's test
• 11) Testing in contingency tables: contingency table, Pearson's chi-squared test, Fisher exact test, odds ratio test
Literature
recommended literature
• BUDÍKOVÁ, Marie, Maria KRÁLOVÁ and Bohumil MAROŠ. Průvodce základními statistickými metodami (Guide to basic statistical methods). vydání první. Praha: Grada Publishing, a.s., 2010. 272 pp. edice Expert. ISBN 978-80-247-3243-5. URL info
not specified
• HENDL, Jan. Kvalitativní výzkum : základní teorie, metody a aplikace. 3. vyd. Praha: Portál, 2012. 407 s. ISBN 9788026202196. info
• BUDÍKOVÁ, Marie, Štěpán MIKOLÁŠ and Pavel OSECKÝ. Popisná statistika. 4th ed. Brno: Masarykova univerzita, 2007. 52 pp. ISBN 978-80-210-4246-9. info
• BUDÍKOVÁ, Marie, Štěpán MIKOLÁŠ and Tomáš LERCH. Základní statistické metody. Vydání první. Brno: Masarykova univerzita, 2005. 180 pp. ISBN 80-210-3886. info
Teaching methods
Practicals, two hours per week. Full-time teaching. This could be substituted by learning from educational videos and on-line consultations using MS Teams at the time of practicals, if epidemiological situation worsens.
Assessment methods
Attandance (two absences are allowed), two written tests (75% correct answers from each test is needed to pass). Absence could be substituted by doing and submitting the solution of the homework in terms of educational videos. This also will be applied to on-line scenario.
Language of instruction
Czech
Further comments (probably available only in Czech)
The course is taught annually.
The course is taught: every week.
General note: Předmět by si neměli zapisovat studenti matematických studijních oborů.
Listed among pre-requisites of other courses
The course is also listed under the following terms Autumn 2012, Autumn 2014, Autumn 2015, Autumn 2016, autumn 2017, Autumn 2018, Autumn 2019, Autumn 2020, autumn 2021, Autumn 2022.
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