MAS10c Applied statistics I - exercises

Faculty of Science
Autumn 2019
Extent and Intensity
0/2/0. 2 credit(s) (příf plus uk k 1 zk 2 plus 1 > 4). Type of Completion: z (credit).
Teacher(s)
Mgr. Veronika Horská, Ph.D. (seminar tutor), doc. PaedDr. RNDr. Stanislav Katina, Ph.D. (deputy)
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
Timetable of Seminar Groups
MAS10c/01: Mon 17:00–18:50 MP2,01014a, V. Horská
MAS10c/02: Mon 14:00–15:50 MP2,01014a, V. Horská
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: 0/20
fields of study / plans the course is directly associated with
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) Descriptive statistics, absolute frequency, relative frequency, conditional relative frequency
  • 2) Descriptive statistics, sample mean, variance and standard deviation
  • 3) Types of data, nominal scale, ordinal scale, interval scale, ratio scale
  • 4) Probability, conditional probability, 1. Bayes formula
  • 5) Binomial distribution, Poisson distribution
  • 6) Normal distribution, statistical tables
  • 7) T-test, F-test, hypotheses testing
  • 8) Normality tests, Kolmogorov-Smirnov test, Lilliefors test
  • 9) Sign test, Wilcoxon test, Kolmogorov-Smirnov test
  • 10) Contingency table, Fisher exact test, Chi-squared test
  • 11) Pearson correlation coefficient, Spearman rank correlation coefficient
  • 12) Pearson correlation coefficient, linear regression
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
exercises, 2 hours a week, in the first hour examples are calculated, second hour is devouted to the work with statistical software R.
Assessment methods
Credit will be granted after gaining at least 75% of the possible points from homework. Students can use arbitrary study materials. It is not allowed to copy code from collegues. 3 absences are allowed.
Language of instruction
Czech
Further comments (probably available only in Czech)
Study Materials
The course is taught annually.
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 2020, autumn 2021, Autumn 2022, Autumn 2023, Autumn 2024.
  • Enrolment Statistics (Autumn 2019, recent)
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