## Bi5560 Basics of statistics for biologists

Faculty of Science
autumn 2021
Extent and Intensity
2/1/0. 3 credit(s) (plus extra credits for completion). Type of Completion: zk (examination).
Taught in person.
Teacher(s)
Mgr. Kateřina Kintrová, Ph.D. (lecturer)
prof. Mgr. Stanislav Pekár, Ph.D. (lecturer)
Guaranteed by
prof. Mgr. Stanislav Pekár, Ph.D.
Department of Botany and Zoology - Biology Section - Faculty of Science
Contact Person: Mgr. Kateřina Kintrová, Ph.D.
Supplier department: Department of Botany and Zoology - Biology Section - Faculty of Science
Timetable of Seminar Groups
Bi5560/01: Tue 9:00–10:50 B09/316, Tue 13:00–14:50 B09/316, K. Kintrová
Bi5560/02: Tue 10:00–11:50 B09/316, Tue 14:00–15:50 B09/316, K. Kintrová
Prerequisites
Bi7560 Introduction to R || SOUHLAS
This course is taught in the Czech language and because of the large extent of course content it is not possible to accept English-speaking students.
Course Enrolment Limitations
The course is also offered to the students of the fields other than those the course is directly associated with.
The capacity limit for the course is 40 student(s).
Current registration and enrolment status: enrolled: 29/40, only registered: 1/40, only registered with preference (fields directly associated with the programme): 1/40
fields of study / plans the course is directly associated with
Course objectives
The aim is to teach students basic statistical methods for the analysis of their own data.
Learning outcomes
Students will be able to: - define explanatory and response variables - define statistical hypothesis - visualise data and parameter estimates - select appropriate statistical method for analysis of their data - interpret results
Syllabus
• 1. Introduction: basic characteristics of data, stochastic variable; 2. Estimation of sample parameters, some of the probability distributions; 3. Statistical hypotheses; 4. Tests of assumptions, parametric and non-parametric methods; 5. One-sample tests; 6. Two-sample tests; 7. Several-sample tests, ANOVA; 8. Correlation; 9. Linear regression; 10. Chi-square tests, contingency tables.
Literature
recommended literature
• ZVÁRA, Karel. Základy statistiky v prostředí R. 1. vyd. Praha: Karolinum, 2013. 259 s. ISBN 9788024622453. info
• LEPŠ, Jan and Petr ŠMILAUER. Biostatistika. Vydání 1. České Budějovice: Nakladatelství Jihočeské univerzity v Českých Budějovicích, 2016. 438 stran. ISBN 9788073945879. info
not specified
• CRAWLEY, Michael J. Statistics : an introduction using R. Chichester: John Wiley & Sons, 2005. xiii, 327. ISBN 0470022973. info
• SOKAL, Robert R. and F. James ROHLF. Biometry : the principles and practice of statistics in biological research. 4th ed. New York, N.Y.: W.H. Freeman and Company, 2012. xix, 937. ISBN 9780716786047. info
• ZAR, Jerrold H. Biostatistical analysis. Fifth edition. Uttar Pradesh, India: Pearson India Education Services, 2014. 756 stran. ISBN 9789332536678. info
Teaching methods
Lectures, commentated examples; practical processing of data in software R, homework.
Assessment methods
Oral examination. Homeworks given during the semester to exercise covered topic. Examination will be conceived as a personal interview over these homeworks to confirm that the student understands the methods.
Language of instruction
Czech
Further comments (probably available only in Czech)
Study Materials
The course is taught annually.
Listed among pre-requisites of other courses
Teacher's information
The interactive curriculum is in preparation on IS MUNI.
The course is also listed under the following terms Autumn 2018, Autumn 2019, Autumn 2020.
• Enrolment Statistics (recent)