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PřF:Bi5040c Biostatistics - practices - Course Information

## Bi5040c Biostatistics - practices

**Faculty of Science**

Autumn 2019

**Extent and Intensity**- 0/1/0. 1 credit(s) (fasci plus compl plus > 4). Type of Completion: z (credit).
**Teacher(s)**- Mgr. Klára Benešová (seminar tutor)

prof. RNDr. Ladislav Dušek, Ph.D. (seminar tutor)

RNDr. Danka Haruštiaková, Ph.D. (seminar tutor)

Mgr. Renata Chloupková (seminar tutor)

RNDr. Jiří Jarkovský, Ph.D. (seminar tutor)

Mgr. Ivana Katinová (seminar tutor)

RNDr. Denisa Krejčí (seminar tutor)

RNDr. Jan Mužík, Ph.D. (seminar tutor)

RNDr. Tereza Nečasová (seminar tutor)

Mgr. Ondřej Ngo (seminar tutor)

RNDr. Lucie Pehalová (seminar tutor)

RNDr. Michal Svoboda (seminar tutor)

Mgr. Jan Švancara (seminar tutor)

Mgr. Michal Uher (seminar tutor) **Guaranteed by**- prof. RNDr. Ladislav Dušek, Ph.D.

RECETOX - Faculty of Science

Contact Person: RNDr. Jiří Jarkovský, Ph.D.

Supplier department: RECETOX - Faculty of Science **Timetable of Seminar Groups**- Bi5040c/02_1: Thu 10:00–11:50 D29/347-RCX2,
*J. Jarkovský*

Bi5040c/02_2: Thu 10:00–11:50 D29/347-RCX2,*J. Jarkovský*

Bi5040c/03_ct14_16: No timetable has been entered into IS.

Bi5040c/04_ct14_16: No timetable has been entered into IS. **Prerequisites**- NOW (
**Bi5040**Biostatistics - basic course )

Bi5040 Biostatistics in the same semester. **Course Enrolment Limitations**- The course is also offered to the students of the fields other than those the course is directly associated with.
**fields of study / plans the course is directly associated with**- there are 7 fields of study the course is directly associated with, display
**Course objectives**- The course is basic introduction into practical data analysis for students of biology and clinical study specialisations. The course accompanies lectures of Bi5040 Biostatistics and shows the computation of presented methods on PC using statistical software (descriptive statistics, one sample and two sample tests, categorical data analysis, ANOVA, correlation and regression analysis, data visualisation, basics of experimental design).
**Learning outcomes**- The students will be able after the course to use the folowing data analysis methods:

Descriptive statistics, data visualisation.

Tables of distribution functions.

Introduction to sampling design and experimental design.

Distribution of continuous and bivariate variables.

Application of binomial distribution in biology.

One sample testing.

Two sample testing.

Application of goodness-of-fit test in biology.

Analysis of variance (ANOVA), non - parametric ANOVA.

Corelation, linear regression. **Syllabus**- Introduction to statistics, testing of hypotheses.
- Tables of distribution functions. Sampling from biological populations, data processing.
- Introduction to sampling design. Continuous, ordinal and nominal data in biology.
- Distribution of continuous and bivariate variables - testing of hypotheses, graphical methods.
- Application of binomial distribution in biology.
- One sample testing: sample mean, median, standard deviation, variance, binomial p.
- Two sample testing. Parametric and non - parametric methods.
- Application of goodness-of-fit test in biology, analysis of R x C contingency tables, discrimination of categorical data.
- Covariance, correlation coefficients.
- Analysis of variance (ANOVA), non-parametric ANOVA alternatives.
- Linear regression.

**Literature**- Petrie, A., Watson, P. (2006) Statistics for Veterinary and Animal Science, Wiley-Blackwell; 2nd ed
- Zar, J.H. (1998) Biostatistical analysis. Prentice Hall, London. 4th ed.
- Sokal, R.R., Rohlf, F.J. (1994) Biometry, W. H. Freeman, 3th ed.

*recommended literature***Teaching methods**- Practical training using computers
**Assessment methods**- Exam on computers based on correct application of statistical methods on example data.
**Language of instruction**- Czech
**Further Comments**- Study Materials

- Enrolment Statistics (Autumn 2019, recent)
- Permalink: https://is.muni.cz/course/sci/autumn2019/Bi5040c