# PřF:Bi9127 Data evaluation in HUBI - Course Information

## Bi9127 Data evaluation in Human Biology

**Faculty of Science**

autumn 2021

**Extent and Intensity**- 0/2/0. 2 credit(s). Type of Completion: zk (examination).

Taught online. **Teacher(s)**- Mgr. Kateřina Dadáková, Ph.D. (lecturer)

doc. RNDr. Eva Drozdová, Ph.D. (lecturer)

doc. Mgr. Tomáš Zeman, Ph.D. (lecturer) **Guaranteed by**- doc. RNDr. Eva Drozdová, Ph.D.

Department of Experimental Biology - Biology Section - Faculty of Science

Contact Person: doc. RNDr. Eva Drozdová, Ph.D.

Supplier department: Department of Experimental Biology - Biology Section - Faculty of Science **Timetable**- Thu 17:00–18:50 D36/347
**Course Enrolment Limitations**- The course is only offered to the students of the study fields the course is directly associated with.

**fields of study / plans the course is directly associated with**- there are 10 fields of study the course is directly associated with, display
**Course objectives**- Students will get acquainted with basic statistical methods for evaluation of experimental data in human biology and will learn to use them on real data.
**Learning outcomes**- Student will be able to:

- to choose appropriate statistical methods for evaluating specific experimental data in human biology;

- interpret the results of statistical evaluation of the data **Syllabus**- 1) basic terms: types of data (nominal scale, ordinal scale, interval scale, and ratio scale), descriptive statistics, definition of probability, principle of statistical hypothesis testing, statistical software
- 2) probability distribution: discrete and continuous distribution, qualitative and quantitative data, examples of discrete distributions, examples of continuous distributions, basic characteristics of data
- 3) data visualization: scatter plot, histogram, box plot, outliers
- 4) statistical evaluation of qualitative data: contingency table, Chi-squared test, Fisher's exact test, Odds Ratio (OR), Risk Ratio (RR)
- 5) statistical evaluation of association study: types of association studies, selection of date for association study, statistical evaluation of genome-wide association studies (GWAS), problem of multiple comparisons: Bonferroni correction
- 6) determination of measurement error in qualitative data: inter-observer error, intra-observer error, kappa coefficient
- 7) parametric tests for statistical evaluation of quantitative data: normality tests, unpaired t-test, paired t-test, F-test of equality variances, ANOVA, post-hoc tests
- 8) nonparametric tests for statistical evaluation of quantitative data: Sign test, Wilcoxon test, Mann-Whitney test, ANOVA, Kruskal-Wallis test
- 9) relative gene expression analysis: calculation of relative gene expression, selection of a suitable test
- 10) correlation analysis: Pearson' correlation coefficient, Spearman's rank correlation coefficient, basics of linear regression, linkage disequilibrium
- 11) determination of measurement error in quantitative data: TEM, reliability coefficient
- 12) estimation of relatedness: Bayes' theorem, conditional probability, principle of paternity testing based on DNA

**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

*recommended literature*- BUDÍKOVÁ, Marie, Maria KRÁLOVÁ and Bohumil MAROŠ.
**Teaching methods**- theoretical lectures, class discussion
**Assessment methods**- final project presentation
**Language of instruction**- Czech
**Further Comments**- Study Materials

The course is taught annually.

- Enrolment Statistics (autumn 2021, recent)
- Permalink: https://is.muni.cz/course/sci/autumn2021/Bi9127