PřF:Bi9127 Data evaluation in HUBI - Course Information
Bi9127 Data evaluation in Human BiologyFaculty of Science
- Extent and Intensity
- 0/2/0. 2 credit(s). Type of Completion: zk (examination).
- 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. Mgr. Tomáš Zeman, Ph.D.
Supplier department: Department of Experimental Biology - Biology Section - Faculty of Science
- Fri 8:00–11:50 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
- 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
- Teaching methods
- theoretical lectures, class discussion
- Assessment methods
- final project presentation
- Language of instruction
- Further Comments
- Study Materials
The course is taught annually.