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).
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
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
    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
Teaching methods
theoretical lectures, class discussion
Assessment methods
final project presentation
Language of instruction
Czech
Further Comments
Study Materials
The course is taught annually.
The course is also listed under the following terms Autumn 2019, Autumn 2020, Autumn 2022, Autumn 2023, Autumn 2024.
  • Enrolment Statistics (autumn 2021, recent)
  • Permalink: https://is.muni.cz/course/sci/autumn2021/Bi9127