BLKBS051c Biostatistics - practice

Faculty of Medicine
autumn 2019
Extent and Intensity
0/0. 1 credit(s). Type of Completion: z (credit).
Teacher(s)
prof. RNDr. Ladislav Dušek, Ph.D. (seminar tutor)
RNDr. Danka Haruštiaková, Ph.D. (seminar tutor)
RNDr. Jiří Jarkovský, Ph.D. (seminar tutor)
Guaranteed by
prof. RNDr. Ladislav Dušek, Ph.D.
Institute of Biostatistics and Analyses – Other Departments for Educational and Scientific Research Activities – Faculty of Medicine
Supplier department: Institute of Biostatistics and Analyses – Other Departments for Educational and Scientific Research Activities – Faculty of Medicine
Timetable
Mon 9. 9. 10:00–10:50 F01B1/709, Tue 10. 9. 13:00–14:40 F01B1/709, Wed 11. 9. 12:00–13:40 F01B1/709
Prerequisites
BLKZI0211 Computer Science - p.
Biostatistics - any theoretical course
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
The course is basic introduction into practical data analysis for students of biology and clinical study specialisations. The course accompanies lectures of BLKBS051 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 analysis, data visualisation).
Learning outcomes
Students will be able after the course to use the folowing data analysis methods:
- Descriptive statistics, data visualisation.
- Distribution of continuous variables.
- One sample tests - parametrical and nonparametrical.
- Two sample tests - parametrical and nonparametrical.
- Analysis of variance (ANOVA), Kruskal-Wallis test.
- Analysis of contingency table.
- Corelation, linear regression.
Syllabus
  • 1. Data processing – principles of correct data manipulation. MS Office Excel – appropriate tool for storing, organizing, and manipulating data.
  • 2. Introduction to statistics. Data types in medicine and biology; nominal, ordinal, continuous variable. Visualization of quantitative and qualitative (categorical) variables.
  • 3. Descriptive statistics. Mean, median, quantiles, variance. Frequency table.
  • 4. Distribution of continuous variables. Normal distribution, log-normal distribution.
  • 5. Principles of hypotheses testing. Definition of null and alternative hypothesis. Significance level. Type I and type II error.
  • 6. Graphical examining of normal distribution (histogram, normal-probability plot). Shapiro-Wilk test – a test of normality.
  • 7. Parametrical tests: t-tests. One-sample t-test, two-sample t-test, t-test for dependent samples.
  • 8. Analysis of variance ANOVA.
  • 9. Nonparametrical tests: one-sample Wilcoxon test, Mann-Whitney U test, Wilcoxon test for dependent samples, Kruskal-Wallis test.
  • 10. Definition of contingency table and its analysis: Pearson chi-square test, Fisher exact test, McNemar test.
  • 11. Correlation. Pearson correlation coefficient, Spearman correlation coefficient.
  • 12. Introduction to regression analysis. Linear regression.
Literature
  • Zar, J.H. (1994) Biostatistical methods. Prentice Hall, London. 2nd ed.
  • J. Benedík, L. Duąek (1993) Sbírka příkladů z biostatistiky. Nakladatelství KONVOJ, Brno.
  • G. W. Snedecor, W. G. Cochran (1971). Statistical methods. Iowa State University Press.
  • HAVRÁNEK, Tomáš. Statistika pro biologické a lékařské vědy. 1. vyd. Praha: Academia, 1993, 476 s. ISBN 8020000801. info
Teaching methods
Practical training using computers
Assessment methods
Individual project on correct application of statistical methods on example data
Language of instruction
Czech
Further comments (probably available only in Czech)
Study Materials
Information on the extent and intensity of the course: 5.
The course is also listed under the following terms Autumn 2011, Autumn 2012, Autumn 2013, Autumn 2014, Autumn 2015, Autumn 2016, Autumn 2017, autumn 2018.
  • Enrolment Statistics (recent)
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