LF:MNBS081c Biostatistics - Course Information

MNBS081c Biostatistics - practice

Extent and Intensity

0/1/0. 1 credit(s). Type of Completion: z (credit).

Teacher(s)

prof. RNDr. Ladislav Dušek, Ph.D. (lecturer)
RNDr. Jiří Jarkovský, Ph.D. (lecturer)
RNDr. Jan Mužík, Ph.D. (seminar tutor)
RNDr. Danka Haruštiaková, Ph.D. (seminar tutor)
Mgr. Jan Švancara (lecturer)
MVDr. Halina Matějová (assistant)

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

Tue 2. 3. 14:00–15:40 F01B1/709, Tue 9. 3. 14:00–15:40 F01B1/709, Tue 16. 3. 14:00–15:40 F01B1/709, Tue 23. 3. 14:00–15:40 F01B1/709, Tue 30. 3. 14:00–15:40 F01B1/709, Tue 6. 4. 14:00–15:40 F01B1/709, Tue 13. 4. 14:00–15:40 F01B1/709, Tue 20. 4. 14:00–15:40 F01B1/709, Tue 27. 4. 14:00–15:40 F01B1/709, Tue 4. 5. 14:00–15:40 F01B1/709, Tue 11. 5. 14:00–15:40 F01B1/709, Tue 18. 5. 14:00–15:40 F01B1/709, Tue 25. 5. 14:00–15:40 F01B1/709, Tue 1. 6. 14:00–15:40 F01B1/709, Tue 8. 6. 14:00–15:40 F01B1/709

Prerequisites

none - basic 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

• Nutrition therapist for child nutrition and Nutrition therapist for adult nutrition (programme LF, N-SZ)

Course objectives

The course is basic introduction into practical data analysis. The course accompanies lectures of MNBS081 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.

Teaching methods

drills

Assessment methods

active participation in the course

Language of instruction

Czech

Follow-Up Courses

• MNDP0932 Diploma Thesis II

Further comments (probably available only in Czech)

Study Materials
The course is taught annually.
Information on the extent and intensity of the course: 15.

• Enrolment Statistics (spring 2021, recent)
  
• Permalink: https://is.muni.cz/course/med/spring2021/MNBS081c