Czech

Not applicable.

Faculty of Medicine, Masaryk University Brno (LF MU)

After completing the course the student is able to:
• apply descriptive statistics on the given data
• select and use tools to test hypotheses
• graphically present statistical data
• clinical studies suggest
• work with databases and statistical programs

Knowledge at the secondary school level of mathematics, PC, work with MS Office, particularly MS Excel is required.

Not applicable.

Teaching methods depend on the type of course unit as specified in the article 7 of BUT Rules for Studies and Examinations.

Compliance with the requirements for terminating exercise: participation in seminar, final exam for more than 50% points.
Written exam for more than 40% of the points.
The final exam is focused on understanding of statistical data analysis and their applications.

1. Introduction to statistics, hypothesis testing. Stochastic distribution, distribution function, frequency tables, percentiles. Tables of model distribution. Withdrawals from biological populations, data processing. Introduction to planning choices.
2. Continuous, ordinal and nominal data in biology. Estimates of selection parameters. The percentages and indices as derived biological data.
3. The distribution of continuous variables - testing hypotheses, graphical methods. The distribution of binary variables - testing hypotheses, graphical methods.
4. One-sample tests. Testing hypotheses about population parameters selection: sample mean, median, standard deviation, variance. Sampling and experimental design to test the parameters of the selection populations.
5. Application of binomial and Poisson distribution in biology, modeling using the binomial distribution. One-sample tests of binomial parameter pa Poisson's constant.
6. Comparing the two selection parameters populations. Experimental plans - a completely randomized pair. Parametric and nonparametric methods. Formal presentation of the comparison of two sample populations in the literature. Graphical methods.
7. The analysis of binary and ordinal data. Goodness: genetics, molecular biology, ecology. Analysis of R x C contingency tables, discrimination of categorical data. Binomial test and a test of homogeneity of binomial frequency.
8. Correlation analysis. Parametric and serial correlation (covariance, correlation coefficients, coefficients of similarity). Correlation and covariance matrix. Partial correlations.
9. Analysis of variance (ANOVA) models a simple classification for experimental and ecological data. Non-parametric methods of analysis of variance.
10. Way classification ANOVA, testing the interaction of one or more experimental interventions, formal presentation of the results of analysis of variance.
11. Introduction to regression analysis. Regression analysis of the line. Analysis of variance in the regression analysis line. Linear regression. Residual analysis of regression models.

Not applicable.

To provide the students with sufficient knowledge for clinical data acquisition, organisation and statistical analysis including presentation and interpretation of outcomes

Participation in seminar is mandatory, two absences are permitted. In the case of multiple absences, it is possible to substitute the seminar after the agreement with teacher (ideally in another parallel group).

Not applicable.

Not applicable.

ALTMAN, Douglas. Practical statistics for medical research. London: Chapman and Hall, 1991. ISBN 0412276305. (EN)
HAVRÁNEK, Tomáš. Statistika pro biologické a lékařské vědy. 1. vyd. Praha: Academia, 1993. ISBN 80-200-0080-1. (CS)

Not applicable.