BOT/BST Biostatistics
Lecturer: Martin Duchoslav
Lecture: 2 hours/week + exercise 2 hours/week
Credits: 4
Winter semester
Form of course completion: exam
Lectures are focusing on the explanation of principles of statistical methods and correct interpretation of the results of statistical tests. The course absolvents should be able correctly (i) design the observations or experiments, (ii) collect, analyze and interpret data for the purposes of their theses, and (iii) understand statistical methods and results appearing in scientific literature. How the test works is illustrated on real data. Computer exercises with statistical software are integral parts of the course.
Lessons
- Introduction, what is science, methodology, philosophy of science, deduction, induction
- Population and sample, sampling design, types of variables, observations and experiments, descriptive and exploratory statistics
- Probability, principles of hypothesis testing, theoretical and empirical distributions
- Analyses of categorical data (chi-square, contingency tables, Fisher exact test, odds ratios, log-linear models)
- Analyses of ordinal and quantitative data I: one and two samples, parametric and non-parametric tests (Monte Carlo), random and block designs, data transformation
- Analyses of ordinal and quantitative data II: three and more samples, ANOVA: one-way, multifactor, with randomized blocks, with repeated measurements, nested
- Relationships between quantitative variables: regression and correlation, linear and non-linear models, ANCOVA
