Content (Syllabus outline)

• Introduction: use of statistics in biology.
• Introduction to statistical analysis system R.
• Sampling and design of experiments.
• Confidence intervals. Simple random sampling. Randomization. Other sampling techniques. Factorial experiments.
• Hypothesis testing.
• Testing hypotheses about the mean and variance. Type I and Type II errors. Nonparametric tests. Randomization tests.
• Bivariate relationships. Linear and generalized linear model. Analysis of variance. Linear correlation and regression. Nonlinear regression. Association and contingency. Logistic regression.
• Overview of multivariate methods: Multiple and multivariate regression, principal component analysis, Multivariate analysis of variance, discriminant analysis, factor analysis, cluster analysis.


Prerequisites for inclusion in the work:
- enrolment in the appropriate academic year

Recommended knowledge of mathematics and statistics.