1. Preparation of sampling plan, storage of biological data.
2. Types of biological data - quantitative and qualitative data, description, measures of location and variability, visualization, identification of outliers.
3. Random variable and probability distribution (normal, standardized normal) and their applications in biology and ecology.
4. Other types of distributions (binomial, Poisson) and their applications in biology and ecology).
5. Introduction to hypothesis testing - null and alternative hypothesis, type I. and II. errors, statistical test and its strength, p - value.
6. The problem of multiple hypothesis testing in biology and ecology and correction procedures.
7. One-sample tests - parametric and nonparametric methods.
8. Comparison of parameters of two sample populations - parametric and nonparametric methods.
9. Analysis of variance (ANOVA) - evaluation of variance of biological and ecological data, evaluation of normality, Kruskal - Wallis test - nonparametric alternative ANOVA.
10. Correlation analysis - Pearson's and Spearman's correlation coefficient, similarity measures in ecology (similarity coefficients, correlation coefficients, covariance).
11. Regression analysis - linear regression, assumptions of linear model, estimation of regression model parameters, detemination coefficient, basic statistical tests.
12. Regression analysis - polynomial regression, basic statistical tests, residue analysis.
13. Introduction to multiple linear regression - types of variable interactions, multicollinearity, the problem of missing data, applications to biological and ecological data.
2. Types of biological data - quantitative and qualitative data, description, measures of location and variability, visualization, identification of outliers.
3. Random variable and probability distribution (normal, standardized normal) and their applications in biology and ecology.
4. Other types of distributions (binomial, Poisson) and their applications in biology and ecology).
5. Introduction to hypothesis testing - null and alternative hypothesis, type I. and II. errors, statistical test and its strength, p - value.
6. The problem of multiple hypothesis testing in biology and ecology and correction procedures.
7. One-sample tests - parametric and nonparametric methods.
8. Comparison of parameters of two sample populations - parametric and nonparametric methods.
9. Analysis of variance (ANOVA) - evaluation of variance of biological and ecological data, evaluation of normality, Kruskal - Wallis test - nonparametric alternative ANOVA.
10. Correlation analysis - Pearson's and Spearman's correlation coefficient, similarity measures in ecology (similarity coefficients, correlation coefficients, covariance).
11. Regression analysis - linear regression, assumptions of linear model, estimation of regression model parameters, detemination coefficient, basic statistical tests.
12. Regression analysis - polynomial regression, basic statistical tests, residue analysis.
13. Introduction to multiple linear regression - types of variable interactions, multicollinearity, the problem of missing data, applications to biological and ecological data.