546-0169/01 – Basics of Environmental Data Processing (ZZED)
| Gurantor department | Department of Environmental Engineering | Credits | 3 |
| Subject guarantor | Mgr. Oldřich Motyka, Ph.D. | Subject version guarantor | Mgr. Oldřich Motyka, Ph.D. |
| Study level | undergraduate or graduate | Requirement | Compulsory |
| Year | 2 | Semester | winter |
| | Study language | Czech |
| Year of introduction | 2021/2022 | Year of cancellation | |
| Intended for the faculties | HGF | Intended for study types | Bachelor |
Subject aims expressed by acquired skills and competences
Students will be able to analyze and evaluate quantitative, semi-quantitative and qualitative biological data. They will be able to correctly describe and visualize these data using the basic characteristics of descriptive statistics, identify and verify erroneous and outliers and the distribution from which the biological data come. They will also be able to formulate a statistical hypothesis, use appropriate test statistics and correctly interpret the results. They will also gain basic skills in correlation and regression analysis of biological data.
Teaching methods
Tutorials
Summary
Students will be acquainted with the basic methods of preparation of a sampling plan, collection, standartization/tranformation and evaluation of biological data. They will learn to use and interpret basic statistical methods with regard to the specifics of biological data. They will also get acquainted with the basics of biostatistical models and statistical evaluation of diversity. Working with data will be using MS Excel tools and R program and its libraries.
Compulsory literature:
Recommended literature:
Way of continuous check of knowledge in the course of semester
Active participation in exercises. Processing and submission of assigned protocols.
Semester work.
E-learning
Submission of assigned protocols.
Semester work.
Other requirements
participation in exercises
project - data evaluation
credit test
Prerequisities
Subject has no prerequisities.
Co-requisities
Subject has no co-requisities.
Subject syllabus:
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.
Conditions for subject completion
Occurrence in study plans
Occurrence in special blocks
Assessment of instruction