Print syllabusStatystic in enviromental sciences
General data
| Course ID: | WF-OB-ZMI |
| Erasmus code / ISCED: |
07.2
|
| Course title: | Statystic in enviromental sciences |
| Name in Polish: | Statystyka w naukach o środowisku |
| Organizational unit: | Center for Ecology and Ecophilosophy |
| Course groups: |
(in Polish) Przedmioty obowiązkowe dla 1 roku Ochrony Środowiska |
| ECTS credit allocation (and other scores): |
0 OR
3.00
(depends on study program)
|
| Language: | Polish |
| Subject level: | elementary |
| Learning outcome code/codes: | OB1_W11 OB1_U06 OB1_K03 |
| Short description: |
The aim of the module is to familiarize the student with the statistical research methodology and to apply basic statistical methods during scientific research. Didactic methods used Lectures using multimedia presentations, Exercises data analysis in the form of solving statistical tasks, multimedia presentations Exercises end with a test on which the practical ability to solve a given statistical problem is tested. After passing the practical part, there is an exam. |
| Full description: |
The course is devoted to familiarizing with basic statistical methods. In the tutorial part, it will be implemented based on practical classes: • Descriptive statistics, including: familiarization with measuring scales, introduction to descriptive statistics, measures of central tendency and dispersion measures, and analysis of variability. • Analysis of sample distribution, measures of distribution asymmetry • Induction statistics, including: stages of scientific research, principles of formulating scientific goals, statistical hypotheses, verification of hypotheses, Type I and Type II errors. • parametric and nonparametric statistical methods (including student's t-tests, ANOVA, MNOVA, tests for fractions) • simple and multivariate regression analysis, Chi2 test, • Multivariate data analysis including: dendrogram analysis, cluster analysis and factor analysis In addition to knowledge about the use of these methods, emphasis will also be placed on the issue of conditions in which analyzes of a given type are allowed to be performed. Emphasis is also placed on the interpretation of results and methods of presenting the results of statistical analyzes. During the course, the student becomes familiar with statistical inference using appropriate statistical tests (Student's t-test, single and multivariate analysis of variance, Mann-Whitney test, Wilcoxon Kruskal Walis test, correlation and straight line regression, Chi 2 test). Performs simple research tasks or expert opinions typical of biological sciences under the supervision of a scientific supervisor. Uses statistical methods at the basic level to describe phenomena and analyze data. Is able to analyze statistical information from various sources and present correct conclusions. He can make the correct hypotheses based on logical premises. Uses basic statistical methods and computational techniques. Can carry out statistical tests. Correctly interprets empirical data and draws appropriate conclusions. |
| Bibliography: |
1. Byrkit DR, Statistics today – a comprahensive introduction. Cummings Publ. Comp. 1987. 2. Marek T, Analiza skupień w badaniach empirycznych – Metody SAHN. PWN, 1989. 3. Łomnicki A. Wprowadzenie do statystyki dla przyrodników, PWN, 2016 4. Blalock H., Statystyka dla socjologów, PWN, 1977. 5. Stanisz A. Biostatystyka, Wyd. UJ, 2005 |
| Efekty kształcenia i opis ECTS: |
In terms of knowledge: After completing the course, the student understands the importance of statistical and numerical methods for the description and interpretation of biological phenomena and processes. Uses basic statistical methods and IT techniques to describe phenomena and data analysis. Understands the importance of researching statistical methods in explaining the basis of biological processes. Demonstrates the ability to correctly reason based on data from various sources. In terms of skills: He can formulate statistical hypotheses and correctly construct a research problem and verify statistical hypotheses. Is able to plan and carry out research tasks under the guidance of a scientific supervisor. Uses statistical methods at the basic level to describe phenomena and analyze data. He can make the correct hypotheses based on logical premises Demonstrates the ability to solve statistical tasks and problems using appropriate statistical formulas. Uses basic statistical methods and computational techniques adequate to the scientific problems posed Is able to analyze information from various sources and present correct conclusions In terms of social competence: The student consistently applies and disseminates the principle of strict, based on empirical foundations, interpretation of biological phenomena and processes. Demonstrates criticism in receiving information related to biological sciences from scientific literature, the Internet, and especially available in mass media. Can be self-critical and draw conclusions based on an analysis of their skills, attitudes and actions |
| Assessment methods and assessment criteria: |
The exam is a single-choice test. Completion of exercises for the grade, colloquium / practical test. Learning outcomes are verified in the form of a written exam, which checks the understanding of the operation of statistical tools, the ability to correctly carry out statistical inference, as well as the assessment of such inference. The exam takes the form of a single-choice test and contains information provided during lectures. In order to complete the course the student should obtain at least 50% of the maximum number of points resulting from the test. The maximum number of points that can be obtained during the exam is variable (depending on the number of questions) and will be announced to students in each academic year |
Classes in period "Summer semester 2021/22" (past)
| Time span: | 2022-02-01 - 2022-06-30 |
 
MO TU W TH WYK
FR WYK
|
| Type of class: |
Lectures, 30 hours, 50 places
|
|
| Coordinators: | Krzysztof Szostek | |
| Group instructors: | Krzysztof Szostek | |
| Course homepage: | https://teams.microsoft.com/l/team/19%3att8jlCVoCfRMqQUgioOvhdXxh6SbDIBy3dN2_yjhuj81%40thread.tacv2/conversations?groupId=268016f4-3d45-4f54-8ff3-287d408ae0c2&tenantId=12578430-c51b-4816-8163-c7281035b9b3 | |
| Students list: | (inaccessible to you) | |
| Examination: |
Course -
examination
Lectures - examination |
|
| (in Polish) E-Learning: | (in Polish) E-Learning (pełny kurs) z podziałem na grupy |
|
| Short description: |
The aim of the module is to familiarize the student with the statistical research methodology and to apply basic statistical methods during scientific research. Didactic methods used Lectures using multimedia presentations, Exercises data analysis in the form of solving statistical tasks, multimedia presentations Exercises end with a test on which the practical ability to solve a given statistical problem is tested. After passing the practical part, there is an exam. |
|
| Full description: |
The course is devoted to familiarizing with basic statistical methods. In the tutorial part, it will be implemented based on practical classes: • Descriptive statistics, including: familiarization with measuring scales, introduction to descriptive statistics, measures of central tendency and dispersion measures, and analysis of variability. • Analysis of sample distribution, measures of distribution asymmetry • Induction statistics, including: stages of scientific research, principles of formulating scientific goals, statistical hypotheses, verification of hypotheses, Type I and Type II errors. • parametric and nonparametric statistical methods (including student's t-tests, ANOVA, MNOVA, tests for fractions) • simple and multivariate regression analysis, Chi2 test, • Multivariate data analysis including: dendrogram analysis, cluster analysis and factor analysis In addition to knowledge about the use of these methods, emphasis will also be placed on the issue of conditions in which analyzes of a given type are allowed to be performed. Emphasis is also placed on the interpretation of results and methods of presenting the results of statistical analyzes. During the course, the student becomes familiar with statistical inference using appropriate statistical tests (Student's t-test, single and multivariate analysis of variance, Mann-Whitney test, Wilcoxon Kruskal Walis test, correlation and straight line regression, Chi 2 test). Performs simple research tasks or expert opinions typical of biological sciences under the supervision of a scientific supervisor. Uses statistical methods at the basic level to describe phenomena and analyze data. Is able to analyze statistical information from various sources and present correct conclusions. He can make the correct hypotheses based on logical premises. Uses basic statistical methods and computational techniques. Can carry out statistical tests. Correctly interprets empirical data and draws appropriate conclusions. |
|
| Bibliography: |
1. Byrkit DR, Statistics today – a comprahensive introduction. Cummings Publ. Comp. 1987. 2. Marek T, Analiza skupień w badaniach empirycznych – Metody SAHN. PWN, 1989. 3. Łomnicki A. Wprowadzenie do statystyki dla przyrodników, PWN, 2016 4. Blalock H., Statystyka dla socjologów, PWN, 1977. 5. Stanisz A. Biostatystyka, Wyd. UJ, 2005 |
|
| Wymagania wstępne: |
The student should know the basics of mathematics and have basic knowledge in the field of population biology |
|
Classes in period "Summer semester 2022/23" (past)
| Time span: | 2023-02-01 - 2023-06-30 |
MO TU W TH WYK
FR WYK
|
| Type of class: |
Lectures, 30 hours, 50 places
|
|
| Coordinators: | Krzysztof Szostek | |
| Group instructors: | Krzysztof Szostek | |
| Course homepage: | https://teams.microsoft.com/l/team/19%3att8jlCVoCfRMqQUgioOvhdXxh6SbDIBy3dN2_yjhuj81%40thread.tacv2/conversations?groupId=268016f4-3d45-4f54-8ff3-287d408ae0c2&tenantId=12578430-c51b-4816-8163-c7281035b9b3 | |
| Students list: | (inaccessible to you) | |
| Examination: |
Course -
examination
Lectures - examination |
|
| (in Polish) E-Learning: | (in Polish) E-Learning (pełny kurs) z podziałem na grupy |
|
| Short description: |
The aim of the module is to familiarize the student with the statistical research methodology and to apply basic statistical methods during scientific research. Didactic methods used Lectures using multimedia presentations, Exercises data analysis in the form of solving statistical tasks, multimedia presentations Exercises end with a test on which the practical ability to solve a given statistical problem is tested. After passing the practical part, there is an exam. |
|
| Full description: |
The course is devoted to familiarizing with basic statistical methods. In the tutorial part, it will be implemented based on practical classes: • Descriptive statistics, including: familiarization with measuring scales, introduction to descriptive statistics, measures of central tendency and dispersion measures, and analysis of variability. • Analysis of sample distribution, measures of distribution asymmetry • Induction statistics, including: stages of scientific research, principles of formulating scientific goals, statistical hypotheses, verification of hypotheses, Type I and Type II errors. • parametric and nonparametric statistical methods (including student's t-tests, ANOVA, MNOVA, tests for fractions) • simple and multivariate regression analysis, Chi2 test, • Multivariate data analysis including: dendrogram analysis, cluster analysis and factor analysis In addition to knowledge about the use of these methods, emphasis will also be placed on the issue of conditions in which analyzes of a given type are allowed to be performed. Emphasis is also placed on the interpretation of results and methods of presenting the results of statistical analyzes. During the course, the student becomes familiar with statistical inference using appropriate statistical tests (Student's t-test, single and multivariate analysis of variance, Mann-Whitney test, Wilcoxon Kruskal Walis test, correlation and straight line regression, Chi 2 test). Performs simple research tasks or expert opinions typical of biological sciences under the supervision of a scientific supervisor. Uses statistical methods at the basic level to describe phenomena and analyze data. Is able to analyze statistical information from various sources and present correct conclusions. He can make the correct hypotheses based on logical premises. Uses basic statistical methods and computational techniques. Can carry out statistical tests. Correctly interprets empirical data and draws appropriate conclusions. |
|
| Bibliography: |
1. Byrkit DR, Statistics today – a comprahensive introduction. Cummings Publ. Comp. 1987. 2. Marek T, Analiza skupień w badaniach empirycznych – Metody SAHN. PWN, 1989. 3. Łomnicki A. Wprowadzenie do statystyki dla przyrodników, PWN, 2016 4. Blalock H., Statystyka dla socjologów, PWN, 1977. 5. Stanisz A. Biostatystyka, Wyd. UJ, 2005 |
|
| Wymagania wstępne: |
The student should know the basics of mathematics and have basic knowledge in the field of population biology |
|
Classes in period "Summer semester 2023/24" (in progress)
| Time span: | 2024-02-15 - 2024-06-30 |
MO TU W TH WYK
FR WYK
|
| Type of class: |
Lectures, 30 hours, 50 places
|
|
| Coordinators: | Krzysztof Szostek | |
| Group instructors: | Krzysztof Szostek | |
| Course homepage: | https://teams.microsoft.com/l/team/19%3att8jlCVoCfRMqQUgioOvhdXxh6SbDIBy3dN2_yjhuj81%40thread.tacv2/conversations?groupId=268016f4-3d45-4f54-8ff3-287d408ae0c2&tenantId=12578430-c51b-4816-8163-c7281035b9b3 | |
| Students list: | (inaccessible to you) | |
| Examination: |
Course -
examination
Lectures - examination |
|
| (in Polish) E-Learning: | (in Polish) E-Learning (pełny kurs) z podziałem na grupy |
|
| Type of subject: | obligatory |
|
| (in Polish) Grupa przedmiotów ogólnouczenianych: | (in Polish) nie dotyczy |
|
| Short description: |
The aim of the module is to familiarize the student with the statistical research methodology and to apply basic statistical methods during scientific research. Didactic methods used Lectures using multimedia presentations, Exercises data analysis in the form of solving statistical tasks, multimedia presentations Exercises end with a test on which the practical ability to solve a given statistical problem is tested. After passing the practical part, there is an exam. |
|
| Full description: |
The course is devoted to familiarizing with basic statistical methods. In the tutorial part, it will be implemented based on practical classes: • Descriptive statistics, including: familiarization with measuring scales, introduction to descriptive statistics, measures of central tendency and dispersion measures, and analysis of variability. • Analysis of sample distribution, measures of distribution asymmetry • Induction statistics, including: stages of scientific research, principles of formulating scientific goals, statistical hypotheses, verification of hypotheses, Type I and Type II errors. • parametric and nonparametric statistical methods (including student's t-tests, ANOVA, MNOVA, tests for fractions) • simple and multivariate regression analysis, Chi2 test, • Multivariate data analysis including: dendrogram analysis, cluster analysis and factor analysis In addition to knowledge about the use of these methods, emphasis will also be placed on the issue of conditions in which analyzes of a given type are allowed to be performed. Emphasis is also placed on the interpretation of results and methods of presenting the results of statistical analyzes. During the course, the student becomes familiar with statistical inference using appropriate statistical tests (Student's t-test, single and multivariate analysis of variance, Mann-Whitney test, Wilcoxon Kruskal Walis test, correlation and straight line regression, Chi 2 test). Performs simple research tasks or expert opinions typical of biological sciences under the supervision of a scientific supervisor. Uses statistical methods at the basic level to describe phenomena and analyze data. Is able to analyze statistical information from various sources and present correct conclusions. He can make the correct hypotheses based on logical premises. Uses basic statistical methods and computational techniques. Can carry out statistical tests. Correctly interprets empirical data and draws appropriate conclusions. |
|
| Bibliography: |
1. Byrkit DR, Statistics today – a comprahensive introduction. Cummings Publ. Comp. 1987. 2. Marek T, Analiza skupień w badaniach empirycznych – Metody SAHN. PWN, 1989. 3. Łomnicki A. Wprowadzenie do statystyki dla przyrodników, PWN, 2016 4. Blalock H., Statystyka dla socjologów, PWN, 1977. 5. Stanisz A. Biostatystyka, Wyd. UJ, 2005 |
|
| Wymagania wstępne: |
The student should know the basics of mathematics and have basic knowledge in the field of population biology |
|
Copyright by Cardinal Stefan Wyszynski University in Warsaw.
