Statystic in enviromental sciences WF-OB-ZMI

Topic/class block and number of hours
1. Introduction to descriptive statistics, selection of research samples, familiarization with measurement scales. 2 hours
2. Frequency distributions and graphical presentation of frequency distributions. 2 hours
3. Measures of central tendency, conditions of use (mean, median, mode). 2 hours
4. Measures of dispersion and analysis of variability (standard deviation, partial deviation, variance, coefficient of variation) 2 hours
5. analysis of sample distribution, measures of distribution asymmetry
outliers, Fisher-Snedecor test for equality of variance 2 hours.
6. introduction to inductive statistics, stages of scientific research, principles of formulating scientific objectives, statistical hypotheses, hypothesis verification, Type I and Type II errors. 2 hours
7. Conditions for the use of parametric tests, analysis of outliers, Fisher-Snedecor test for equality of variances 2 hours
8. Parametric statistical methods, including Student's t-tests for large and small groups, Student's t-test for paired samples. 2 hours
9. One-way analysis of variance (ANOVA). 2 hours.
10. tests for fractions. 2 hours.
11. multi-field and four-field Chi2 tests. 2 hours.
12. non-parametric tests, including the Kruskal-Wallis test. 2 hours.
13. Multivariate data analysis, including: dendrogram analysis, cluster analysis, and factor analysis. 2 hours
14. Simple and multivariate regression analysis. 2 hours
15. Correlation analysis 2 hours
Total hours: 30

Term 2023/24_L:

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.

Term 2024/25_L:

Term 2025/26_L:

(in Polish) E-Learning

(in Polish) E-Learning (pełny kurs) z podziałem na grupy

(in Polish) Grupa przedmiotów ogólnouczenianych

(in Polish) nie dotyczy

(in Polish) Opis nakładu pracy studenta w ECTS

Term 2021/22_L:

ECTS 4 task 1: active participation in classes- 30h task 2: preparation for the exam - 60h assignment 3: own work - 25h

Term 2022/23_L:

ECTS 4 task 1: active participation in classes- 30h task 2: preparation for the exam - 60h assignment 3: own work - 25h

Term 2024/25_L:

ECTS 4 task 1: active participation in classes- 30h task 2: preparation for the exam - 60h assignment 3: own work - 25h

Term 2023/24_L:

ECTS 4 task 1: active participation in classes- 30h task 2: preparation for the exam - 60h assignment 3: own work - 25h

Term 2025/26_L:

Description of student workload in ECTS 1. Direct contact with the lecturer - participation in classes - 30 hours, participation in assessments outside of classes - 2 hours. 2. Independent work - preparation for classes - reading literature and listening to lecture notes - 10 hours, preparation for the exam - 20 hours. Total: 62 hours/2 ECTS

Subject level

elementary

Learning outcome code/codes

Informacje o zajęciach w cyklu 2026/26_L OB1_W05, OB1_W08, OB1_U05, OB1_U06, OB1_K02 Stare informacje o zajęciachOB1_W06 OB1_W10 OB1_U01 OB1_U06 OB1_U07 OB1_U08 OB1_K05

Type of subject

obligatory

Course coordinators

Krzysztof Szostek

Learning outcomes

Learning outcomes:
W_01 The student explains the main concepts of statistics and selects appropriate statistical tests for a scientific problem. Course topics: (1, 6).
Methods of verifying learning outcomes - Written exam

W_02 The student verifies statistical hypotheses. The student correctly explains the results of the analyses and applies statistical inference. The student correctly performs and interprets statistical tests and describes population phenomena. Course topics: (2, 3, 4, 5, 7, 8, 9, 10, 11, 12, 13, 14, 15).
Methods of verifying learning outcomes - Written exam
U_01 The student explains the results of analyses and applies statistical inference.
Class topics: (1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15)
Methods of verifying learning outcomes - Written exam

U_02 The student formulates and verifies statistical hypotheses. Course topics: (6).
Methods of verifying learning outcomes - Written exam
K_01 The student critically diagnoses statistical errors in scientific research and presents reliable research results. Course topics: (3, 6, 14, 15).
Methods of verifying learning outcomes - Written exam.

Learning outcomes:
W_01 Graduates are familiar with the main conceptual categories and terminology in the field of natural sciences and the development of these disciplines and the research methods used in them (OB1_W05)
W_02 Graduates are familiar with mathematical and statistical tools at a level sufficient to describe natural phenomena (OB1_W08)
U_01 The graduate is able to interpret observations and measurements and draw correct conclusions based on them (OB1_U05)
U_02 The graduate is able to make correct hypotheses about the causes of situations/threats that have arisen (OB1_U06)
K_01 Graduates are prepared to exercise caution and critical thinking when accepting information provided by the mass media concerning environmental protection (OB1_K02)

Assessment criteria

Graded exam (test). In order to pass the course, students must obtain at least 50% of the maximum number of points available in the test.
The exam takes the form of a single-choice test and covers information provided during lectures, mp4 presentations, and PDF study aids.
Two absences are permitted. Make-up work is arranged with the instructor. Cases of prolonged illness will be considered on an individual basis.

Grading criteria based on the final exam:
very good 86-100%
good plus 80-85%
good 71-79%
sufficient plus 60-70%
sufficient 51%-59%

Bibliography

The lecturer provides assistance in selecting literature
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
6. Szostek K., i inni. 2005. Metody opracowania i prezentacji wyników. [w:] Dziecko Żywieckie, K. Kaczanowski (ed.), Wyd. PiT Kraków. pp. 17-19.

Term 2023/24_L:

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
6. Szostek K., i inni. 2005. Metody opracowania i prezentacji wyników. [w:] Dziecko Żywieckie, K. Kaczanowski (ed.), Wyd. PiT Kraków. pp. 17-19.

Term 2024/25_L:

Term 2025/26_L:

Notes

Term 2023/24_L:

The student should know the basics of mathematics and have basic knowledge in the field of population biology

Term 2024/25_L:

The student should know the basics of mathematics and have basic knowledge in the field of population biology

Additional information

Information on level of this course, year of study and semester when the course unit is delivered, types and amount of class hours - can be found in course structure diagrams of apropriate study programmes. This course is related to the following study programmes:

Environmental Protection - full-time first cycle studies

Additional information (registration calendar, class conductors, localization and schedules of classes), might be available in the USOSweb system:

Description of WF-OB-ZMI in USOSweb