Informatics 2 - using of statistical methods in enviromental sciences WF-OB-INFO2

Topic/block of classes and number of hours
1. Introductory classes on basic conceptual categories of descriptive statistics and terminology in the field of natural sciences/statistics 2 hours
2. Creating distribution series and graphical representation of the structure of a distribution series (histograms and polygons of frequency). 2 hours
3. Calculating basic statistics from distribution series in the form of measures of central tendency and measures of dispersion (arithmetic mean using the accumulation and deviation method). 2 hours
4. Calculating basic statistics from distribution series in the form of measures of central tendency and measures of dispersion (median and modal value using the accumulation and deviation method). 2 hours.
5. Calculation of basic statistics from distribution series in the form of measures of central tendency and measures of dispersion (standard deviation using the accumulation and deviation method, coefficient of variation). 2 hours.
6. Introduction to inductive statistics and practical application of statistical research methods (stages of scientific research, principles of formulating scientific objectives, statistical hypotheses, hypothesis testing, Type I and Type II errors). 2 hours.
7. Fisher-Snedecor test for equality of distributions. 2 hours.
8. Student's t-tests for independent samples. 2 hours.
9. Student's t-tests for paired samples. 2 hours.
10. Tests for two fractions. 2 hours.
11. Chi2 independence tests for a 4-field table. 2 hours.
12. Chi2 independence tests for a multi-field table. 2 hours.
13. Linear regression – least squares method. 2 hours.
14. Pearson's correlation coefficient. 2 hours.
15. Revision and recap of the material. 2 hours.
Total hours: 30

Term 2023/24_L:

Exercises are devoted to independent statistical calculations. Practical classes include:
• Creating distribution series and graphical representation of the distribution series structure (histograms and polygons)
• Calculation of basic statistics from distribution series in the form of central trend measures and dispersion measures. (mean and standard deviation by the method of accumulation and deviations, coefficients of variation)
• 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 tests (including student's t-tests, ANOVA, fraction tests)
• regression analysis,
• Chi2 test,

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, one-way analysis of variance, Mann-Whitney test, Wilcoxon, Kruskal Walis, 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 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 2 Task 1: active participation in classes- 30h task 2: preparation for colloquia - 30h

Term 2022/23_L:

ECTS 2 Task 1: active participation in classes- 30h task 2: preparation for colloquia - 30h

Term 2024/25_L:

ECTS 2 Task 1: active participation in classes- 30h task 2: preparation for colloquia - 30h

Term 2023/24_L:

ECTS 2 Task 1: active participation in classes- 30h task 2: preparation for colloquia - 30h

Term 2025/26_L:

Description of student workload in ECTS 1. Direct contact with the lecturer – participation in classes – 30 hours. 2. Independent work – preparation for classes, completing tasks posted on the remote learning platform – 15 hours, preparation for the test, presentation – 15 hours. Total: 60 hours/2 ECTS

Subject level

intermediate

Learning outcome code/codes

Informacje o zajęciach w cyklu 2025/26_L OB1_W05, OB1_W08, OB1_U01, OB1_U05, OB1_U06, OB1_K02 Stare informacje o zajęciachOB1_W06 OB1_W10 OB1_U02 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 - Test
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 - Test
U_01 The student describes population phenomena in the natural environment and controls the reliability of the obtained research results. The student assesses the representativeness of the sample in statistical inference. Course topics: (1, 2, 3, 4, 5)
Methods of verifying learning outcomes - Test
U_02 The student explains the results of the analyses and applies statistical inference. Course topics: (1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15)
Methods of verifying learning outcomes - Test
U_03 The student formulates and verifies statistical hypotheses. Course topics: (6, 7, 8, 9, 10, 11, 12, 13, 14, 15)
Methods of verifying learning outcomes - Test
K_01 The student critically diagnoses and evaluates statistical errors in scientific research and presents reliable research results. Course topics: (1, 2, 6, 13, 14)
Methods of verifying learning outcomes - Test

LLearning outcomes:
W_01 Graduates know the main conceptual categories and terminology in the field of natural sciences, as well as the development of these disciplines and the research methods used in them.
W_02 Graduates know mathematical and statistical tools at a level that allows them to describe natural phenomena.
U_01 They are able to take measurements, determine values, and assess the reliability of basic physical and chemical quantities (OB1_U01).
U_02 Graduates are able to interpret observations and measurements and draw correct conclusions based on them.
U_03 Graduates are able to formulate correct hypotheses regarding the causes of situations/threats that have arisen.
K_01 Graduates are prepared to exercise caution and critical thinking when accepting information provided by the mass media that relates to environmental protection.

Assessment criteria

Passing exercises for a grade, test/practical exam.
Learning outcomes are verified in the form of tests conducted during classes.
In order to pass the course, students must correctly solve statistical problems using the appropriate formulas. The final grade is the average of the partial tests and the final test.
Two absences are permitted. Make-up work is arranged with the instructor. Cases of prolonged illness will be considered on an individual basis.

Assessment criteria:
5.0 - error-free solution of the task
4.5 - minor calculation errors
4.0 - lack of statistical hypotheses in the task and minor calculation errors, correct interpretation
3.5 - no hypotheses, major calculation errors, and correct interpretation of results
3.0 - no hypotheses, major calculation errors, incomplete interpretation

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:

Attending lectures, basic mathematics and population biology

Term 2024/25_L:

Attending lectures, basic mathematics and 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-INFO2 in USOSweb