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Informatics 2 - using of statistical methods in enviromental sciences

General data

Course ID: WF-OB-INFO2
Erasmus code / ISCED: 07.2 Kod klasyfikacyjny przedmiotu składa się z trzech do pięciu cyfr, przy czym trzy pierwsze oznaczają klasyfikację dziedziny wg. Listy kodów dziedzin obowiązującej w programie Socrates/Erasmus, czwarta (dotąd na ogół 0) – ewentualne uszczegółowienie informacji o dyscyplinie, piąta – stopień zaawansowania przedmiotu ustalony na podstawie roku studiów, dla którego przedmiot jest przeznaczony. / (unknown)
Course title: Informatics 2 - using of statistical methods in enviromental sciences
Name in Polish: Informatyka 2 - zastosowanie metod statystycznych w naukach przyrodniczych
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 2.00 (depends on study program) Basic information on ECTS credits allocation principles:
  • the annual hourly workload of the student’s work required to achieve the expected learning outcomes for a given stage is 1500-1800h, corresponding to 60 ECTS;
  • the student’s weekly hourly workload is 45 h;
  • 1 ECTS point corresponds to 25-30 hours of student work needed to achieve the assumed learning outcomes;
  • weekly student workload necessary to achieve the assumed learning outcomes allows to obtain 1.5 ECTS;
  • work required to pass the course, which has been assigned 3 ECTS, constitutes 10% of the semester student load.
view allocation of credits
Language: Polish
Subject level:

intermediate
Learning outcome code/codes:

OB1_U03

OB1_K03

OB1_K04

OB1_K05
Short description:

The purpose of the module is the practical application of basic statistical methods during scientific research.

Didactic methods used

Exercises in the form of multimedia presentations and independent data analysis in the form of solving statistical tasks.

Exercises end with a test on which the practical ability to solve a given statistical problem is tested.
Full description:

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.
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 and neurobiological 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:

Completion of exercises for the grade, colloquium / practical test.

Learning outcomes are verified in the form of colloquia carried out during classes.

In order to pass the course, students should correctly solve statistical sentences using appropriate formulas. The final grade of the exercises is the result of partial tests checking the knowledge of the exercises. The exam is in the form of written task solving.

Classes in period "Summer semester 2021/22" (past)

Time span: 2022-02-01 - 2022-06-30
Selected timetable range:
Navigate to timetable
Type of class:
Classes, 30 hours, 17 places more information
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 - graded credit
Classes - graded credit
(in Polish) E-Learning:

(in Polish) E-Learning z podziałem na grupy
Short description:

The purpose of the module is the practical application of basic statistical methods during scientific research.

Didactic methods used

Exercises in the form of multimedia presentations and independent data analysis in the form of solving statistical tasks.

Exercises end with a test on which the practical ability to solve a given statistical problem is tested.
Full description:

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.
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:

Attending lectures, basic mathematics and population biology

Classes in period "Summer semester 2022/23" (past)

Time span: 2023-02-01 - 2023-06-30
Selected timetable range:
Navigate to timetable
Type of class:
Classes, 30 hours, 17 places more information
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 - graded credit
Classes - graded credit
Short description:

The purpose of the module is the practical application of basic statistical methods during scientific research.

Didactic methods used

Exercises in the form of multimedia presentations and independent data analysis in the form of solving statistical tasks.

Exercises end with a test on which the practical ability to solve a given statistical problem is tested.
Full description:

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.
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:

Attending lectures, basic mathematics and population biology

Classes in period "Summer semester 2023/24" (in progress)

Time span: 2024-02-15 - 2024-06-30
Selected timetable range:
Navigate to timetable
Type of class:
Classes, 30 hours, 17 places more information
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 - graded credit
Classes - graded credit
Type of subject:

obligatory
(in Polish) Grupa przedmiotów ogólnouczenianych:

(in Polish) nie dotyczy
Short description:

The purpose of the module is the practical application of basic statistical methods during scientific research.

Didactic methods used

Exercises in the form of multimedia presentations and independent data analysis in the form of solving statistical tasks.

Exercises end with a test on which the practical ability to solve a given statistical problem is tested.
Full description:

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.
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:

Attending lectures, basic mathematics and population biology
Course descriptions are protected by copyright.
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