Informatics 2 - using of statistical methods in enviromental sciences

(in Polish) E-Learning z podziałem na grupy

ECTS 2

Task 1: active participation in classes- 30h

task 2: preparation for colloquia - 30h

obligatory

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.

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.

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.

Attending lectures, basic mathematics and population biology

ECTS 2

Task 1: active participation in classes- 30h

task 2: preparation for colloquia - 30h

obligatory

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.

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.

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.

Attending lectures, basic mathematics and population biology

ECTS 2

Task 1: active participation in classes- 30h

task 2: preparation for colloquia - 30h

obligatory

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.

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.

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.

Attending lectures, basic mathematics and population biology

ECTS 2

Task 1: active participation in classes- 30h

task 2: preparation for colloquia - 30h

obligatory

(in Polish) nie dotyczy

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.

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.

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.

Attending lectures, basic mathematics and population biology