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Statistics in environmental studies

Informacje ogólne

Kod przedmiotu: R.1sa.SES.SM.ROSAY Kod Erasmus / ISCED: (brak danych) / (brak danych)
Nazwa przedmiotu: Statistics in environmental studies
Jednostka: Wydział Rolniczo-Ekonomiczny
Grupy:
Punkty ECTS i inne: 4.00
Język prowadzenia: angielski
Skrócony opis: (tylko po angielsku)

KIERUNEK STUDÓW : Environmental Studies / ECTS: 4 / semestr: 1

Profil: ogólnoakademicki / Forma i poziom: SM

status: kierunkowy

Prerequisites: No

The aim of the statistics course is presentation and characterization of the basic techniques of the analysis of quantitative information with application of statistical methods.

The course curriculum comprises the methods of description and statistical inference that relates to investigations of structure and the correlation of phenomena. The content of the course is replenished examples of the statistical analysis employing the statistical software.

Pełny opis: (tylko po angielsku)

LECTURES:

1. Science, observations, and statistics. Research methods, data structures, measurement, and statistics.

2. Frequency distributions.

3. Central tendency and the shape of distribution.

4. Measures of central tendency.

5. Variability and measures of variability.

6. Probability and the normal distribution.

7. Linear relationship. The Pearson Correlation. The Spearman Correlation.

8. Interpreting the correlation measure. Hypothesis tests with the correlation measure.

9. Linear regression model.

10. Testing the significance of the regression equation.

11. Hypothesis tests with the t statistic. Effect size for the t Statistic. Directional hypotheses and one-tailed tests.

12. Introduction to Independent-Measures Designs. The t Test for two independent samples.

13. Introduction to Repeated-Measures Designs. The t Test for two related samples

14. The logic of analysis of variance.

15. Post hoc tests.

CLASSES:

1. Science, observations, and statistics. Data structures, measurement, and statistics.

2. Frequency distributions.

3. Central tendency and the shape of distribution.

4. Variability and measures of variability.

5. Standardized distributions. Z-scores.

6. Probability and the normal distribution.

7. Inferences about means and means differences. The logic of hypothesis testing.

8. Hypothesis tests with t-statistics.

9. The t-tests for two independent samples. The t-tests for two related samples.

10. Measures of relationship. Pearson Correlation – interpreting the measure.

11. Hypothesis tests with the Pearson Correlation.

12. Linear relationship.

13. Linear regression model Testing the significance of the regression equation.

14. The logic of analysis of variance.

15. Post hoc tests. The relationship between analysis of variance and t-tests.

Struktura aktywności studenta:

zajęcia realizowane z bezpośrednim udziałem prowadzącego 35 godz. (ECTS** 1,4)

w tym:

wykłady 15 godz.

ćwiczenia i seminaria 15 godz.

konsultacje 3 godz.

udział w badaniach 0 godz.

obowiązkowe praktyki i staże 0 godz.

udział w egzaminie i zaliczeniu 2 godz.

e-learning 0 godz.

Praca własna 50 godz. (ECTS** 2,6)

Literatura: (tylko po angielsku)

LITERATURE PRIMAL:

Cohen P., Cohen J., West S.G., Aiken L.S., Applied Multiple Regression/Correlation Analysis for the Behavioral Sciences, Lawrence Erlbaum Associates Inc., New Jersey, 2002.

McClave J.T., Sincich T., 2016, Statistics, Prentice Hall.

Gotelli N.J., Ellison A.M., A primer of ecological statistics, Sinauer Associates, Sunderland, 2004.

LITERATURE SUPPLEMENTAL:

Krishnaiah P. R., Analysis of variance, Elsevier, Amsterdam, 1980.

Rees D. G., Essential statistics, Chapman & Hall, London, 1995.

Sokal R., Rohlf F.J., Biometry: the principles and practice of statistics in biological research, W. H. Freeman and Company, New York, 1998.

Efekty uczenia się: (tylko po angielsku)

KNOWLEDGE − the graduate knows and understands:

- Possesses advanced knowledge in mathematical statistics and knows the tests used in agricultural and environmental sciences.

- Knows statistical measures used for model verification.

- Knows the rules of planning and conducting single and multi-factor field and pot experiments.

SKILLS − the graduate be able to:

- Uses statistical terms, parametrical tests and measures connected with structural research

- Models processes occurring in the natural environment

SOCIAL COMPETENCES − the graduate:

- Appreciates the necessity of logical thinking, is aware of the necessary control of work quality.

- Is aware of the level of his/her knowledge, feeling the necessity for further professionally oriented studies.

- Appreciates the necessity of combining interdisciplinary knowledge and using computer techniques in research and projects.

Metody i kryteria oceniania: (tylko po angielsku)

Written exam, for passing an examination at least 51% of the scores should be received.

The contribution of the evaluation of the lectures in the final grade is 66.6%.

Zajęcia w cyklu "Semestr zimowy 2018/2019" (zakończony)

Okres: 2018-10-01 - 2019-02-24
Wybrany podział planu:


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Typ zajęć: Ćwiczenia audytoryjne, 15 godzin więcej informacji
Wykład, 15 godzin więcej informacji
Koordynatorzy: Jacek Strojny
Prowadzący grup: Jacek Strojny
Lista studentów: (nie masz dostępu)
Zaliczenie: Zaliczenie na ocenę
Opisy przedmiotów w USOS i USOSweb są chronione prawem autorskim.
Właścicielem praw autorskich jest Uniwersytet Rolniczy im. Hugona Kołłątaja w Krakowie.