Uniwersytet Rolniczy im. Hugona Kołłątaja w Krakowie - Centralny System Uwierzytelniania Nie jesteś zalogowany | zaloguj się Drukuj sylabus

# Statistics and modeling in environmental studies

## Informacje ogólne

 Kod przedmiotu: R.SME1.A.SM.ROSOA Kod Erasmus / ISCED: (brak danych) / (brak danych) Nazwa przedmiotu: Statistics and modeling in environmental studies Jednostka: Katedra Statystyki Matematycznej Grupy: Punkty ECTS i inne: (brak)  zobacz reguły punktacji Język prowadzenia: angielski Skrócony opis: Statistics and modeling in environmental studies course takes basic statistical concepts and extends them to topics of special relevance in environmental studies. The course is intended to provide an insight what is needed to successfully analyze data in environmental sciences. The program emphasizes statistical modeling. Pełny opis: Methods of Teaching and Learning Lectures, classes, class discussion, guided self study. 1. Science, observations, and statistics. Research methods, data structures, measurement, and statistics. Frequency distributions. 2-3. Central tendency and the shape of distribution. Variability and measures of variability. 4. Probability and the normal distribution. 5-6. Hypothesis tests with t-statistics. The t-tests for two independent samples. The t-tests for two related samples. 7-8. Linear relationship. Linear regression model Testing the significance of the regression equation. 9-10. Measures of relationship. Pearson Correlation - interpreting the measure. Hypothesis tests with the Pearson Correlation. Other measures of relationship. 11-12. The logic of analysis of variance. Post hoc tests. The relationship between analysis of variance and t-tests. 13-14. Statistical models and their purposes. Statistical model formulas. 15. Confidence in statistical models. The logic of hypothesis testing. 16. Model and natural phenomenon. Modeling and models. Types of models used in environmental science. 17. Use of models in environmental science. 18-19. Structure of deterministic model. Parameters identification. Boundary and initial conditions. Verification. Model quality measures. 20. Use of neural networks in environmental processes modeling. 1. Frequency distributions. 2-3. Central tendency and the shape of distribution. Variability and measures of variability. 4. Standardized distributions. Z-scores. Probability and the normal distribution. 5-7. Inferences about means and means differences. The logic of hypothesis testing. Hypothesis tests with t-statistics. The t-tests for two independent samples. The t-tests for two related samples. 8-9. Linear relationship. Linear regression model Testing the significance of the regression equation. 10-11. Measures of relationship. Pearson Correlation - interpreting the measure. Hypothesis tests with the Pearson Correlation. Other measures of relationship. 12-13. The logic of analysis of variance. Post hoc tests. The relationship between analysis of variance and t-tests. 14. Statistical model formulas. The logic of hypothesis testing of statistical models. 15-16. Universal equation of soil water movement and its use. 17-18. Models rainfall-discharge in basin. 19-20. Erosion modeling. Use of the USLE model. 21. Evapotranspiration process modeling. 22. Model of water movement in the soil-plant-atmosphere system. 23-24. Modeling bases of pollutant dissemination in environment. 25. Subject assessment. Literatura: 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. Freedman D.A., Statistical Models: Theory and Practice, Cambridge University Press, New York, 2005. Gotelli N.J., Ellison A.M., A primer of ecological statistics, Sinauer Associates, Sunderland, 2004. 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.
 Przedmiot nie jest oferowany w żadnym z aktualnych cykli dydaktycznych.
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Właścicielem praw autorskich jest Uniwersytet Rolniczy im. Hugona Kołłątaja w Krakowie.