Předmět Stat. methods for physical geogr. in R (KFG / STMGR)
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Další informace
Obsah
Lectures:1. Introduction to the course, basic types of statistical design, variables, distributions, scales.2. Sampling, summary statistics of non-spatial and spatial data.3. Correlation, regression, multiple regression, the general linear model.4. Time series, interval estimations, null hypothesis significance testing.5. Student's t-test, ANOVA, Chi-square tests.6. Non-parametric statistics, non-linear regression.Exercises:1. Introduction to R.2. Histograms and summary statistics.3. Scatterplots and correlations.4. Regression.5. Confidence intervals.6. Multiple regression.7. Group comparisons (t-tests, ANOVA, post-hoc tests).8. Factorial ANOVA.9. Chi-square.10. Non-parametric tests.11. Non-linear regression.12. Course summary.
Literatura
" The R Project for Statistical Computing. Accessible < http://www.r-project.org/ >. McGrew, J.CH., Monroe, CH.B. An Introduction to Statistical Problem Solving in Geography. 2nd ed. New York: McGraw-Hill. ISBN: 0-697-22971-8. 2000. Barber, G.M. Elementary Statistics for Geographers. New York: Guilford Press. ISBN: 0-89862-777-X. 1988. WALFORD, N. Geographical data analysis. Chichester: Wiley, 1997. Walford, N. Practical Statistics for Geographers and Earth Scientists. 1st ed. Chichester: John Wiley & Sons. ISBN: 978-0-470-84914-9. 2001. Davis, J.C. Statistics and Data Analysis in Geology. New York: John Wiley & Sons. ISBN: 0-471-17275-8. 2002. MARSAL, D. Statistics for Geoscientists. Pergamon Press, Oxford, 1987. ISBN 0-08-026268-6.
Požadavky
Students don't need to have previous statistical knowledge or programming skills. For the course completion, it is required to be present in classes and to submit a correct solution of several homework tasks assigned by lecturer. Final exam consists of two parts, written test covering the lecture topics (40 % of the final grade) and time-limited practical solution of a given task in R (60 % of the final grade). The result of a course examination is expressed on a four-point scale: 1 = excellent, 2 = very good, 3 = good, 4 = fail. Final assessment of the exam is as follows: 0 - 50 pts. = fail, 51 - 70 pts. = good, 71 - 90 pts. = very good, 91 - 100 pts. = excellent. For successful completion of the course, basic knowledge of algebra is useful, but not necessary.
Garant
RNDr. Veronika Kapustová, Ph.D.
Vyučující
RNDr. Veronika Kapustová, Ph.D.RNDr. Veronika Kapustová, Ph.D.