Lecturer(s)


Duchoslav Martin, RNDr. Ph.D.

Course content

Lectures are focusing on the explanation of principles of statistical methods and correct interpretation of the results of statistical tests. The course absolvents should be able correctly (i) design the observations or experiments, (ii) collect, analyze and interpret data for the purposes of their theses, and (iii) understand statistical methods and results appearing in scientific literature. How the test works is illustrated on real data. Computer exercises with statistical software are integral parts of the course. Lessons 1. Introduction, what is science, methodology, philosophy of science, deduction, induction 2. Population and sample, sampling design, types of variables, observations and experiments, descriptive and exploratory statistics 3. Probability, principles of hypothesis testing, theoretical and empirical distributions 4. Analyses of categorical data (chisquare, contingency tables, Fisher exact test, odds ratios, loglinear models) 5. Analyses of ordinal and quantitative data I: one and two samples, parametric and nonparametric tests (Monte Carlo), random and block designs, data transformation 6. Analyses of ordinal and quantitative data II: three and more samples, ANOVA: oneway, multifactor, with randomized blocks, with repeated measurements, nested 7. Relationships between quantitative variables: regression and correlation, linear and nonlinear models, ANCOVA

Learning activities and teaching methods

Lecture, Dialogic Lecture (Discussion, Dialog, Brainstorming), Projection (static, dynamic)

Learning outcomes

The aim of the course is to acquaint students with the basic principles of statistical applications in biology / ecology.
Student should be able to (after attending the course):  explain the principles of statistical methods and correct interpretation of the results of statistical tests.  design correctly the observations or experiments,  collect, analyze and interpret the data using statistical software

Prerequisites

unspecified

Assessment methods and criteria

Mark, Oral exam, Written exam
combined exam in extent of the lectures: written test and calculating some mathematical/ecological examples in statistical software on PC

Recommended literature


Delventhal K. a kol. (2004). Kompendium matematiky.. Universum.

Gotelli N., Ellison A. (2004). A Primer of Ecological Statistics.. Sinauer Associates.

Havránek, T. (1993). Statistika pro biologické a lékařské vědy.. Academia, Praha.

Hendl, J. (2006). Přehled statistických metod zpracování dat. Portál, Praha.

Komenda S. (1994). Biometrie.. Vydavatelství UP, Olomouc.

Lepš, J. (1996). Biostatistika. JČ Univerzita, České Budějovice.

Meloun M. & Militký J. (2002). Kompendium statistického zpracování dat.. Academia, Praha.

Moore D. S. (2007). The basic practice of statistics.. Freeman, New York.

Quinn G.P. & Keough M.J. (2002). Experimental design and data analysis for biologist.. Cambridge University Press.

Sokal R. & Rohlf F. (1995). Biometry.. Freeman and Company, New York.

Zar J. H. (1998). Biostatistical analysis.. Prentice Hall, Englewood Cliffs.
