PřF:Bi8661 Data analysis on PC III

Bi8661 Data analysis on PC III

Faculty of Science
Autumn 2008

Extent and Intensity

0/2/0. 2 credit(s) (plus extra credits for completion). Type of Completion: graded credit.

Teacher(s)

RNDr. Eva Gelnarová (seminar tutor)

Guaranteed by

Prerequisites (in Czech)

Bi5040 Biostatistics - basic course && Bi7490 Intr. to Stochastic Modelling
This subject is suitable for more advanced students with good knowledge of statistics. More advanced statistical software will be presented.

Course Enrolment Limitations

The course is also offered to the students of the fields other than those the course is directly associated with.

fields of study / plans the course is directly associated with

Course objectives

The course is oriented on advanced software for data analyses.

Syllabus

1. Introduction to R software, basic statistical methods a) Basics of R – history, installation, data loading, data types and structures, function creation, libraries, formatting of outputs, matrix operations b) data visualization – boxplots, histograms, scatter-plots c) data operations, transformation, summary of statistical distributions, correlation coefficients d) Statistical tests – tests of normality, one and two-sample t-test, nonparametric tests e)Analysis of variance. 2. Advanced statistical methods in R a)contingency tables, chi-square test b)linear regression models – estimation of parameters, residual diagnostics, outliers, parameters selection c) generalized linear models – logistic regression, poisson regression d)principal component analysis – eigenvalues. 3. Block based on students requests with possibilities a)analysis of real dataset in R, reporting b) introduction to other software

Literature

Zar, J.H.: Biostatistical analysis. New Jersey 1984, Prentice-Hall
StatSoft, Inc. (2007). Electronic Statistics Textbook. Tulsa, OK: StatSoft. WEB: http://www.statsoft.com/textbook/stathome.html
www.r-project.org
Snedecor, G.W., Cochran, W.G.: Statistical methods, Iowa 1971, Iowa State University Press.
Legendre, P., Legendre, L. (1998) Numerical ecology. Elsevier, 2nd ed.
ter Braak, C.J.F. (1996). Unimodal models to relace species to environment. DLO-Agricultural Mathematics Group, Wageningen Flury, B., Riedwyl, H. (1988) Multivariate statistics. A practical approach. Chapman and Hall, London.

Assessment methods

The credit is obtain through presence of student on course.

Language of instruction

Czech

Further Comments

Study Materials
The course is taught annually.

The course is also listed under the following terms Autumn 2009.