Bi7930 Analysis of biological data

Faculty of Science
Spring 2005
Extent and Intensity
0/2/0. 2 credit(s). Type of Completion: zk (examination).
Teacher(s)
prof. Mgr. Stanislav Pekár, Ph.D. (seminar tutor)
Guaranteed by
prof. RNDr. Jaromír Vaňhara, CSc.
Faculty of Science
Contact Person: prof. Mgr. Stanislav Pekár, Ph.D.
Prerequisites (in Czech)
Bi5040 Biostatistics - basic course
Course Enrolment Limitations
The course is also offered to the students of the fields other than those the course is directly associated with.
The capacity limit for the course is 20 student(s).
Current registration and enrolment status: enrolled: 0/20, only registered: 0/20, only registered with preference (fields directly associated with the programme): 0/20
fields of study / plans the course is directly associated with
Course objectives
This lecture aims to teach how to analyse biological data using appropriate univariate statistical methods.
Syllabus
  • 1) Introduction: Explanatory and response variables, Key to analyses, Statistical software, R, Literature, Data frames, Basic functions. 2) Experimental Design: Type of studies, Pseudoreplications, Randomised, Stratified, Latin-squares, Split-plot, Factorial, Nested design. 3) Exploratory Data Analysis: Central tendency, Variance, Tabular analysis, Graphical analysis, Functions, Examples. 4) Classical tests: One-sample tests, Two-sample tests, Tests on proportions, Distribution test, Contingency tables, Correlations, Examples. 5) Statistical modelling: Modelling, Formulae, Output, Functions, Model simplification, Model criticism. 6) Regression: Concept, Linear regression, Non-linear regression, Multiple regression, Examples. 7) Analysis of variance: Concept, Assumptions, Analyses, Transformations, Kruskal-Wallis ANOVA, Split-plot ANOVA, Nested ANOVA, Examples. 8) Analysis of covariance: Concept, Examples. 9) Comparisons: Contrasts, Posteriori simplifications, Multiple comparisons, Examples. 10) Generalised Linear Models: Concept, Analyses, Gaussian distribution, Gamma distribution, Examples. 11) GLM with counts: Poisson distribution, Negative binomial distribution, Examples. 12) GLM with proportions: Binomial distribution, Bernoulli distribution, Examples. 13) Generalised Additive Models: Concept, Smoothing, Examples. 14) Tree models: Concept, Regression trees, Classification trees, Examples. 15) Survival analysis: Concept, Exponential distribution, Kaplan-Meier estimator, Cox proportional hazards model, other hazard models, Examples. 16) Mixed effects models. Concept, Fixed and random effects, ANOVA repeated measures, linear and non-linear mixed effects models (REML), Friedman's ANOVA, Examples.
Assessment methods (in Czech)
Hodnocení na základě výsledků domácích ůkolů, které jsou zadávány v průběhu semestru.
Language of instruction
Czech
Further comments (probably available only in Czech)
The course can also be completed outside the examination period.
The course is taught annually.
Information on course enrolment limitations: výuku zajišťují jednotlivé katedry biologické sekce, před zápisem je nutno kontaktovat jednotlivé vyučující z biologických kateder
The course is also listed under the following terms Autumn 2007 - for the purpose of the accreditation, Autumn 2010 - only for the accreditation, Autumn 2002, Autumn 2003, Autumn 2004, Autumn 2005, Spring 2006, Autumn 2006, Autumn 2007, Autumn 2008, Autumn 2009, Autumn 2010, Autumn 2011 - acreditation.
  • Enrolment Statistics (Spring 2005, recent)
  • Permalink: https://is.muni.cz/course/sci/spring2005/Bi7930