BMBS051 Biostatistics - basic course

Faculty of Medicine
Autumn 2017
Extent and Intensity
3/0/0. 3 credit(s) (plus 1 credit for an exam). Type of Completion: zk (examination).
Teacher(s)
prof. RNDr. Ladislav Dušek, Ph.D. (lecturer)
RNDr. Jiří Jarkovský, Ph.D. (lecturer)
Guaranteed by
prof. RNDr. Ladislav Dušek, Ph.D.
Institute of Biostatistics and Analyses – Other Departments for Educational and Scientific Research Activities – Faculty of Medicine
Contact Person: prof. RNDr. Ladislav Dušek, Ph.D.
Supplier department: Institute of Biostatistics and Analyses – Other Departments for Educational and Scientific Research Activities – Faculty of Medicine
Prerequisites
VLLM0522p Medical Microbiology II - lect && VLIM051p Immunology - lecture && ( VSBC041p Biochemistry II -l || VSBC0422p Biochemistry II -l ) && VSIP0622c Introduction to internal II-pr
None - basic course.
Course Enrolment Limitations
The course is offered to students of any study field.
Course objectives
The course is aimed on applied data analysis for students of biological and clinical sciences. The presented topics range from theoretical background (statistical estimates, statistical distributions, statistical hypothesis testing) and simple applications (one sample and two sample tests, correlation analysis) to stochastic modelling (experimental design, regression analysis, analysis of variance).
Learning outcomes
At the end of the course the students are able to:
Define structure of dataset for statistical analysis;
Visualize the data and interpret data visualisation;
Identify correct methods of descriptive statistics;
Formulate hypothesis for statistical testing;
Select the correct statistical tests for hypotheses confirmation/refusal;
Interpret results of statistical evaluation, both analysis of own data and statistics in scientific literature;
Assess the applicability of statistical methods on various types of data.
Syllabus
  • Introduction to statistics, testing of hypotheses.
  • Tables of distribution functions. Sampling from biological populations, data processing.
  • Introduction to sampling design. Continuous, ordinal and nominal data in biology.
  • Distribution of continuous and bivariate variables - testing of hypotheses, graphical methods.
  • Application of binomial and Poisson distribution in biology.
  • One sample testing: sample mean, median, standard deviation, variance, binomial p and Poisson constant.
  • Two sample testing. Experimental design - randomized and blocked. Parametric and non - parametric methods.
  • Application of goodness-of-fit test in biology, analysis of R x C contingency tables, discrimination of categorical data.
  • Measures of similarity in ecology (covariance, correlation coefficients, similarity coefficients).
  • Analysis of variance (ANOVA): one-way and two-way model.
  • Simple linear regression. Linear regression. Introduction to multivariate linear regression.
  • Experimental design: one-way and two-way models; factorial design, randomized blocks. Laboratory and field trials. Nested design of ANOVA in genetics and ecology. Non - parametric ANOVA.
Literature
  • Zar, J.H. (1994) Biostatistical methods. Prentice Hall, London. 2nd ed.
  • G. W. Snedecor, W. G. Cochran (1971). Statistical methods. Iowa State University Press.
  • HAVRÁNEK, Tomáš. Statistika pro biologické a lékařské vědy. 1. vyd. Praha: Academia, 1993, 476 s. ISBN 8020000801. info
  • J. Benedík, L. Duąek (1993) Sbírka příkladů z biostatistiky. Nakladatelství KONVOJ, Brno.
Teaching methods
Theoretical lectures supplemented by commented examples; students are encouraged to ask quaetions about discussed topics.
Assessment methods
Course is finished by written exam aimed on principles, prerequisties and correct selection of methods for solution of practical examples.
Language of instruction
Czech
Further comments (probably available only in Czech)
Study Materials
The course is taught annually.
The course is taught: every week.
Teacher's information
http://www.cba.muni.cz/vyuka/
The course is also listed under the following terms Autumn 2002, Autumn 2003, Autumn 2004, Autumn 2005, Autumn 2006, Autumn 2007, Autumn 2008, Autumn 2009, Autumn 2010, Autumn 2011, Autumn 2012, Autumn 2013, Autumn 2014, Autumn 2015, Autumn 2016, autumn 2018, autumn 2019, autumn 2020, autumn 2021, autumn 2022, autumn 2023, autumn 2024.
  • Enrolment Statistics (Autumn 2017, recent)
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