BLKBS051p Biostatistics - lecture

Faculty of Medicine
Autumn 2017
Extent and Intensity
0/0. 1 credit(s). Type of Completion: zk (examination).
Teacher(s)
prof. RNDr. Ladislav Dušek, Ph.D. (lecturer)
RNDr. Jiří Jarkovský, Ph.D. (lecturer)
RNDr. Danka Haruštiaková, Ph.D. (seminar tutor)
Mgr. et Mgr. Jiří Kalina, Ph.D. (seminar tutor)
RNDr. Denisa Krejčí (seminar tutor)
Guaranteed by
prof. RNDr. Ladislav Dušek, Ph.D.
Institute of Biostatistics and Analyses - Other Departments for Educational and Scientific Research Activities - Faculty of Medicine
Supplier department: Institute of Biostatistics and Analyses - Other Departments for Educational and Scientific Research Activities - Faculty of Medicine
Prerequisites
BLKZI0211 Computer Science - p.
None - basic course
Course Enrolment Limitations
The course is only offered to the students of the study fields the course is directly associated with.
fields of study / plans the course is directly associated with
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.
  • W. Snedecor, W. G. Cochran (1971). Statistical methods. Iowa State University Press.
  • J. Benedík, L. Duąek (1993) Sbírka příkladů z biostatistiky. Nakladatelství KONVOJ, Brno.
  • HAVRÁNEK, Tomáš. Statistika pro biologické a lékařské vědy. 1. vyd. Praha: Academia, 1993. 476 s. ISBN 8020000801. info
Teaching methods
Theoretical lectures supplemented by commented examples; students are encouraged to ask quaetions about discussed topics.
Assessment methods
Biostatistics 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
Information on the extent and intensity of the course: 10.
The course is also listed under the following terms Autumn 2011, Autumn 2012, Autumn 2013, Autumn 2014, Autumn 2015, Autumn 2016, autumn 2018, autumn 2019.
  • Enrolment Statistics (Autumn 2017, recent)
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