Bi5040 Biostatistics - basic course

Faculty of Science
Autumn 2020
Extent and Intensity
3/0/0. 3 credit(s) (fasci plus compl plus > 4). Type of Completion: zk (examination).
Teacher(s)
RNDr. Jiří Jarkovský, Ph.D. (lecturer)
prof. RNDr. Ladislav Dušek, Ph.D. (lecturer)
Mgr. Jan Fikejs (assistant)
Mgr. Ivana Kupčíková, DiS. (assistant)
Guaranteed by
prof. RNDr. Ladislav Dušek, Ph.D.
RECETOX – Faculty of Science
Contact Person: RNDr. Jiří Jarkovský, Ph.D.
Supplier department: RECETOX – Faculty of Science
Timetable
Wed 17:00–19:50 prace doma
Prerequisites
None - 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.
fields of study / plans the course is directly associated with
there are 14 fields of study the course is directly associated with, display
Course objectives
The aim of the course is to provide students with basic principles of statistical analysis of biological data from the experimental design, data collection and visualisation to descriptive statistics and statistical hypotheses testing.
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 nonparametric 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. Nonparametric ANOVA.
Literature
  • Petrie, A., Watson, P. (2006) Statistics for Veterinary and Animal Science, Wiley-Blackwell; 2nd ed
  • Zar, J.H. (1998) Biostatistical analysis. Prentice Hall, London. 4th ed.
  • Sokal, R.R., Rohlf, F.J. (1994) Biometry, W. H. Freeman, 3th ed.
Teaching methods
Presentations in Microsoft Teams; students are encouraged to ask questions about discussed topics.
Assessment methods
Biostatistics course is finished by written exam aimed on principles, prerequisites and correct selection of methods for solution of practical examples.
Language of instruction
Czech
Follow-Up Courses
Further comments (probably available only in Czech)
Study Materials
The course is taught annually.
Listed among pre-requisites of other courses
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, Autumn 2006, Autumn 2007, Autumn 2008, Autumn 2009, Autumn 2010, Autumn 2011, Autumn 2011 - acreditation, Autumn 2012, Autumn 2013, Autumn 2014, Autumn 2015, Autumn 2016, autumn 2017, Autumn 2018, Autumn 2019, autumn 2021.
  • Enrolment Statistics (Autumn 2020, recent)
  • Permalink: https://is.muni.cz/course/sci/autumn2020/Bi5040