Bi9001c Statistical analysis of biological data - practice

Faculty of Science
Autumn 2020
Extent and Intensity
0/2/0. 2 credit(s). Type of Completion: z (credit).
Teacher(s)
RNDr. Milan Baláž, Ph.D. (seminar tutor)
Guaranteed by
RNDr. Milan Baláž, Ph.D.
Department of Experimental Biology – Biology Section – Faculty of Science
Contact Person: Naděžda Bílá
Supplier department: Department of Experimental Biology – Biology Section – Faculty of Science
Timetable
Wed 9:00–10:50 prace doma
Prerequisites
NOW( Bi9001 Statistical data analysis )
Basic knowledge of PC and spreadsheet handling (MS Excel will be used in the course) are required.
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 6 fields of study the course is directly associated with, display
Course objectives
The aims of these practical trainings is to learn use the software Statistica (partly also Microsoft Excel) for treatment of experimental biological data, adequately to the design of the experiment.
Learning outcomes
Passing through this practical training, students should be able to:
devise the adequate design of experiment;
select appropriate statistical method for given biological experimental data and design;
analyze these data using software Statistica;
efficiently present obtained result using reports, graphs and tables.
Syllabus
  • Data collecting. Organization of data within spreadsheets. PC-based statistical packages. Data import from spreadsheets. Variable types, statistical distributions, quantiles, null hypothesis, I. and II. error type. Experimental design, selecting of an appropriate statistical method. X2 test. F-test, t-test. One-way analysis of variance, homogeneity of variances, independence of residuals, data transformations, contrasts, a priori and post-hoc tests. Multiple analysis of variance: factorial, nested, and block designs, repeated measures ANOVA; interaction, fixed effect and random effect models, mixed model. Covariance analysis. Correlation analysis, Pearson, Spearman and partial correlation coefficient. Regression analysis, linear and non-linear regression, multiple regression.
Literature
  • LEPŠ, Jan. Biostatistika. Vyd. 1. České Budějovice: Jihočeská universita, 1996, 165 s. ISBN 8070401540. info
  • SOKAL, Robert R. and James F. ROHLF. Biometry :the principles and practice of statistics in biological research. 3rd ed. New York: W.H. Freeman and Company, 1995, xix, 887 s. ISBN 0-7167-2411-1. info
  • FRY, J. Biological data analysis - a practical approach. Oxford: Oxford University Press, 1994. info
Teaching methods
Practical training using software MS Excel and Statistica.
Assessment methods
Knowledge will be evaluated using model examples calculated by students during the whole semester.
Language of instruction
Czech
Further Comments
Study Materials
The course can also be completed outside the examination period.
The course is taught annually.
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, Autumn 2022, Autumn 2023, Autumn 2024.
  • Enrolment Statistics (Autumn 2020, recent)
  • Permalink: https://is.muni.cz/course/sci/autumn2020/Bi9001c