Bi7541 Data analysis on PC

Faculty of Science
Spring 2021
Extent and Intensity
0/2/0. 2 credit(s) (plus extra credits for completion). Type of Completion: z (credit).
Teacher(s)
RNDr. Jiří Jarkovský, Ph.D. (seminar tutor)
Mgr. et Mgr. Jiří Kalina, Ph.D. (seminar tutor)
prof. RNDr. Ladislav Dušek, Ph.D. (seminar tutor)
Guaranteed by
prof. RNDr. Ladislav Dušek, Ph.D.
RECETOX – Faculty of Science
Contact Person: Mgr. et Mgr. Jiří Kalina, Ph.D.
Supplier department: RECETOX – Faculty of Science
Prerequisites
Basic knowledge of MS Windows, MS Office and basic statistisc.
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
Course objectives
The course is basic introduction into practical data analysis for students of biology and clinical study specialisations. The course accompanies theoretical lectures of biostatistics and shows the computation of presented methods on PC using statistical software (descriptive statistics, one sample and two sample tests, categorical data analysis, ANOVA, correlation and regression analysis, data visualisation, basics of experimental design).
Learning outcomes
In the end of the course student should be able to apply basic principles of biostatistical analysis and utilize them in his/her research work:
Using MS Excel for data preprocessing
Using Statistica for Windows for data analysis
Application of charts in MS Office and Statistica software for data visualisation
Application of descriptive statistics in Statistica for Windows
Application of statistical tests in Statistica for Windows
Syllabus
  • 1. Computer aided data analyses - introduction and principles of hierarchical data analysis. 2. Software for data analyses, data manipulation within MS-Windows. 3. Graphical features of statistical softwares - graphical presentation of continuous and categorical data, examples - model data files. 4. Exploratory and summary statistics - mean, median, confidence intervals, variance - calculations, presentation and interpretation. 5. Data distribution - graphical presentations (histograms, distribution functions), fitting to model distributions, testing of data normality. 6. One-sample testing (one- and two-tailed comparisons). 7. Two-samples comparisons (independent and dependent samples) - assumptions (normality, homogeneity of variances) and testing. Parametric tests (independent and paired t-test), nonparametric tests (Mann-Whitney, median test, Wilcoxon test). 8. Introduction to parametric and nonparametric correlation analysis. 9. Binomially distributed data - frequencies comparisons, chi-square and its applications, contingency tables. 10. Introduction to analysis of variance - assumptions, experimental design, calculations and results interpretations. 11. Analysis of model data -examples of complex data analysis (exploratory analysis, graphs and plots. 12. experimental design, hypotheses, selection of appropriate test, calculations and interpretations): two-sample testing, correlations, contingency tables.
Literature
  • Petrie, A., Watson, P. (2006) Statistics for Veterinary and Animal Science, Wiley-Blackwell; 2nd ed
  • Sokal, R.R., Rohlf, F.J. (1994) Biometry, W. H. Freeman, 3th ed.
  • Zar, J.H. (1998) Biostatistical analysis. Prentice Hall, London. 4th ed.
  • http://www.statsoft.com/textbook/stathome.html
Teaching methods
Practical training using computers
Assessment methods
Individual projects on correct application of statistical methods on example data
Language of instruction
Czech
Further comments (probably available only in Czech)
Study Materials
The course can also be completed outside the examination period.
The course is taught annually.
The course is taught: every week.
Note related to how often the course is taught: možno i blokově.
Information on the extent and intensity of the course: Online výuka Po 14:00–16:00 hod.
The course is also listed under the following terms Autumn 2007 - for the purpose of the accreditation, Spring 2011 - only for 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, Spring 2011, Autumn 2011, Spring 2012, Autumn 2011 - acreditation, spring 2012 - acreditation, Autumn 2012, Spring 2013, Autumn 2013, Spring 2014, Autumn 2014, Spring 2015, Autumn 2015, Spring 2016, Autumn 2016, Spring 2017, autumn 2017, spring 2018, Autumn 2018, Spring 2019, Autumn 2019, Spring 2020, Autumn 2020, autumn 2021.
  • Enrolment Statistics (Spring 2021, recent)
  • Permalink: https://is.muni.cz/course/sci/spring2021/Bi7541