Bi7541 Data analysis on PC

Faculty of Science
Spring 2011
Extent and Intensity
0/2/0. 2 credit(s) (plus extra credits for completion). Type of Completion: graded credit.
Teacher(s)
RNDr. Jiří Jarkovský, Ph.D. (seminar tutor)
RNDr. Jan Mužík, Ph.D. (seminar tutor)
Mgr. Lukáš Kohút (seminar tutor)
Mgr. Tomáš Zdražil (seminar tutor)
Guaranteed by
prof. RNDr. Ladislav Dušek, Ph.D.
RECETOX – Faculty of Science
Contact Person: RNDr. Jiří Jarkovský, Ph.D.
Timetable of Seminar Groups
Bi7541/pondeli: No timetable has been entered into IS.
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
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. Grafical features of statistical softwares - graphical presentation of continuous and cathegorial 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, homogenity of variances) and testing. Parametric tests (independent and paired t-test), nonparametric tests (Mann-Whitney, median test, Wilcoxon test). 8. Introduction to parametric and neparametric corelation analysis. 9. Binomically 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, contingecy 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
Follow-Up Courses
Further Comments
Study Materials
The course can also be completed outside the examination period.
The course is taught annually.
Teacher's information
http://www.cba.muni.cz/vyuka/
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, 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, Spring 2021, autumn 2021.
  • Enrolment Statistics (Spring 2011, recent)
  • Permalink: https://is.muni.cz/course/sci/spring2011/Bi7541