Bi8660 Data analysis on PC II

Faculty of Science
Spring 2008
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. Danka Haruštiaková, Ph.D. (seminar tutor)
RNDr. Eva Gelnarová (seminar tutor)
RNDr. Jan Mužík, Ph.D. (seminar tutor)
prof. RNDr. Ladislav Dušek, Ph.D. (seminar tutor)
Guaranteed by
RNDr. Jiří Jarkovský, Ph.D.
RECETOX – Faculty of Science
Contact Person: RNDr. Jiří Jarkovský, Ph.D.
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
Practical statistical techniques on PC. Application and usage of statistical software on PC. Summary statistics and data vizualization in MS Office products. Data analysis in software available on Internet. Introduction to uni-dimensional statistical techniques and associated graphical outputs. Exploratory data analysis. Distribution investigation and distribution fitting, statistical comparison of distribution functions. Normality testing. Parametric and non-parametric two-sample and multiple-sample comparisons. Correlation analysis. Introduction to ANOVA techniques, experimental design.
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
  • Snedecor, G.W., Cochran, W.G.: Statistical methods, Iowa 1971, Iowa State University Press.
  • Zar, J.H.: Biostatistical analysis. New Jersey 1984, Prentice-Hall
  • Benedík, J., Dušek, L: Sbírka příkladů z biostatistiky. Nakladatelství Konvoj 1993, Brno.
  • HEBÁK, Petr and Jiří HUSTOPECKÝ. Vícerozměrné statistické metody s aplikacemi. Praha: SNTL - Nakladatelství technické literatury, 1987. info
Language of instruction
Czech
Further comments (probably available only in Czech)
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.
Teacher's information
http://www.cba.muni.cz/vyuka/
The course is also listed under the following terms Spring 2008 - for the purpose of the accreditation, Spring 2003, Spring 2004, Spring 2005, Spring 2006, Spring 2007, Spring 2009, Spring 2010, Spring 2011.
  • Enrolment Statistics (Spring 2008, recent)
  • Permalink: https://is.muni.cz/course/sci/spring2008/Bi8660