PřF:Bi9001c Statistical Data Analysis- pr. - Course Information
Bi9001c Statistical analysis of biological data - practice
Faculty of ScienceAutumn 2010
- 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: Věra Faronová - Timetable
- Fri 10:00–11:50 B11/235
- 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
- General Biology (programme PřF, M-BI, specialization Plant Physiology)
- General Biology (programme PřF, N-BI, specialization Plant Physiology)
- Course objectives
- Passing through this practical training, students should be able to:
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.
- Enrolment Statistics (Autumn 2010, recent)
- Permalink: https://is.muni.cz/course/sci/autumn2010/Bi9001c