LF:ASTAp Biostatistics - lecture - Course Information

ASTAp Biostatistics - lecture

Extent and Intensity

2/0/0. 3 credit(s). Type of Completion: zk (examination).
In-person direct teaching

Teacher(s)

prof. RNDr. Ladislav Dušek, Ph.D. (lecturer)
RNDr. Jiří Jarkovský, Ph.D. (lecturer)

Guaranteed by

prof. RNDr. Ladislav Dušek, Ph.D.
Institute of Biostatistics and Analyses – Other Departments for Educational and Scientific Research Activities – Faculty of Medicine
Supplier department: Institute of Biostatistics and Analyses – Other Departments for Educational and Scientific Research Activities – Faculty of Medicine

Timetable

Wed 17:00–18:40 B11/132

Prerequisites

None - basic course.

Course Enrolment Limitations

The course is only offered to the students of the study fields the course is directly associated with.

fields of study / plans the course is directly associated with

• Biomedicínská technika a bioinformatika (programme LF, C-CV)
• Clinical Data Management (programme LF, B-SZ)

Course objectives

The course is aimed on applied data analysis for students of biological and clinical sciences. The presented topics range from theoretical background (statistical estimates, statistical distributions, statistical hypothesis testing) and simple applications (one sample and two sample tests, correlation analysis) to stochastic modelling (experimental design, regression analysis, analysis of variance).

Learning outcomes

At the end of the course the students are able to:
Define structure of dataset for statistical analysis;
Visualize the data and interpret data visualisation;
Identify correct methods of descriptive statistics;
Formulate hypothesis for statistical testing;
Select the correct statistical tests for hypotheses confirmation/refusal;
Interpret results of statistical evaluation, both analysis of own data and statistics in scientific literature;
Assess the applicability of statistical methods on various types of data.

Syllabus

• Introduction to statistics, testing of hypotheses.
• Tables of distribution functions. Sampling from biological populations, data processing.
• Introduction to sampling design. Continuous, ordinal and nominal data in biology.
• Distribution of continuous and bivariate variables - testing of hypotheses, graphical methods.
• Application of binomial and Poisson distribution in biology.
• One sample testing: sample mean, median, standard deviation, variance, binomial p and Poisson constant.
• Two sample testing. Experimental design - randomized and blocked. Parametric and non - parametric methods.
• Application of goodness-of-fit test in biology, analysis of R x C contingency tables, discrimination of categorical data.
• Measures of similarity in ecology (covariance, correlation coefficients, similarity coefficients).
• Analysis of variance (ANOVA): one-way and two-way model.
• Simple linear regression. Linear regression. Introduction to multivariate linear regression.
• Experimental design: one-way and two-way models; factorial design, randomized blocks. Laboratory and field trials. Nested design of ANOVA in genetics and ecology. Non - parametric ANOVA.

Literature

• Petrie, A., Watson, P. (2006) Statistics for Veterinary and Animal Science, Wiley-Blackwell; 2nd ed
• Zar, J.H. (1998) Biostatistical analysis. Prentice Hall, London. 4th ed.
• Sokal, R.R., Rohlf, F.J. (1994) Biometry, W. H. Freeman, 3th ed.

Teaching methods

Theoretical lectures supplemented by commented examples; students are encouraged to ask quaetions about discussed topics.

Assessment methods

Course is finished by written exam aimed on principles, prerequisties and correct selection of methods for solution of practical examples.

Language of instruction

Czech

Further comments (probably available only in Czech)

Study Materials
Information on the extent and intensity of the course: 30.

Teacher's information

http://www.cba.muni.cz/vyuka/

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