BLAM061p Analysis and Data Management for Healthcare Specialisation - lesson

Faculty of Medicine
Spring 2017
Extent and Intensity
1/0/0. 3 credit(s). Type of Completion: k (colloquium).
Teacher(s)
prof. RNDr. Ladislav Dušek, Ph.D. (lecturer)
RNDr. Jiří Jarkovský, Ph.D. (lecturer)
RNDr. Danka Haruštiaková, Ph.D. (seminar tutor)
Michaela Gregorovičová (assistant)
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
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
Course objectives
The aim of the course is to provide students with basic principles of statistical analysis of biological data from the experimental design, data collection and visualisation to descriptive statistics and statistical hypotheses testing.
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 and medicine.
  • 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 nonparametric methods.
  • Application of goodness-of-fit test, analysis of R x C contingency tables, discrimination of categorical data.
  • Analysis of variance (ANOVA): one-way and two-way model.
  • Simple linear regression. Linear regression.
Literature
  • ZAR, Jerrold H. Biostatistical analysis. 5th ed. Upper Saddle River, N.J.: Prentice Hall, 2010, xiii, 944. ISBN 9780131008465. info
  • PETRIE, Aviva and Caroline SABIN. Medical statistics at a glance. 1st ed. Oxford: Blackwell Science, 2001, 138 s. ISBN 0632050756. info
  • ALTMAN, Douglas G. Practical statistics for medical research. 1st ed. Boca Raton: Chapmann & Hall/CRC, 1991, xii, 611. ISBN 0412276305. info
Teaching methods
Theoretical lectures supplemented by commented examples; students are encouraged to ask questions about discussed topics.
Assessment methods
Biostatistics course is finished by written exam aimed on principles, prerequisites and correct selection of methods for solution of practical examples.
Language of instruction
Czech
Further comments (probably available only in Czech)
Study Materials
The course is taught annually.
Information on the extent and intensity of the course: u komb. studia 10 h/semestr.
The course is also listed under the following terms Spring 2014, Spring 2015, Spring 2016, Spring 2018, spring 2019, spring 2020, spring 2021, spring 2022, spring 2023, spring 2024, spring 2025.
  • Enrolment Statistics (Spring 2017, recent)
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