EMBS0111p Biostatistics

Faculty of Medicine
autumn 2024
Extent and Intensity
2/0/0. 5 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
Contact Person: RNDr. Jiří Jarkovský, Ph.D.
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
Course objectives
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.
Learning outcomes
At the end of the course, students are able to:
Define the structure of a data set for statistical analysis;
Visualize input data for analysis and interpret these visualizations;
Identify appropriate methods for descriptive data analysis;
Fomulate hypotheses for statistical data analysis;
Select correct statistical tests to confirm/refute the hypotheses;
Interpret the results of statistical evaluation of data (both own and in professional literature);
Assess the appropriateness of applying different statistical methods to different 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 nonparametric 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. Nonparametric 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 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
Information on the extent and intensity of the course: 30.
The course is also listed under the following terms autumn 2020, autumn 2021, autumn 2022, autumn 2023.
  • Enrolment Statistics (recent)
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