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Lecturer(s)
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Pikner Richard, MUDr. Ph.D.
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Course content
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Lectures 1. Paradigm, axiom, postulate, doctrine, dogma, premise, causality. 2. Evidence-based practice. Quantitative research methods and statistics in the field of laboratory research. Data file structure for statistical analysis. 3. Quantification and stratification of statistical features. Data typology and categorization according to degree of quantification. 4. Descriptive statistics - calculation of empirical characteristics, principles of graphical expression of outputs, selection of a suitable method of descriptive data analysis, method of interpretation of outputs. 5. Reliability and validity of the research instrument based on the empirical characteristics of descriptive statistics. Sampling errors, confidence level and intervals, principles of probability (random phenomenon), p-value. Interpretation of statistical testing results. Basic data randomization procedures and statistical test power analysis procedures. 6. Inductive-inferential statistics and the formulation of statistical hypotheses from objective hypotheses in the research topics of the field of medical laboratory technician. A generally valid statistical hypothesis testing procedure. Correct statistical tests to verify the validity of stat. hypothesis. Normality tests - normal distribution of data including stat. tests suitable for assessing normality in small data sets. Variability tests for testing the equality of variances of random-independent samples from a population. 7. Parametric and non-parametric statistical tests of the mean value for one, two or more dependent and independent data samples obtained from the research activity of a medical laboratory technician. Continuity correction and multiple testing. Principles of exclusion of extreme values using stat. tests. Interpretation of the results of the used quantitative research methods (inductive statistics). 8. Statistical tests of the mean for more than two samples with more than one factor-independent stat. sign. Types of effect and its size (standardized, non-standardized). Factor analysis.. Examples in the context of the research activity of a health laboratory technician. 9. Chi (square) goodness-of-fit tests (for paired and unpaired data) and a test of independence. Assessing the appropriateness of applying different statistical methods to different types of data. 10. Processing of large data files. Calculations of epidemiological indicators. 11. Ethical principles and principles of scientific and research work (including publication ethics). Basic principles of bioethics. Ethical codes and standards for the healthcare professional in the context of research conducted by obtaining data from living subjects. Related documents and legislative framework in the process of approval of the research plan by the ethics committee. Clinical data anonymization procedures. Seminars - thematically follow the topics of the lectures with practical applications.
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Learning activities and teaching methods
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- Contact hours
- 44 hours per semester
- Preparation for comprehensive test (10-40)
- 25 hours per semester
- Presentation preparation (report) (1-10)
- 10 hours per semester
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| prerequisite |
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| Knowledge |
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| to explain the principles used in retrieving, viewing, organizing, formatting, analyzing, representing and storing tabular data |
| Skills |
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| effectively process data using software tools known as spreadsheets |
| Competences |
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| N/A |
| learning outcomes |
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| Knowledge |
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| defines the structure of the dataset for statistical analysis |
| assesses the appropriateness of applying different statistical methods to different types of data |
| chooses correct statistical tests to confirm/refute established hypotheses |
| Skills |
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| visualizes input data for analysis and interprets these visualizations |
| identifies appropriate methods of descriptive data analysis |
| formulates hypotheses of statistical data analysis |
| interprets the results of statistical evaluation of data |
| observes the ethical principles and principles of scientific research work |
| Competences |
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| N/A |
| teaching methods |
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| Knowledge |
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| Interactive lecture |
| Skills |
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| Task-based study method |
| Competences |
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| Task-based study method |
| assessment methods |
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| Knowledge |
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| Test |
| Skills |
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| Individual presentation at a seminar |
| Competences |
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| Individual presentation at a seminar |
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Recommended literature
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BLITZSTEIN, Joseph K a Jessica HWANG. Introduction to probability.. Boca Raton, FL: CRC Press, 2015. ISBN 978-1-4665-7559-2.
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GÖPFERTOVÁ, Dana. Základy obecné epidemiologie [online]. 1. vyd.. Praha: Ústav epidemiologie 2. Lékařské fakulty Univerzity Karlovy, 2019.
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GURKOVÁ, Elena. Praktický úvod do metodologie výzkumu v ošetřovatelství. 1. vyd.. Olomouc: Univerzita Palackého v Olomouci, 2019. ISBN 978-80-244-5627-0.
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HAŠKOVCOVÁ, Helena. Lékařská etika. Čtvrté, aktualizované a rozšířené vydání.. Praha : Galén, 2015. ISBN 978-80-7492-204-6.
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HENDL, Jan. Přehled statistických metod: analýza a metaanalýza dat. Páté, rozšířené vydání.. Praha: Portál, 2015. ISBN 978-80-262-0981-2.
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HOLČÍK, Jiří, KOMENDA, Martin (eds.) a kol. Matematická biologie: e-learningová učebnice [online: https://portal.matematickabiologie.cz/]. 1. vydání.. Brno: Masarykova univerzita, 2015. ISBN 978-80-210-8095-9.
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JANOUT, Vladimír a Jana JANOUTOVÁ. Medicína založená na důkazu a klinická epidemiologie [online].. 2021. ISBN 978-80-271-3076-4.
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OCHRANA, František. Metodologie, metody a metodika vědeckého výzkumu. První vydání.. Praha: Karolinum, 2019. ISBN 978-80-246-4200-0.
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REITEROVÁ, Eva. Statistika pro nelékařské zdravotnické obory. 1. vyd.. Olomouc: Univerzita Palackého v Olomouci, 2016. ISBN 978-80-244-5082-7.
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VARKEY, Basil. Principles of clinical ethics and their application to practice. 2020.
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ZVÁROVÁ, Jana. Základy statistiky pro biomedicínské obory. 2., dopl. vyd.. Praha: Karolinum, 2011. ISBN 978-80-246-1931-6.
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