Syllabus
B i o s t a t i s t i c s - syllabus 3rd Medical Faculty, 2nd year, 1st term
SEMINARS 1. Statistical concepts and terms
Historical remarks, statistics in medical sciences
Logic of statistical reasoning (observations vs hypotheses)
Important steps in the application of statistics
Types of variables
Descriptive statistics (location, variability)
Probability, distribution
Population - sample, sampling techniques
Representativity of the sample
Point and interval estimation, standard error
Confidence interval 2. Statistical inference and testing (continuous variables)
Principles of statistical testing
Statistical hypothesis and significance level
One-sided and two-sided hypotheses
One-sample, two-sample, and paired tests
Parametrical and non-parametrical tests
Testing hypotheses concerning the mean (t-test, Wilcoxon test)
Introduction to multivariate methods, analysis of variance (ANOVA)
Interpretation of results of statistical procedures 3. Statistical concepts used in epidemiology (categorical variables)
Contingency and 2-by-2 tables and methods for comparison of proportions
Chi-square test, Fisher and McNemar tests, test for trend
Basic types of studies used in epidemiology and related statistical models for their evaluation
Vital statistics, rates and ratios
Odds ratio, relative risk, attributable risk for cross-sectional, cohort, and case-control study
Confounding, bias, precision
Methods of standardization and stratification, Mantel-Haenszel technique
Evaluation of diagnostic and screening tests (sensitivity and specificity, cut-off point) 4. Advanced statistical methods
Association between two variables: correlation, regression
Advanced statistical methods in epidemiology logistic regression censored data survival analysis
Mathematical tools for planning surveys and experiments, sample size determination
PRACTICALS 1. Statistical concepts: types of variables, probability distribution (binomial, Poisson, normal), population and sample, sampling methods, characteristics of location and variability, standard error, histogram, point and interval estimation, confidence interval 2. Statistical inference: testing statistical hypotheses, p-value, significance level
Statistical tests for continuous variables: t-test and Wilcoxon test (one-sample, two-sample, paired), analysis of variance (ANOVA), F-test 3. Statistical tests for categorical variables: contingency table, chi-square test, McNemar test, test for trend
Statistical methods in epidemiology: epidemiological measures of risk and corresponding confidence intervals, interpretation 4. Statistical association: linear regression, correlation, logistic regression
Planning surveys: sample size determination
Practical use of statistics: statistical packages, statistics in published papers
Annotation
A part of Module IE. An introduction to statistical methods in medicine and epidemoilogy.