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

A part of Module IE. An introduction to statistical methods in medicine and epidemoilogy.