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Medical statistics I. II. Katedra Podstaw Teoretycznych Nauk Biomedycznych i Informatyki Medycznej Head of the unit: dr hab. Przemysław Staszewski, Prof. UMK III. Faculty of Medicine, Medical Program, 2nd year IV. Course coordinator: dr hab. Przemysław Staszewski, Prof. UMK V. VI. VII. VIII. Form of classes: lectures, tutorials Form of crediting: Credit with grade, 2 ECTS points Number of hours: 15 (lectures), 20 (tutorials) Aim of the course: Lectures: Basic notions of probability theory: random events and their properties, probability and its properties, combinatorial formulae, conditional probability, independent events, Bernoulli experiment and Bernoulli scheme. Random variables: One-dimensional random variables: discrete and continuous. Examples of important distribution functions of random variables: binomial distribution, Poisson distribution, normal distribution. Parameters of distribution functions of random variables: mean (expectation) value, variance, moments and central moments of order n, median. Statistical inference for probabilistic experiments of two possible outcomes: de Moivre-Laplace theorem. A statistical hypothesis, significance level and significance test, statistical hypothesis testing, test functions. Verifying statistical hypotheses of p p 0 and p p 0 . The power of a statistical test. Estimation of the parameter p. A confidence level and confidence interval. Two-dimensional random variables. Populations and samples of two-dimensional random variables. Examples of significance tests and their applications: A chi-square test for fit of a distribution, A chi-square test for independence, Student’s t-test. Pearson’s linear correlation coefficient. Computer laboratory classes: Solving simple problems of probability theory using combinatorics. Determination and analysis of the distribution parameters of a sample. Verification of statistical hypotheses given in the lectures. Determination of the coefficient of linear correlation to verify the dependence of random variables. IX. Self-study topics: ----------- X. Booklist: Medical Statistics at a Glance, Aviva Petrie & Caroline Sabin, Blackwell, 2005. Essentials of Statistics In Heath Information Technology, Carol E. Osborn, Jones & Bartlett, 2007. XI. Detailed list of required practical skills and confirmation of completing List of acquirements: Applcation of Bayes theorem, law of total probability and conditional probability in solving medical problems; Determining the shape and estimation of the parameters of distribution function of random variable; Standardizing the random variable and using the tables of distributions of random variables; Interval estimation of distribution parameters, confidence interval; Putting and verification of hypotheses, the choice of parametric and nonparametric tests of significance, checking assumptions of the tests; Application of computer programs to medical statistics calculations. Teaching method: lecture and computer laboratory classes. Crediting conditions: classes credit.