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Medical statistics
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Katedra Podstaw Teoretycznych Nauk Biomedycznych i Informatyki Medycznej
Head of the unit: dr hab. Przemysław Staszewski, Prof. UMK
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Faculty of Medicine, Medical Program, 2nd year
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Course coordinator: dr hab. Przemysław Staszewski, Prof. UMK
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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.
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Self-study topics:
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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.
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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
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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.