CC BY-NC-ND 4.0
Co-funded by the European Union. Views and opinions expressed are however those of the author(s) only and do not necessarily reflect those of the European Union or the National Agency of Erasmus+ Programme. Neither the European Union nor the National Agency of Erasmus+ Programme can be held responsible for them. Project Number: 2022-1-PL01-KA220-HED-000087008
This module introduces the foundations of statistical inference in medical research, focusing on how to draw reliable conclusions about a population based on sample data. It covers parameter estimation (point and interval estimation), including the conditions for a good sample (representativeness, random selection, sufficient size) and the properties of estimators (consistency, unbiasedness, efficiency). Learners practice constructing confidence intervals for the population mean under different assumptions (normal distribution with known/unknown variance; large-sample case) and for proportions. The second part develops the logic of hypothesis testing, including formulation of H0 and H1, significance level, rejection regions, and Type I/Type II errors, with worked examples using tests for the mean (z and t tests), variance (chi-square test), and selected nonparametric test families (randomness, goodness-of-fit, independence). [in Polish]
- Teacher: Mariola Chrzanowska