STATISTICS APPLIED TO MEDICINE
View single details Learning Unit
The main aim of the course is to illustrate the basic elements needed to critically read and correctly interpret the results of quantitative medical research.
Descriptive and inferential statistics are framed into the scientific knowledge process. We read the “results” section of a scientific article on a study topic of interest for the students.
- The process of scientific knowledge: how to generate and verify a hypothesis. Why statistics is so important for health professionals?
- Descriptive statistics: definition of variable, frequencies
- Data synthesis: measures of position, variability, symmetry
- Probability and known distributions: binomial and normal distributions
- Population and sample. Elements of sampling theory: definition, simple random sample, clustering, stratification. Central limit theorem and probability distribution for the sample mean
- Elements of statistical inference: general theory for hypothesis test
- Test on the mean of one population, test on the mean of two populations
- Confidence intervals
Lesson notes on the web (e-learning)