Populations and samples; datatypes; description of data: histograms, measures of centre and spread.

Basics of probability: probabilitymodels, random variables, probability distributions and their properties:binomial, Poisson and normal distribution. Indipendence.

Parameter estimates; confidenceintervals; one and two sided confidence intervals of the mean.

Hypothesis testing; comparing onemean with a fixed one, or comparing two means; size of the sample and power of the test. Test ofindependence of two factors.

Introduction to analysis ofvariance and regression models.

Students will be invited toperform statistical computation through computer software (esp. Excel or R,depending on aims), but this will not be described in detail in the course.