As an introduction to inferential statistics, the concept of sampling distribution is explained, with the following examples: random sample proportions, random sample averages and the central limit theorem, and finally random sample variance. These concepts then lead to the setting up of reliability intervals and hypothesis testing. After a general introduction on testing, we deal with the most important tests for location, dispersion and distribution for different measurement scales and for 1, 2 or more than 2 populations respectively. The principles of equivalence tests and optimal design of experiments are also discussed. The course is entirely based on (business-)economic applications. All concepts and calculations are illustrated by means of the software package JMP.