1.1 Learning goals

At the end of this course students should:

• have gained the competence to
  • understand complex data sets,
  • manipulate a data set (using R), so as to
  • plot aspects of it in ways that are useful for answering a given research question
• understand the general logic of statistical inference, in particular
  • be able to interpret and apply standard analyses from a frequentist and a Bayesian approach
• be able to independently evaluate statistical analyses based on their adequacy for a given research question and data set
• be able to critically assess the adequacy of analyses commonly found in the literature

Notice that this is, although a lot of hard work already, still rather modest! It doesn’t actually say that we necessarily aim at the competence to do it or even to do it flawlessly! Our main goal is understanding, because that is the foundation of practical success and the foundation of an ability to learn more in the future. We do not teach tricks! We do not share recipes!