Introduction to applied statistics and R for PhD students

• Perform descriptive analyses, including descriptive plots, to describe data.
• Generate a statistical hypothesis based on a practical problem.
• Differentiate between the choice of different statistical methods.
• Formulate and apply common statistical regression models.
• Perform statistical model check.
• Perform estimation and hypothesis test in commonly used statistical models.
• Interpret the results from commonly used statistical models and relate the results to the practical application.
• Perform simple statistical analyses using R.
• Interpret output from analyses using R.
• Critical assessment of results from statistical analyses.
• Document and present results in a written report to persons without a statistical background.
• Plan, perform and present a simple statistical analysis.

Basic statistical methods and ideas will be taught with emphasis on applications and the interpretation of results and their relationship to the applications. Specific content is Statistical inference and t-tests, simple and multiple linear regression, one- and two-way analysis of variance, analysis of covariance and linear models, categorical data, logistic regression, principal components analysis, statistical report writing and an optional topic. There will be a practical project based on the participants’ own data consisting of planning, performing and presenting a statistical analysis.

The course is aimed at PhD students, who have taken a statistics course during their studies, but have not used it and therefore need statistics refreshed from scratch.
It will be an advantage (but not a requirement) to have taken a basic programming course.

The course has two parts. First there will be a week of class room teaching with lectures and exercises. This will be followed by a two week period where a project is completed under supervision, preferably based on the participants’ own data. During the project period there will be group sessions with a supervisor. Before the start of the main course one day will be given with an introduction to the statistical program R.

Mandatory presence for lectures in statistics: Minimum 4 out of 5 days, not counting the introduduction.

Minimum: 6, Maximum: 30.

Please be aware that this course has a minimum requirement for the number of participants needed, in order for it to be held. If these requirements are not met, then the course will not be held. Furthermore, there is a limited number of seats available. If there are too many applicants, a pool will be created for the remainder of the qualified applicants, and they will be selected at random. You will be informed 8 days before the start of the course, whether you have been allocated a spot.