Content, progress and pedagogy of the module

Purpose
The course will support the students in the learning of classical statistical analysis of measured date.

Learning objectives

Knowledge

• Understanding of the classical methods of statistical analysis of quantitative and qualitative measurement data in connection with designed experiments, including:
  • Exploratory techniques for data analysis
  • Multi-variance analysis
  • Multiple regression analysis
  • Covariance analysis
  • Analysis of Latin squares
• and
  • Logistic regression analysis
  • Item-response analysis
  • Contingency table analysis (including 2-sided and 3-sided tables and conditional independence)

In addition, knowledge of graphical models

Skills

• The student should be able to use a software package for analysis and interpretation of data related to specific trials.

Competences

• Can identify and calculate relevant and simple empirical frequency and association and to assess their statistical uncertainty.
• Can compile, analyze and verify a statistical model for describing data from a designed experiment
• Can on basis on scientific hypotheses formulate, test and evaluate hypothesis corresponding statistical validity.
• Can disseminates the results of a statistical analysis and discuss implications of the analysis predictions.

Type of instruction

Extent and expected workload

Since it is a 5 ECTS course module, the work load is expected to be 150 hours for the student

Exam

Exams

Additional information

In collaboration with the supervisor the student can replace Statistics course with another approved course if it can  improve the student's profile. Application must be sent to the Board of Study.