Program Overview

Program Overview

The Applied Statistics (AppStat) course is designed to provide students with hands-on experience in statistical analysis. The course covers various statistical themes, including data types, comparison of two samples, analysis of tables of counts, regression analysis, and more.

Course Content

The course content includes:

• Data types
• Comparison of two samples by parametric and non-parametric methods
• Analysis of tables of counts
• Regression analysis of categorical data
• Linear and multilinear regression
• Analysis of variance
• Basic design of experiments
• Usage of random effects
• Analysis of longitudinal data and of repeated measurements
• Practical techniques for analyzing data in the open source software package R using the RStudio interface

Learning Outcome

After completing the course, students should be able to:

• Recognize certain data types, identify and specify appropriate statistical models, and argue for the appropriateness
• Explain the prerequisites, prospects, and limitations of the methods
• Formulate relevant problems and choose an appropriate statistical model addressing these problems
• Carry out the actual analysis (computations), including model fitting, model validation, and hypothesis testing
• Extract relevant estimates, draw conclusions, and communicate the results from the analysis
• Use the statistical programming language R to carry out the analyses
• Independently formulate scientifically relevant questions motivated by data of similar types as those presented in the course and answer them by the use of statistical methods

Teaching and Learning Methods

The course will include lectures, practical exercises, and project work. During the first part of the course, lectures and practical exercises will run parallel with the initial part of the project work, while the second part will concentrate on the projects. At the oral exam, students will make individual conference-style presentations of their projects.

Recommended Prerequisites

Students must have followed an introductory course in statistics and therefore know the basic statistical concepts (variation, estimation, confidence intervals, hypothesis tests) and have experience with simple statistical models (at least one-way ANOVA, linear regression). Academic qualifications equivalent to a BSc degree are recommended.

Assessment

The course assessment includes:

• A written assignment (report in a journal paper format about the project)
• An oral examination (30 minutes, individual conference-style presentation of the project with emphasis on the statistical issues)
• The oral examination is without preparation and divided into 20 minutes presentation by the student and 10 minutes questioning from the examiner
• The grade is awarded on the basis of an overall assessment of the report and the oral exam
• All aids are allowed

Course Details

• Course type: Single subject courses (day)
• Workload:
  • Lectures: 24 hours
  • Preparation: 70 hours
  • Theory exercises: 24 hours
  • Project work: 84 hours
  • Guidance: 3 hours
  • Exam: 1 hour
• Language: English
• Course number: NMAK14003U
• ECTS: 7.5 ECTS
• Programme level: Full Degree Master
• Duration: 1 block
• Placement: Block 2
• Schedule group: C
• Capacity: 25
• Study board: Study Board of Natural Resources, Environment and Animal Science
• Contracting department: Department of Mathematical Sciences
• Contracting faculty: Faculty of Science
• Course Coordinator: Jonas Rysgaard Jensen

Timetable

The course is scheduled in block 2, with 25E-B2-2;Hold 01;;Applied Statistics.

Additional Information

For bachelor or kandidat students, the course information can be found in the course catalog for students. The University of Copenhagen is located at Nørregade 10, 1165 København K. The course is part of the Continuing and Lifelong Learning program.