# NMAK14003U Applied Statistics

Volume 2014/2015
Education
MSc Programme in Agriculture
Content

Each student carries out a statistical project (in a group) related to an experiment or a numerical investigation preferably delivered by one of the students in the group. A report is written in journal style and presented orally. Besides, a small number of statistical themes are taught. Examples of such themes are multi-way ANOVA, random effects, analysis of repeated measures and cross-over trials, analysis of count data or ordinal data, analysis of data with detection limit, simulation methods, non-linear regression models, analysis of time series data, Markov models. There will also be some discussion of statistical methods relevant to application areas such as biology, chemistry, computer science, nutrition, and sport science.. The statistical themes as well as the application areas may vary somewhat from year to year and to some extent adapt to the interests of the students.

Learning Outcome

The course aims at giving the student experience of carrying out statistical analyses. The topics (methods) taught may vary from year to year.

After completing the course the student should be able to:

Knowledge:

- recognize certain data types, identify and specify appropriate statistical models, and argue for the appropriateness

- explain the prerequisities, prospects and limitations of the methods

Skills:

- formulate relevant problems and choose an appropriate statistical model addressing these problems

- carry out the actual analysis (computations). This includes 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

Competences:

- 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.

During the first half of the course lectures and practical (computer) exercises will run parallel with the initial part of the project work, while the second half will concentrate on the projects. In the last week the students will present their projects orally and give critique to one of the other projects.
• Category
• Hours
• Exam
• 2
• Guidance
• 5
• Lectures
• 20
• Practical exercises
• 20
• Preparation
• 69
• Project work
• 80
• Theory exercises
• 10
• Total
• 206
Credit
7,5 ECTS
Type of assessment
Written assignment
Oral examination, 30 minutes
Description of Examination: Each group writes a report in a journal paper format about their project. At the end of the course each student is examined individually. The grade is awarded on the basis of an overall assessment of the report and the oral exam.
Aid
All aids allowed
Marking scale
passed/not passed
Censorship form
No external censorship
Several internal examiners
##### Criteria for exam assesment

Quality of written report with focus on describing and using appropriate statistical methods. Quality of oral presentation with focus on presenting key methodology and results.
The student must in a satisfactory way demonstrate that he/she has mastered the learning outcome of the course.