BB852: Data handling, visualization and statistics

Comment

04013901 + N110015101 (former UVA) is identical with this course description.

Entry requirements

None

Academic preconditions

Students taking the course are expected to:

Have basic knowledge of statistics and mathematics
Have a Bachelor’s degree in a field with some level or focus on quantitative methods

Course introduction

The aim of this course is to provide students with the tools to explore, analyse, and interpret data, and to present the results of biological studies.

The course builds on knowledge acquired in previous courses in mathematics and statistics.

The course gives an academic basis for work carried out in individual study activities and the masters project.

In relation to the competence profile of the degree it is the explicit focus of the course to:

Develop skills in data exploration, visualisation and interpretation.
Develop the students’ competence to undertake appropriate quantitative analysis of the student’s own data (e.g. masters project).
Develop skills to critically evaluate statistical analyses (e.g. in scientific papers/presentations).
Develop skills to use the R statistical software for analysis and graphing.
Structure personal learning

Expected learning outcome

The learning objectives of the course are that the student demonstrates the ability to:

formulate appropriate scientific questions in biological disciplines, e.g. ecology, physiology, neurobiology, and evolutionary biology.
design appropriate laboratory or field studies in order to address scientific questions.
manipulate and explore visually data from experimental and field studies.
select appropriate statistical approaches for a variety of different data types.
fit and interpret appropriate regression models (ordinary least squares, generalised linear models), randomisation tests, and “classical tests” (t-tests, chi-squared tests etc.).
understand and commonly used model selection approaches.
present quantitative the results from biological studies, including graphically.

Content

The following main topics are contained in the course:

Questions and hypotheses in research
Designing data collection for biological studies
Manipulating data with R (dplyr, tidyr, magrittr)
Visualising data with R (ggplot2)
Regression models, randomisation tests and “classical” tests
Model selection
Presenting results of statistical analyses

Literature

Beckerman, Childs & Petchey (2017) Getting Started With R. 2nd Edition. Oxford University Press.
Other literature uploaded to, or linked to, on Blackboard.
See Blackboard for syllabus lists and additional literature references.

Examination regulations

Exam element a)

Timing

Autumn

Tests

Take home exam

EKA

N110040102

Assessment

Second examiner: Internal

Grading

7-point grading scale

Identification

Student Identification Card

Language

Normally, the same as teaching language

Examination aids

To be announced during the course.

ECTS value

Additional information

Reexam in the same exam period or immediately thereafter.
The mode of exam at the re-examination may differ from the mode of exam at the ordinary exam.

Indicative number of lessons

48 hours per semester

Teaching Method

At the faculty of science, teaching is organized after the three-phase model ie. intro, training and study phase.

Activities during the study phase:

Computer-based exercises
Research oriented learning (guided exploration of data)
Reading relevant literature, or other written material (e.g. blog posts)

Teacher responsible

Name	E-mail	Department
Owen Jones	jones@biology.sdu.dk	Biologisk Institut

Timetable

Odense

Show full time table

Administrative Unit

Biologisk Institut

Team at Registration

NAT

Offered in

Odense

Recommended course of study

Profile	Education	Semester	Offer period
MSc major in biology - Registration 1 September 2020	Master of Science MSc in biology \| Odense	1	E20
MSc major in biology - Registration 1 September 2020	Master of Science MSc in biology \| Odense	1	E20