Faculty of Science

Applied biostatistics in biological sciences using R - with focus on applications in nutrition, physiology, and plant and environmental sciences - Module 2
Provider: Faculty of Science

Activity no.: 5485-19-06-31
	Enrollment deadline: 26/08/2019

Date and time	23.09.2019, at: 00:00 - 00:00
Regular seats	25
Course fee	0.00 kr.
ECTS credits	3.00

Contact person	Signe Marie Jensen E-mail address: smj@plen.ku.dk

Enrolment Handling/Course Organiser	Christian Ritz E-mail address: ritz@nexs.ku.dk
Exam form	Written assignment
Exam details	A written project report has to be submitted 4 weeks after the teaching week for module 1. Research questions should be defined during a consultation with one of the course instructors in the first week after module 1 and should relate to the participants own research and/or area of work. Participants are expected to bring their own data for the report. Reports should be article-style but with enhanced statistics sections and reduced introduction and discussion (5-10 pages, 1½ line spacing, 12 pt., excl. figures). The reports will be examined by the course coordinators (passed/not passed) based on a number of formal requirements to be announced during the course.
Grading scale	Passed / Not passed

Content The course will introduce the PhD student to a broad range of statistical analyses that are used for analysis of various types of biological data and on how to perform the analysis in the statistical software R. The participants will be introduced to statistical methods for analysis of continuous and categorical data and also univariate and multivariate data. The course is divided in 2 modules: 1 - Lectures and exercises 2 - Project on own data It is a prerequisite for module 2 that module 1 is followed the same year. In module 2, participants will work on their own data, on their own but with supervision from the teachers. Learning outcome Skills • To understand key concepts and ideas underlying a wide range of statistical methods • To interpret output and results from a wide range of statistical analyses Competences • To identify and apply appropriate R functionality for data analysis and visualization • To define statistical challenges for given data sets and limitations in the introduced statistical methodology Teaching and learning methods Work on own data based on a consultation with one of the course instructors. Lecturers • Course leader: Christian Ritz, Associate Professor, NEXS, e-mail: ritz@nexs.ku.dk • Course co-leader: Signe M. Jensen, Assistant Professor, PLEN, e-mail: smj@plen.ku.dk Workload Report - 70 hours Remarks Preparation We recommend that you prepare data for your report and spend a moment on defining the research questions related to you data. Time Report deadline: September 23, 2019 Location PLEN, UCPH, Frederiksberg Campus Exam form: A written project report has to be submitted 4 weeks after the teaching week for module 1. Research questions should be defined during a consultation with one of the course instructors in the first week after module 1 and should relate to the participants own research and/or area of work. Participants are expected to bring their own data for the report. Reports should be article-style but with enhanced statistics sections and reduced introduction and discussion (5-10 pages, 1½ line spacing, 12 pt., excl. figures). The reports will be examined by the course coordinators (passed/not passed) based on a number of formal requirements to be announced during the course. Course fee None. Remarks To enroll this course, please 1) Apply for module 1 2) Apply for module 2 3) Click on “apply” 4) Send a motivated application to smj@plen.ku.dk mentioning when you started your PhD project (for PhD students) and including a description of the data you expect to use for your report. The description should resemble the method part of a research paper (excluding the statistical analysis part) but in a condensed form. Application deadline: July 20, 2019.

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