| Responsible Department | Department of Food Science
50 % Department of Basic Science and Environment 50 % | ||||||||||||||||
| Research School | FOOD Denmark | ||||||||||||||||
| Course Dates | Annually, one week course dates to be announced Dates for the course 2010/2011: 27th June - 1st July, 2011 | ||||||||||||||||
| Course Abstract | The course is a 5-day course with the main objective of being a starting point to understand and start using several basic tools for data analysis and statistics. The course offers a perfect platform for students and researchers to start handling and managing the scientific data by themselves. Nowadays, many PhD projects include data handling and Chemometrics. The course gives a first impression about the possibilities of R and MATLAB, as well as an introduction to statistics and Chemometrics | ||||||||||||||||
| Course Home Page | http://www.chance.life.ku.dk/ | ||||||||||||||||
| Course Registration | To sign up for the course, please send an e-mail to Ditte Carlsen (CHANCE@life.ku.dk) or to José Manuel Amigo (jmar@life.ku.dk) | ||||||||||||||||
| Deadline for Registration | Latest two weeks before the starting date (to be announced) | ||||||||||||||||
| Credits | 3 (ECTS) | ||||||||||||||||
| Level of Course | PhD course | ||||||||||||||||
| Language of Instruction | English | ||||||||||||||||
| Course Content | |||||||||||||||||
| The course will be divided into theoretical and practical sessions. The theoretical sessions will be held during the morning. During the afternoon, the students will work on several examples. The content of the course is: 1st day - Introduction to R interface. 2nd day - Statistics with R. 3rd day - Introduction to MATLAB interface 4th day - Principal Components Analysis with MATLAB. 5th day - Personal work. Examination day | |||||||||||||||||
| Teaching and learning Methods | |||||||||||||||||
| - Teaching: the basis of the course teaching will be done by lectures in powerpoint + examples with the computer. The students will be able to follow all the master exercises in their own computers. - Learning: Apart from the exercises presented at class, the students will be given several exercises that they must solve individually in the final report. - Educational approaches: The background of the students may be totally different: Chemistry, Food Science, Technical careers, etc. The course may be the basis for the students to start using R, MATLAB and some Chemometric tools in their own future job and research. | |||||||||||||||||
| Learning Outcome | |||||||||||||||||
| Knowledge, skills, competences: - MATLAB and R interfaces: They will be able to "move" by themselves in the most important utilities and windows in MATLAB and R interfaces. - Chemometrics: They will be able to apply the basic Chemometric tools: Principal Component Analysis and Partial Least Squares regression. - Statistics: The students will learn how to apply different statistics methods by using R interface. | |||||||||||||||||
| Course Literature | |||||||||||||||||
| Handouts and scientific papers provided during the course. | |||||||||||||||||
| Course Material | |||||||||||||||||
| Handouts and scientific papers provided during the course; scripts and source code provided during the course. | |||||||||||||||||
| Course Coordinator | |||||||||||||||||
| Jose Manuel Amigo Rubio, jmar@life.ku.dk, Department of Food Science/Quality and Technology, Phone: 353-32570 | |||||||||||||||||
| Other Lecturers | |||||||||||||||||
| Prof. Rasmus Bro. Department of Food Scieneces, Quality and Tecnhology. Prof. Ib M. Skovgaard. Department of Basic Sciences and Environment. Associate Prof. Christian Bressen Pipper. Department of Basic Sciences and Environment. | |||||||||||||||||
| Type of Evaluation | |||||||||||||||||
| Written report based on several problems proposed at class or in a study performed on their own data; work out by the participants individually. The reports have to be handed in maximally one week after the last lecture and are evaluated and credited with PASS/FAIL by the course lectures. | |||||||||||||||||
| Work Load | |||||||||||||||||
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