Graduate School of health and Medical Sciences

Statistics for experimental medical researchers
Provider: Faculty of Health and Medical Sciences

Activity no.: 3325-19-00-00
	Enrollment deadline: 05/04/2019

Date and time	07.05.2019, at: 08:00 - 04.06.2019, at: 15:00
Regular seats	40
Course fee	3,000.00 kr.
Lecturers	Julie Forman
ECTS credits	4.30

Contact person	Susanne Kragskov Laupstad E-mail address: skl@sund.ku.dk


Aim and content This is a generic course. This means that the course is reserved for PhD students at the Graduate School of Health and Medical Sciences at UCPH. Anyone can apply for the course, but if you are not a PhD student at the Graduate School, you will be placed on the waiting list until enrollment deadline. After the enrolment deadline, available seats will be allocated to the waiting list. The course is free of charge for PhD students at Danish universities (except Copenhagen Business School). All other participants must pay the course fee. Course title Statistics for experimental medical researchers Aim This five-day intensive course is aimed at biomedical research students at the Ph.D. level working in a laboratory or similar, performing experiment on e.g. mice, cells, or tissues. The participant will get a working knowledge of statistical concepts, models, and methods of analysis, as well as hands on experience in analysing data from medical laboratory experiments with R statistical software. Learning objectives A student who has met the objectives of the course will be able to: After participating in this course, the participant will be able to: Distinguish the statistical models most frequently encountered in experimental research. 1. Apply these models to his or her own data using the statistical software R. 2. Interpret the output from statistical software packages in general (not just R). 3. Present the results from these statistical analyses in numbers, words, and figures. 4. Judge the validity of these analyses by knowing which model assumptions are important and how to check them. 5. Seek expert statistical advice when needed and engage in a qualified statistical discussion. Content Data types, numerical and graphical descriptive statistics. Basics of statistical inference: significance tests and confidence intervals. Proper and improper use of p-values. Reproducible research. Statistical power. The two-sample and the paired t-test. Frequency distributions. Risk differences, risk ratios, and odds ratios. The chi-square test. Linear regression and correlation. Analysis of variance. Random effects models for repeated measurements (brief introduction). Statistical software We will be working with the open source statistical software R and the likewise free interface R Studio. Participants must bring their own laptops with R and R Studio installed for the exercises. Prerequisites No pre-knowledge of statistics is formally required, but we cover many topics in few days and at good pace. To be able to do the exercise and solve the homework problems, we strongly recommend that students make themselves familiar with basic R programming as in the Ph.D.-course Use of the statistical software R, or the free access e-learning course developed by Susanne Rosthøj at the Section of Biostatistics (https://absalon.ku.dk/courses/29790). Participants Ph.D.-students. In case of vacant seats also other medical researchers. Max. 40 participants. Relevance to graduate programmes The course is relevant to PhD students from the following graduate programmes at the Graduate School of Health and Medical Sciences, UCPH: All graduate programmes Language English. Form Forum lectures and computer exercises 3 hours in the morning 3 hours in the afternoon. Course director Associate professor Julie Forman, Section of Biostatistics Teachers Associate professors Julie Forman and others. Dates 7, 14, 21, 28 May, 4 June 2019, all days 8-15. Course location CSS Registration Please register before 5 April 2019 Seats to PhD students from other Danish universities will be allocated on a first-come, first-served basis and according to the applicable rules. Applications from other participants will be considered after the last day of enrolment. Note: All applicants are asked to submit invoice details in case of no-show, late cancellation or obligation to pay the course fee (typically non-PhD students). If you are a PhD student, your participation in the course must be in agreement with your principal supervisor.

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