Graduate School of health and Medical Sciences

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

Activity no.: 3325-18-00-00
	Enrollment deadline: 26/03/2018

Date and time	26.04.2018, at: 08:00 - 31.05.2018, at: 15:00
Regular seats	36
Course fee	3,120.00 kr.
Lecturers	Julie Forman
ECTS credits	4.30

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

Enrolment Handling/Course Organiser	PhD administration E-mail address: phdkursus@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. Aim and contents 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 After participating in this course, the participant will be able to: ? Distinguish the statistical models most frequently encountered in experimental research. ? Apply these models to his or her own data using the statistical software R. ? Interpret the output from statistical software packages in general (not just R). ? Present the results from these statistical analyses in numbers, words, and figures. ? Judge the validity of these analyses by knowing which model assumptions are important and how to check them. ? 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. Frequency distributions. Risk differences, risk ratios, and odds ratios. The chi-square test. The two-sample and the paired t-test. Analysis of variance. Linear regression and correlation. Random effects models for repeated measurements. Depending on student interests some of the following optional topics might be covered: Multiple testing procedures. Power calculations. Experimental design. Dose-response modelling. Analysis of baseline follow-up studies. 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 similar. Participants Ph.D.-students. In case of vacant seats also other medical researchers. Max. 36 participants. 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. Course secretary Susanne Kragskov Laupstad, Section of Biostatistics, e-mail: skl@sund.ku.dk Dates 26 April, 3, 8, 24, 31 May 2018, all days 8-15. Course location CSS Registration: Please register before 26 March 2018. Admission to Ph.D. students from Danish universities will be allocated on a first-come, first-served basis and according to the rules in force. Applications from other participants will be considered after 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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