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Statistics for experimental medical researchers (online)
Provider: Faculty of Health and Medical Sciences
Activity no.: 3325-20-00-00
There are no available seats
Enrollment deadline: 14/04/2020
Date and time
12.05.2020, at: 08:00 - 09.06.2020, at: 15:00
Regular seats
40
Course fee
3,120.00 kr.
Lecturers
Julie Forman
ECTS credits
3.50
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), and for PhD students at graduate schools in the other Nordic countries. All other participants must pay the course fee.
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 (http://r.sund.ku.dk/).
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
12, 19, 26 May and 2, 9 June 2020
All days 8-15
Course location
CSS
Registration
Please register before 14 April 2020
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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