Login for PhD students at UCPH
Login for others
Home
Course Catalogue
Communication & Teaching
Online Courses
Responsible Conduct of Research
Specialist Courses
Statistics
Summer Schools
PhD Supervision for Academic staff
Course fee, cancellation policy and invoice details
How to apply for a course
PhD students from Nordic universities
Newly enrolled PhD students at SUND
PhD students at UCPH
Other applicants
How to log on to the course system
How to log in as a student
How to log in as a course provider
Contact information
Processing...
Basic Statistics for Health Researchers (Danish course)
Provider: Faculty of Health and Medical Sciences
Activity no.: 3304-18-00-01
Enrollment deadline: 15/12/2017
Date and time
15.01.2018, at: 12:00 - 21.03.2018, at: 15:00
Regular seats
25
Course fee
5,640.00 kr.
Lecturers
Lene Theil Skovgaard
ECTS credits
11.00
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.
Learning objectives
A student who has met the objectives of the course will be able to:
After finishing the course, the participants will
1. have a general feeling for the ideas in a statistical model and the type of conclusions that can be drawn from the subsequent statistical analysis
2. be able to understand and interpret the results of basic statistical procedures (t-test, associations in 2x2 tables, linear regression, multiple linear regression, logistic regression, survival analysis)
3. know the assumptions involved in the basic statistical procedures, and why these are not all equally important, depending on the aim of the analysis
4. be able to carry out these basic statistical procedures using one of the mainstream statistical software packages
5. have required tools for detecting gross misfit of the model and make remedies such as transformation of outcome and/or covariates
6. have a thorough understanding of the concepts of confounding and interaction, preferably in the context of their own work
7. know about estimation of association parameters, statistical significance and power, so that they can write the statistical methods and results sections for their own research reports (limited to basic statistical procedures)
8. know when to seek expert help.
The participants are invited to bring their own data to the exercises, since in quiet moments during the practical exercises, there will be a limited access to discuss these in the light of the topics covered in the course.
Content
Topics covered: Basic statistical concepts (probability, distribution, estimation, test of significance). Analysis of quantitative measurements (group comparisons, regression and the general linear model). Sample size determination. Categorical data (association in two-way tables, logistic regression analysis). Survival analysis (Kaplan-Meier, Cox regression). Correlated measurements, longitudinal data.
Use of statistical software:
In the lectures, we show output from SAS and provide SAS code for many of the examples used.
In the exercises:
For course 0, 1 and 2, SAS is used for examples and exercise solutions.
For course 3, we use SPSS for the exercises.
R and STATA may also be used but only if you have the necessary experience.
The participants are encouraged to bring their own laptops during the course, and must in that case download the necessary software before the beginning of the course. They are also encouraged to install Eduroam in order to have Internet access during the exercises. Otherwise, data for use in the exercise class must be downloaded before coming to the class. There will be stationary computers available for use instead of personal laptops, but you will not be able to save your data on those.
As a Ph.D.-student, you have access to download SAS, SPSS and Eduroam from the Self Service pages on KU-net, free of charge.
Participants
Ph.D. students. In case of vacant seats also other health researchers. Max. 25 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
Danish
Form
10x 3 hr forum lectures and 10 x3 hr class exercises.
Compulsory home exercise.
Course director
Associate professor Lene Theil Skovgaard
Teachers
Associate professors Lene Theil Skovgaard, Susanne Rosthøj plus external teachers.
Dates
15, 17, 22, 24, 29, 31 January, 5, 7, 12, 14, 19, 21, 26, 28 February, 5, 7, 12, 14, 19, 21 March 2018, all days 12-15.
Please note: SAS will be used for exercises
Course location
CSS
Registration
Please register before 15 December 2017.
If you have been assigned a seat on one of the courses, your place on the waiting list for all other courses will be cancelled. Therefore, only apply for courses you can participate on and with the use of the right statistical software.
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.
Search
Click the search button to search Courses.
Choose course area
Course Catalogue
Choose sub area
Communication & Teaching
Online Courses
Responsible Conduct of Research
Specialist Courses
Statistics
Summer Schools
PhD Supervision for Academic staff
Course calendar
See which courses you can attend and when
Jan
Feb
Mar
Apr
May
Jun
Jul
Aug
Sep
Oct
Nov
Dec
Processing...
RadEditor - HTML WYSIWYG Editor. MS Word-like content editing experience thanks to a rich set of formatting tools, dropdowns, dialogs, system modules and built-in spell-check.
RadEditor's components - toolbar, content area, modes and modules
Toolbar's wrapper
Paragraph Style
Font Name
Real font size
Apply CSS Class
Custom Links
Zoom
Content area wrapper
RadEditor hidden textarea
RadEditor's bottom area: Design, Html and Preview modes, Statistics module and resize handle.
It contains RadEditor's Modes/views (HTML, Design and Preview), Statistics and Resizer
Editor Mode buttons
Statistics module
Editor resizer
Design
HTML
Preview
RadEditor - please enable JavaScript to use the rich text editor.
RadEditor's Modules - special tools used to provide extra information such as Tag Inspector, Real Time HTML Viewer, Tag Properties and other.
N
ew courses
Courses are published regularly. High demand courses are announced in spring and autumn.
Learn which courses are announced on fixed dates