Course catalogue doctoral education - VT22

  • Application can be done between 2021-10-15 and 2021-11-15
Application closed
Title Basic Course in Medical Statistics
Course number 3134
Programme 0-Not part of doctoral programme
Language English
Credits 3.0
Notes The course meets the requirements for a general science course.

Date 2021-10-18 -- 2021-10-29
Responsible KI department Department of Learning, Informatics, Management and Ethics
Specific entry requirements
Purpose of the course The aim of the course is to introduce the basic statistical methods and the fundamental principles of statistical inference and to offer basic skills that involve hands on data analysis using statistical software.
Intended learning outcomes The course participants shall after the course be able to; 1) perform and interpret basic descriptive statistics from frequency tables and graphical presentations, 2) perform and interpret results from basic inferential statistical analysis and tests, 3) recognize and critically examine the statistics being presented in articles within the medical field of research.
Contents of the course Concepts being treated are descriptive vs inferential statistics, collection of data and study design, different types of data and level of measurement, independent and dependent samples, correlation and regression, hypothesis testing and different type of statistical errors in relation to the testing and data collection procedure. The major topics for the course are t-test, chi-square test, nonparametric test and regression analysis, and how to evaluate the assumptions for the different techniques.
Teaching and learning activities This course is a Team-Based Learning (TBL) course. TBL is a specific form of learning method that integrates individual assessment and group work with immediate feedback. Focus will be on solving statistical problems in a team setting. This two weeks course consists of online preparation through video lectures and exercises, and several TBL sessions (in class meeting). The time in between TBL sessions will be spent reading the course material, and preparing for the assessment and group application exercises.
Compulsory elements In class attendance during TBL sessions are mandatory for passing grade. If a student misses one of the five TBL sessions a supplementary exercise will be given. If the student misses more than one TBL session it is recommended that the student takes the course at another occasion (since absence also affects the other members of the team).
Examination Individual and group readiness assurance tests, as well as application exercises.
Literature and other teaching material Medical Statistics - A textbook for the health sciences, 4th edition, Wiley by Michael J. Campbell et al. (2007).

Other recommended literature on basic statistics:
Essential medical statistics, Betty R. Kirkwood & Jonathan A.C. Sterne, Blackwell, (2003).
Intuitive Biostatistics, 1st edition, Oxford University Press by Harvey Motulsky, (2009).
Medical statistics at a glance, 1st edition, Blackwell Science by Aviva Petrie & Caroline Sabin, (2000).
An Introduction to Medical Statistics, 3rd edition, Oxford University Press by Martin Bland, (2000).
Number of students 35 - 45
Selection of students Selection will be based on: 1) start date of doctoral studies (priority given to earlier start date), 2) the relevance of the course syllabus for the applicant's doctoral project/post doctoral research (according to written motivation).
More information This course is a TBL-course, former course number was 1383. TBL, Team-Based Learning, is a special form of learning that integrates individual work, group work and immediate feedback. Focus will be on solving statistical problems in group/team setting. The course will consist of 2-3 full days per week for two weeks. Course dates (via Zoom) are: October 18-19, 21 and October 25, 27, 29.
Additional course leader Mesfin Tessma
Latest course evaluation Course evaluation report
Course responsible Mesfin Tessma
Department of Learning, Informatics, Management and Ethics
Contact person Karin Wrangö
Institutionen för lärande, informatik, management och etik