Course catalogue doctoral education - VT21

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Title Biostatistics I: Introduction for Epidemiologists
Course number 3042
Programme Epidemiologi
Language English
Credits 3.0
Notes The course meets the requirements for a general science course.

Date 2021-04-07 -- 2021-04-27
Responsible KI department Institutet för miljömedicin
Specific entry requirements
Purpose of the course The aim is to introduce classical statistical concepts and methods with emphasis on methods for continuous outcome data.
Intended learning outcomes After successfully completing this course, students should be able to:
- define the concept of probability, laws of probability, and make simple probability calculations,
- suggest a statistical distribution to describe a naturally occurring phenomenon and evaluate the appropriateness of the distribution given real data,
- present appropriate tabular and graphical descriptions of study data,
- explain the difference between hypothesis testing and interval estimation and the relation between p-values and confidence intervals for the mean,
- explain the necessary assumptions for inference under various tests for continuous data,
- fit and interpret the coefficients of linear regression, with or without adjustment, with or without an interaction,
- explain and apply non-parametric tests for differences in distribution,
- explain the concepts of confounding and effect modification, describe the difference between them and use models correctly to account for them.
Contents of the course The course introduces classical statistical concepts and methods with emphasis on methods used in epidemiology and public health. Topics covered include: the importance of statistical thinking; types of data (nominal, binary, discrete and continuous variables); data summary measures; graphical representations; notions of probability; probability models (distributions); principles of statistical inference for the mean via the central limit theorem, concepts of confidence intervals and hypothesis tests; and an introduction to linear regression.
Teaching and learning activities Lectures, exercises focusing on analysis of real data using statistical software, exercises not requiring statistical software, group discussions, literature review.
Compulsory elements
Examination To pass the course, the student has to show that the intended learning outcomes have been fulfilled. The course grade is based on the individual written examination. Students who fail will be offered a re-examination within two months of the final day of the course. Students who fail the re-exam will be given top priority for admission the next time the course is offered. If the course is not offered during the following two academic terms then another re-examination will be scheduled within 12 months of the final day of the course.
Literature and other teaching material Recommended texts:
Kirkwood BR. Essentials of Medical Statistics. 2th ed. John Wiley & Sons; 2003.
Rabe-Hesketh S, Everitt BS. A Handbook of Statistical Analyses Using Stata. 4th ed. College Station: Stata Press; 2006.
Juul S. An Introduction to Stata for Health Researchers. College Station: Stata Press; 2006.
Dawson B, Trapp R. Basic & Clinical Biostatistics. 4th ed. McGraw-Hill Medical; 2004
Woodard M. Epidemiology: Study Design and Data Analysis. 2nd ed. Chapman & Hall;2004
Number of students 8 - 25
Selection of students Eligible doctoral students are prioritized according to 1) the relevance of the course syllabus for the applicant's doctoral project (according to written motivation), 2) date for registration as a doctoral student. Give all information requested, including a short description of current research training and motivation for attending, as well as an account of previous courses taken. Prior knowledge in any software, e.g. Stata, R or SAS is strongly recommended.
More information The course is extended over time in order to promote reflection and reinforce learning. Course dates are April 7, 8, 9, 12 and 13 (week 1) and April 21, 22, 23, 26 and 27 (week 2).
Additional course leader Matteo Bottai, Institute of Environmental Medicine will be teaching week 1 and Nicola Orsini, Department of Global Public Health will be teaching week 2.
Latest course evaluation Course evaluation report
Course responsible Matteo Bottai
Institutet för miljömedicin
08-524 870 24
matteo.bottai@ki.se
Contact person Johanna Bergman
Institutet för miljömedicin

johanna.bergman@ki.se

Nobels väg 13

17177
Stockholm