Course catalogue doctoral education - VT18

  • Ansökan kan ske mellan 2017-10-16 och 2017-11-15
Application closed
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 2018-04-04 -- 2018-04-24
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 used in epidemiology and public health.
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 descriptive statistics for an epidemiological study.
- explain the difference between hypothesis testing and interval estimation and the relation between p-values and confidence intervals.
- suggest an appropriate statistical test for a comparison of two groups, perform the hypothesis test using standard statistical software, and interpret the results.
- estimate and interpret three alternative measures of association between binary exposures and binary outcomes and discuss the relative merits of each measure for a given research question.
- explain the concept of confounding in epidemiological studies and demonstrate how to control/adjust for confounding using stratified analysis.
- explain the basis of the linear regression model, fit a linear regression model using standard statistical software, assess the fit of the model, and interpret the results.
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; contingency tables; graphical representations; notions of probability; probability models (distributions); principles of statistical inference; parameter estimation (mean, proportion (prevalence), incidence and ratios); concepts of confidence intervals and hypothesis tests; and a general introduction to correlation and linear regression models.
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 The individual written examinations (summative assessments) are compulsory.
Examination The course grade is based on the two written examinations. The course is divided into two parts, and each part will be examined separately. To pass the course, the student must pass both parts. 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 Compulsory texts Kirkwood BR. Essentials of Medical Statistics. 2th ed. John Wiley & Sons; 2003. Recommended texts 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 will be 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 (priority given to earlier registration date). 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 Stata software is strongly recommended.
More information The course is extended over time in order to promote reflection and reinforce learning. The course will be held the dates April 4, 5, 6, 9 and 10 (week 1) and April 18, 19, 20, 23 and 24 (week 2). The individual examination will be performed as an in-class examination the last course day of each week.
Additional course leader
Earlier evaluation of the course Evaluation report
Course responsible Matteo Bottai
Institutet för miljömedicin
08-524 870 24
Contact person Johanna Bergman
Institutet för miljömedicin

Nobels väg 13