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SYLLABI FOR DOCTORAL COURSES

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Swedish title Biostatistik I: Introduktion för epidemiologer
English title Biostatistics I: Introduction for epidemiologists
Course number 3154
Credits 3.0
Notes The course meets the requirements for a general science course.

Responsible KI department Institutionen för medicinsk epidemiologi och biostatistik
Specific entry requirements
Grading Passed /Not passed
Established by The Board of Doctoral Education
Established 2018-09-05
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. (S2)
-suggest a statistical distribution to describe a naturally occurring phenomonen and evaluate the appropriateness of the distribution given real data. (S3)
-present appropriate descriptive statistics for an epidemiological study. (S2)
-explain the difference between hypothesis testing and interval estimation and the relation between p-values and confidence intervals. (S3)
-suggest an appropriate statistical test for a comparison of two groups, perform the hypothesis test using standard statistical software, and interpret the results. (S3)
-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. (S3)
-explain the concept of confounding in epidemiological studies and demonstrate how to control/adjust for confounding using stratified analysis. (S2)
-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. (S2)

Learning outcomes are classified according to Bigg's structure of the observed learning outcome (SOLO) taxonomy: (S1) uni-structural, (S2) multi-structural, (S3) relational, and (S4) extended abstract.
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
Course responsible Erin Gabriel
Institutionen för medicinsk epidemiologi och biostatistik


erin.gabriel@ki.se

Contact person Gunilla Nilsson Roos
Institutionen för medicinsk epidemiologi och biostatistik
08-524 822 93

gunilla.nilsson.roos@ki.se