Course catalogue doctoral education - VT18

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Title Biostatistics I: Introduction for epidemiologists
Course number 1579
Program Epidemiologi
Language English
Credits 3.0
Notes The course meets the requirements for a general science course.

Date 2017-09-20 -- 2017-10-12
Responsible KI department Institutionen för medicinsk epidemiologi och biostatistik
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.
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
Number of students 8 - 25
Selection of students Eligible doctoral students, with required prerequisite knowledge, will be selected based on 1) the relevance of the syllabus for the applicant's doctoral project (according to written motivation), and 2) date for registration as doctoral student (priority given to earlier registration date). To be considered, submit a completed application form. Give all information requested, including a description of current research and motivation for attending, and an account of previous courses taken.
More information The course is extended over time in order to promote reflection and reinforce learning. The course will be given the following dates: week1: September 20-September 26, Exam 1: September 28; week2: October 4-October 10, Exam 2: October 12. We strongly recommend prior knowledge in Stata software.
Additional course leader
Earlier evaluation of the course Evaluation report
Course responsible Yudi Pawitan
Institutionen för medicinsk epidemiologi och biostatistik

Yudi.Pawitan@ki.se
Contact person Gunilla Nilsson Roos
Institutionen för medicinsk epidemiologi och biostatistik
08-524 822 93
gunilla.nilsson.roos@ki.se