Syllabus database for doctoral courses
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Syllabus database for doctoral courses
SYLLABI FOR DOCTORAL COURSES
| Swedish title | Biostatistik I: Introduktion för psykiater |
|---|---|
| English title | Biostatistics I: Introduction for psychiatrists |
| Course number | 2729 |
| Credits | 1.5 |
| Notes |
The course meets the requirements for a general science course. |
| Responsible KI department | Institutionen för klinisk neurovetenskap |
| Specific entry requirements | |
| Grading | Passed /Not passed |
| Established by | Styrelsen för forskarutbildning |
| Established | 2016-10-25 |
| Purpose of the course | The purpose of this course is to acquire basic knowledge in statistics in a broader sense, but also more specifically in terms of the statistical procedures that are common in psychiatric research. The student will after the course be able to choose statistical analysis methods that are appropriate for specific research questions, conduct analysis and interpret results adequately. |
| 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 | Examination moment. Attendance to all the lectures are compulsory and missed lecture will be complemented with a relevant assignment related to the topic missed. |
| Examination | The course grade is based mainly on a written examination, but group tasks and individual written assignments are also used. The written examination will mainly test the abilities to choose the appropriate statistical method in different settings, to carry out the tests using statistical software or by hand and to interpret the results and draw reasonable conclusions.Students who fail will be offered a re-examination within 2 months of the final day of the course. |
| Literature and other teaching material | Bring, Johan, Taube, Adam & Wikman, Per (2015). Introduktion till medicinsk statistik. 2., utök. uppl. Lund: Studentlitteratur. | Course responsible |
Helena Fatouros-Bergman Institutionen för klinisk neurovetenskap Helena.Fatouros-Bergman@ki.se |
| Contact person |
