Course syllabus for Applied biostatistics
Tillämpad biostatistik
Versions of this syllabus:
Essential data
Specific entry requirements
A Bachelor's degree or a professional degree worth at least 180 credits in biomedicine, biotechnology, cellular and molecular biology, medicine, or the equivalent. Proficiency in English equivalent to the Swedish upper secondary school course English 6/English B.
Outcomes
The main aim of the course is to equip students with statistical concepts and tools for relating biological outcomes to multiple possible explanatory variables.
The course will mainly focus on regression modelling.
Upon completion of the course the student should be able to:
Regarding knowledge and understanding
- explain the concept of random variation in biological phenomena as it relates to experimental and observational studies in research
- describe appropriate statistical methods to quantify random and systematic effects in complex biological data
- discuss the distinction between explanatory and predictive modelling
Regarding competence and skills
- choose and fit multivariate regression models of intermediate complexity using a standard statistical software package
- utilize R programming for data analysis and statistical model building, and interpret the results.
Regarding judgement and approach
- evaluate and integrate empirical evidence in relation to biostatistical problems and biostatistical literature
- demonstrate insights into the ethical dimensions of statistical analysis and how findings are reported
Content
Randomness of biological observations. Experimental and observational data. Types of data: nominal, ordinal, continuous variables. Data summary measures. Graphical representations. Concepts of probability and probability distributions. Parameter estimation: mean, proportion, standard deviation, standard error. Concepts of statistical inference: confidence intervals and hypothesis tests. Elementary parametric hypothesis tests. Univariate linear regression. Multivariate linear regression and general linear model. Continuous and categorical predictors. Role of covariates. Interactions. Nonlinear effect of covariates. Model fitting and diagnostics. Generalised linear models and logistic regression. Survival analysis and Cox proportional hazard models. Quantile regression. Models for longitudinal data. Use of R in data analysis, visualization, and statistical modeling, supported by hands-on training with R functions and packages.
Teaching methods
Teaching is in the form of lectures, practical computer activities and assignments.
Examination
The examination, which is graded Fail/Pass/Pass with distinction, consists of a written examination.
Compulsory participation
The examiner assesses if and, in that case, how absence from compulsory components can be compensated. The student must participate in all compulsory parts or compensate for absence in accordance with the examiner's instructions, in order to pass the course. Absence from a compulsory activity may result in the student not being able to compensate the absence until the next time the course is given.
Limitations of the number of examinations or practical training sessions
A student who does not pass an examination at their first attempt is entitled to participate in five additional examination sessions. If the student does not pass after four examinations, he/she is recommended to retake the course at the next regular course occasion, and may, after that, participate in two more examination sessions. If the student has failed six examinations, no additional examination sessions are provided.
Physically attending or otherwise commencing an examination is regarded as an examination session. Handing in a blank exam is considered taking part in an examination session. An examination, for which the student registered but did not participate, is not counted as an examination session.
Adaption of examination
If there are special grounds, or a need for adaptation for a student with a disability, the examiner may decide to deviate from the syllabus's regulations on the examination form, the number of examination opportunities, the possibility of supplementation or exemptions from the compulsory section/s of the course etc. Content and learning outcomes as well as the level of expected skills, knowledge and abilities may not be changed, removed or reduced.
Other directives
The course language is English and examination is performed in English.
Course evaluation will be carried out in accordance with the guidelines established by the Committee for Higher Education.
Oral evaluation in the form of course council meetings will be carried out during the course.
Literature and other teaching aids
Recommended literature
- Altman, Douglas G., Practical statistics for medical research, London : Chapman and Hall, 1991 - xii, 611 s. ISBN: 0-412-38620-8 (hft.), LIBRIS-ID: 8286190,
- Bland, Martin, An introduction to medical statistics, 3. ed., [Nachdr.] : Oxford : Oxford University Press, 2009 - XVI, 405 S ISBN: 978-0-19-263269-2, LIBRIS-ID: 11926588,
- Dalgaard, Peter, Introductory statistics with R, 2. ed. : New York : Springer, cop. 2008 - xvi, 363 s. ISBN: 978-0-387-79053-4 (pbk. : alk. paper), LIBRIS-ID: 11305121,
- Pagano, Marcello; Gauvreau, Kimberlee, Principles of biostatistics, 2. ed. : Pacific Grove : Duxbury, cop. 2000 - xvi, 525 s. , [42] s. ISBN: 0-534-22902-6 ; No price, LIBRIS-ID: 5036554,
- Rosner, Bernard, Fundamentals of biostatistics, 6. ed. : Belmont, Calif. : Thomson/Brooks/Cole, cop. 2006 - xx, 868 p. ISBN: 0534418201, LIBRIS-ID: 9942420,