3570.16 - Study Design and Data Analysis

Course number
Study Design and Data Analysis
Basic Statistics, 3-4 ects
To give the students statistical tools to use in data analysis and the confidence to use them, demonstrate the importance of well planned study design, and to show the students how the study plan is connected to the data analysis.
Formulating hypothesis, Sampling, Randomisation, Experimental designs, Statistical Power, Taking Measurements, Ethics, Probability, Discrete and Continuous Variables, Confidence Intervals, P-values, Statistical Tests, Fitting Models to Data, Analysis of Variance. Software R.
Learning and teaching approaches
Lectures, exercises, consulting, seminars and group project
Learning outcomes
After this course, the student can: o Explain the importance of study design o Explain the importance of randomisation and replication in sampling and its effect on data analysis o Design simple experiments and/or studies o Construct clear testable hypothesis o Prepare a plan for structuring and archiving incoming data o Explain possible ethical complications in experiments and studies o Describe different experimental designs o Perform a pilot study based on own study design o Evaluate study designs and pilot study o Revise study design according to critic and evaluation of pilot study o Solve basic statistical problems in R o Carry out calculations on statistical strength of statistical tests o Carry out calculations on confidence intervals of means, proportions and differences in means and proportions o Carry out calculations on t-test and other basic statistical test o Interpret p-values, and draw correct conclusions from them
Assessment method
Evaluation of the students achievements on the course is based on the following elements: Written exam, 50 % Project, 50 % To pass the course, students need to succeed both the written examination and on the project. The project is made in groups of 3-4 students. The project is made up by two rapports, two seminars and one presentation. All five parts are obligatory. The students are expected to participate actively in the seminars and in the presentation. The evaluation of the projects is based on the following elements: Project on study design, 40 % Project on data analysis, 40 % Presentation of study findings, 20 %
Marking scale
Experimental Design for the Life Sciences, Graeme Ruxton, OUP Oxford, 3’rd edition, (2010), ISBN: 9780199569120, pp. 200. Intuitive Biostatistics - a nonmathematical guide to statistical thinking, Harvet Motulsky, OUP USA, 3’rd edition, (2013), ISBN: 9780199946648, pp. 576.
Hóraldur Joensen