3570.20 - Study Design and Data Analysis
Study Design and Data Analysis
Basic Statistics, 3.5 ECTS
To give the students statistical tools to use in data analysis and the competence 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. Regression analysis. Software R.
Learning and teaching approaches
Lectures, exercises, consulting, seminars and group project
After passing the 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 critique 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 of confidence intervals of means, proportions and differences in means and proportions o Carry out t-test and other basic statistical tests o Interpret p-values, and draw correct conclusions from them o Carry out variance analysis and regression analysis
Evaluation of the students´ achievements on the course is based on the following elements: Written examination: 50 % Project performance: 50 % In order to pass the course, students need to succeed both in the written examination and the project activities. The project is carried out in groups of 3-4 students. In the project one assignment and one project report have to be written, two seminars held and one presentation given. All five parts are obligatory. The students are expected to participate actively at the seminars. The evaluation of the total project performance is based on the following percentages: Assignment on study design: 40 % Project report on data analysis: 40 % Oral presentation of study findings: 20 %
Experimental Design for the Life Sciences, Graeme Ruxton, Nick Colegrave, OUP Oxford, 4th edition, (2016). ISBN 9780198717355; pp. 202. Intuitive Biostatistics - A Nonmathematical Guide to Statistical Thinking, Harvet Motulsky, OUP USA, 4th edition, (2018). ISBN 9780190643560; pp. 568.