Experimental design and data analysis

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[[Image:Tübingen logo word 300px.png|right]]
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This page lists resources discussed in the ''Design and Analysis'' seminar and includes links to relevant further reading. Please feel free to add your own suggestions to the sections. The course is run approximately yearly and takes places in the [http://www.ifib.uni-tuebingen.de/institute.html Institute of Biochemistry] of the [http://www.uni-tuebingen.de/en/landingpage.html University of Tübingen]. See the Institute's [http://www.ifib.uni-tuebingen.de/master/special-courses.html course page] for dates and contact information.
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This page lists resources discussed in the ''Design and Analysis'' seminar and includes links to relevant further reading. Please feel free to '''add your own suggestions and comments''' to the sections. The course is run approximately yearly and takes places in the [http://www.ifib.uni-tuebingen.de/institute.html Institute of Biochemistry] of the [http://www.uni-tuebingen.de/en/landingpage.html University of Tübingen]. See the Institute's [http://www.ifib.uni-tuebingen.de/master/special-courses.html course page] for dates and contact information.
== Aim of the course ==
== Aim of the course ==
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== 3. Data analysis ==
== 3. Data analysis ==
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* [http://www.methodenberatung.uzh.ch/datenanalyse.html overview diagram to decide which statistical test to use] - in German by the University of Zürich
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* [http://udel.edu/~mcdonald/statintro.html Handbook of biological statistics] - online textbook by John McDonald at U Delaware
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* [http://rfd.uoregon.edu/files/rfd/StatisticalResources/outl.txt Dealing with outliers] - very detailed essay on the topic
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* [http://www.youtube.com/watch?v=iRrcUzHF-rE video tutorial: non-parametric rank sum test with Excel] - see how a basic rank sum test is done using Excel
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* [https://www.gnu.org/software/octave/ free Matlab alternative Octave]
== 4. Psychological pitfalls ==
== 4. Psychological pitfalls ==
== Organizer & host institution ==
== Organizer & host institution ==

Revision as of 04:49, 3 April 2014

This page lists resources discussed in the Design and Analysis seminar and includes links to relevant further reading. Please feel free to add your own suggestions and comments to the sections. The course is run approximately yearly and takes places in the Institute of Biochemistry of the University of Tübingen. See the Institute's course page for dates and contact information.

Aim of the course

Experimental design and data analysis is a new graduate seminar piloted in 2013 to address the questions of how to plan an experiment and how to best analyze the resulting data. We look at how to do a proper background check, where to find the best protocols, how to formulate a useful hypothesis, methods to keep experiments on schedule, tools of data analysis, and finally we will talk about some psychological pitfalls frequently seen in the interpretation of results.

1. Selecting a project

2. Planning your project

3. Data analysis


4. Psychological pitfalls

Organizer & host institution

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