|Fundamentals of Statistics contains material of various lectures and courses of H. Lohninger on statistics, data analysis and chemometrics......click here for more.|
|See also: anova|
When analyzing data we can distinguish two basic types of experiments: (1) observational experiments force the experimenter just to watch and listen, with no possibility to influence or select the observed variables. (2) In contrast to this, we may performe designed experiments, which allow a control of the level of variables applied to the experimental setup. Although in many practical situations the experimenter does not have any opportunity to control the variables, it is quite instructive to have a working knowledge on experimental designs and the analysis of the data obtained.
Here is a collection of the most important terms concerning experimental designs:
A designed experiment is one for which the experimenter controls the treatments and the assignment of experimental units to the particular treatments.
The most important question in experimental design is how to set up the factor levels and how to assign the experimental units to the individual treatments. Several possibilities are commonly used:
One major tool for statistical analysis of experimental designs is the
analysis of variance (ANOVA).
Last Update: 2012-10-08