Unterschiede

Hier werden die Unterschiede zwischen zwei Versionen angezeigt.

--- en:versuchsdatenverwaltung:versuchsplanung [2026/01/11 19:16] – neelest
+++ en:versuchsdatenverwaltung:versuchsplanung [2026/01/11 19:19] (aktuell) – [Design:] neelest
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-**Figure:** Design of experiment 1: Selection of the target values
 Besides the manual set up of measuring data tables described above, SIGMA enables the user to generate a measuring data table according to a design of experiment. In that case the defined target variables will be transformed to measuring points in a measuring data table and control variables are represented by special columns. By choosing Experimental data, Design of experiments in the menu a wizard dialog opens, which assists the user by designing an experiment. The wizard is build up of three steps at which end a measuring data table is generated by SIGMA according to the chosen target variables, control variables and the selected design.
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 In SIGMA there are three types of factorial designs with different properties and restrictions to generate a measuring data table accordingly.
-  * Full factorial $2^k$ designs: Any type of control variable can be used. The values of the control variables are varied at two levels.
+  * **Full factorial $2^k$ designs**: Any type of control variable can be used. The values of the control variables are varied at two levels.
-  * Half fractional factorial $2^{k-1}$ designs: There has to be at least three control variables defined. The control variables are varied at two levels.
+  * **Half fractional factorial $2^{k-1}$ designs**: There has to be at least three control variables defined. The control variables are varied at two levels.
-  * Full factorial $3^k$ designs: Each control variable is varied at three levels.
+  * **Full factorial $3^k$ designs**: Each control variable is varied at three levels.
 === Central Composite Design ===