Related Topics:
	Design Types

One Factor Designs

One factor designs, also called "one factor at a time" (OFAT) or one-way analysis of variance (ANOVA), are used to determine if a particular factor has an effect on an output or response. This approach allows you to take a detailed look at the effect of the factor (using up to 255 levels), and it helps you determine whether a change in output is due to a change in the input (level) instead of random error.

Note that the factor in a one factor design must be configured as a qualitative factor. For this reason, predictions cannot be made for factor levels that are not tested, nor can one factor designs be used for optimization.

The following topics describe how to work with one factor designs, including:

• Creating a one factor design

• One factor design Data tab

• One factor design analysis results

• One factor design plots

• One factor design example

What's Changed? In the current version of DOE++, you can create a one factor design in the standard design folio. In this case, the format for entering response data for a one factor design is consistent with the format used for other design types. With this format, you enter the different factor levels in a single column, and you can analyze multiple responses if desired. To enter data in the same format that was used in Version 1 (with multiple columns for a single response, one for each factor level), use the one-way ANOVA folio.

In general, one-way ANOVA is a statistical method that is well suited to examining existing data, rather than planning an experiment. For planning an experiment involving a single factor, the standard design folio is the appropriate tool.