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Design Folio

General Full Factorial: Data Tab

After you build a general full factorial design, the Data tab will include a test "plan" with Response columns for entering response data. The first ten rows of an example plan are displayed next.

 

Each row represents a test run. The green columns display the factor level combinations to be used in each run, and the last column records the response values measured for each run.

All of the available columns for two level factorial designs are described in more detail below. To hide/show columns, use the Visible Columns window.

Tip: If you need to use a non-randomized order in an actual experiment, you can sort the design by clicking a cell in the column you wish to sort by and choosing Sheet > Sheet Actions > Sort > [Order]. For example, if changing levels in a randomized experiment would be too expensive, you can sort the design table by factor levels.

Factor levels can be displayed as the actual values assigned in the factor properties or as coded values. When you use coded values for two level factorial or Plackett-Burman designs, the low level will be displayed as -1 and the high level will be displayed as 1. When you use coded values for general full factorial or Taguchi OA factorial designs, the lowest level will be displayed as 1, the next level as 2, and so on. To switch between coded and actual values, choose Data > Display > [Value Type].

If your design includes only one observation per test run, the following columns will be available:

Each column contains a check box in the column header that specifies whether the response will be included in the analysis. If a column is selected, the color of the check box border will indicate the status of that response's analysis. A green border indicates that the response has been analyzed using the current analysis settings; a red border indicates that it has not. Note that if you clear the check box, you will not be able to specify analysis settings for the response, nor will you be able to display it in plots or use it in optimization.

If your design includes multiple measurements per test run, the following columns will be available:

 

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