How Minitab stores design information in the worksheet

When you create a design, Minitab creates a design object that stores the appropriate design information in the worksheet. Minitab needs this stored information to analyze and plot data correctly.

The following columns contain your design:
StdOrder
StdOrder (Standard order) is the non-randomized order of the runs. This is useful to compare the design to designs found in textbooks or other applications. To display the design in standard order, choose Stat > DOE > Display Design. Choose Standard order for design and click OK.
RunOrder
RunOrder (Run order) is the order you should perform the experiment in. You reduce the potential for bias when you run the experiment in random order. The run order is used if you create a "Residuals versus order" graph. To display the design in run order, choose Stat > DOE > Display Design. Choose Run order for design and click OK.
CenterPt (2-level factorial design)
Center points represent experimental runs with all factor levels set halfway between the low and high settings.
  • 1 is a corner point
  • 0 is a center point
PtType (Plackett-Burman, definitive screening, split-plot, general full factorial, response surface, and mixture design)
The type of point in a designed experiment.
  • 1 is a corner point
  • 0 is a center point
  • -1 is an axial point
  • 2 is an edge point
Blocks
A block is a categorical variable that identifies groups of experimental runs conducted under relatively homogeneous conditions. Use blocks in experimental design and analysis to minimize bias and error variance due to uncontrolled factors. Blocks can explain variation in the response variable that is not caused by the experimental factors.
Factor or component columns
The variables in an experiment that you change to determine whether they effect a response variable.

To analyze your design, you must follow certain rules when modifying worksheet data. To analyze your design in Minitab, choose Stat > DOE > design > Analyze Design. If you make changes that corrupt your design, you might still be able to analyze it by defining a custom design. To define a custom design in Minitab, choose Stat > DOE > design > Define Custom Design.

  • You cannot delete or move the columns that contain the design.
  • You can enter, edit, and analyze data in all the other columns of the worksheet, that is, all columns beyond the last design column. You can put the response and covariate data here, or any other data you want to enter into the worksheet.
  • You can delete runs from your design. If you delete runs, you might not be able to fit all terms in your model. In this case, Minitab will automatically remove any terms that cannot be fit and do the analysis using the remaining terms.
  • You can add runs to your design. For example, you might want to add center points or a replicate of a specific run of interest. Ensure the levels are appropriate for each factor or component and that you enter appropriate values in StdOrder, RunOrder, CenterPt, PtType, and Blocks. These columns and the factor or component columns must all be the same length. You can use any numbers that seem adequate for StdOrder and RunOrder. Minitab uses these two columns to order data in the worksheet.
  • You can change the level of a factor for a botched run in the Data window.
  • You can change factor level settings by modifying the design. To modify the design, choose Stat > DOE > Modify Design. However, you cannot change a factor type from numeric to text or text to numeric.
  • You can change the name of factors and components, randomize the design, or re-randomize the design using Stat > DOE > Modify Design.
  • You can use any procedures to analyze the data in your design, not only the procedures in the DOE menu.
  • You can add factors to your design by entering them in the worksheet. Then, define a custom design.
By using this site you agree to the use of cookies for analytics and personalized content.  Read our policy