General Factorial DOE (Legacy)

When to use this tool

Use the general factorial DOE to analyze the effects of multiple factors, each at two or more levels, on a numerical response. Like full factorial designs, these designs are best used when you have few factors (up to 4 or 5), since they can get quite large and cost prohibitive.

Using EngineRoom

Use the Design Wizard to create the experimental design. Use the Guide Me mode if you're not sure which design to use, and the Expert mode if you already know which design you want to use. Once the design matrix is created, enter the response variable data into the last column in the matrix. Then use the DOE Analyzer tool to analyze the design. Follow the example below to learn how to do this in EngineRoom.

Example:

Create and analyze a full factorial to find the optimal factor combination to maximize Profit (%). Two factors are under study, at three levels each:

• Price Hike (%): 5/10/15
• Special: None/Miles/Gift Card

Steps:

1. Create Design:

• Select Analyze > Design of Experiments > click on the Design Wizard:
• Select the Guide Me mode.
• For the question: "Do all of your factors have 2 levels each, or do some of them have more than 2 levels?" select '3+ Levels'
• Click on the plus '+' sign below the two rows already displayed and enter the information on the three factors under study, then click Continue:

• The design will be run over two weeks, so create two replicates of the design. Also, select 2 blocks to account for the variability from the replicates.

• Click continue and select the design option corresponding to 2 replicates and an effect size of 2 standard deviations. This design has only 33% power, but that assumes you have all the effects in the model - the power increases as soon as you reduce the model, so select this option:

• The design summary/description is shown; click Create Design:

2. Enter Data:

• The design matrix opens up from the data sources panel. It contains all the information about the design, with a blank column at the end for the response variable data.
• Normally you would run the experiment by following the Randomized run order, and enter the response data into this column. However, we already have the response data, so we can simply enter or copy-paste it here, after making sure the run order of both designs is identical (i.e., run #1 in the design we just created is the same as run #1 in the design table provided.) The response data provided are in Standard order, so sort the created design in the Standard order as well by clicking on the Up arrow in the Standard order column:

• Copy-paste the response data into the blank column and click the Save Changes button:

3. Analyze Design:

• It's time to analyze the design - select Analyze > Design of Experiments > DOE Analyzer.
• Drag the Design matrix variable from the data sources panel onto the Design matrix drop zone on the Analyzer, and the Profit % variable onto the Response Variable drop zone.
• The output contains several parts. You can close the pop-up message that says 'The default model contains the significant terms at the chosen alpha level and any terms needed to preserve model hierarchy.'
• Click on the Summary tab to see the design summary

• Click on the Model Output tab to see the model output along with the residual plots:

• Click on the Factorial Plots tab to see the main effect and interaction plots:

General Factorial DOE (Legacy) Video Tutorial