2.42.3.1.5 The Analyze Taguchi Design Dialog Box

1 Supporting Information
2 Model
3 Settings
- 3.1 Static Taguchi Design
- 3.2 Dynamic Taguchi Design
4 Quantities
5 Response Summary
6 Diagnotics
7 Prediction
8 Plots
9 Dialog Theme

Supporting Information

To open the Analyze Design dialog

Activate a worksheet with your experimental design data which is generated via Generate Design or Define Custom Design
Select Statistics: Quality Improvement: Design of Experiment from the Origin menu
Select the Analyze Design icon

Topics for Further Reading:

Model

Response	Select the column containing the measured outcome variable.
Model Terms	Specify which effects to include in the fitted model. Click the + button to open a dialog to select model terms

Settings

Static Taguchi Design

Signal to Noise Ratios	Selects the S/N ratio formula according to the optimization goal for the response. Nominal is best (I) The response has a specific target value. This formulation uses the mean squared deviation from the target relative to the variance. Nominal is best (II) The response has a specific target value. This alternative formulation adjusts the S/N calculation to account for the mean and standard deviation differently. Larger is better The response should be maximized. The S/N ratio increases as the mean increases and the variation decreases. Smaller is better The response should be minimized. The S/N ratio increases as the mean decreases and the variation decreases.
Use Adjusted Formula	Available only for Nominal is best options. Toggles whether to use an adjusted formula. When enabled, the software applies the displayed formula below instead of the standard formulation.
Formula	Displays the mathematical formula corresponding to the selected S/N ratio type.
Use Ln(s) for All Standard Deviation	Toggles whether to use the natural logarithm of the standard deviation, ln(s), as the measure of variability across all experimental runs.

Dynamic Taguchi Design

The settings below determine how the dynamic response is modeled and how the S/N ratio is computed, which directly affects factor optimization in the subsequent analysis.

Fit Lines	Specifies how the ideal function (response versus signal) is fitted. Three options are available Through Fixed Point Constrains the regression line to pass through a specified reference point rather than using ordinary least squares. Enter the coordinates in Fixed Response Value and Fixed Signal Value. Through Average Response at Fixed Signal Constrains the fitted line to pass through the average observed response at a specified signal value. This anchors the line to the data mean at a given signal level while still estimating the slope from the overall data. Enter the specified signal value in Fixed Signal Value Without Fixed Point Fits the line using ordinary least squares with no constraints. Both the intercept and slope are estimated freely from the data.
Use Adjusted Formula	Toggles whether to use an adjusted formula for the dynamic S/N ratio or sensitivity calculation. When enabled, the software applies the displayed formula below instead of the standard formulation.
Formula	Displays the mathematical formula
Use Ln(s) for All Standard Deviation	Toggles whether the natural logarithm of the standard deviation, ln(s), is used as the measure of variation across all experimental runs. This is commonly applied in Taguchi analysis to stabilize variance and linearize the relationship between the mean and variation.

Quantities

Select which numerical results are reported after fitting the model. Refer to the interpreting results page for details of the statistics

Display Response Table	Selects which summary statistics to show in the response table. Refer to the Response table section for more details of the results. This typically includes Signal to Noise Ratios Measures robustness (slope-to-error ratio) for dynamic systems Slopes Available for dynamic taguchi anlyhsis. Measures the linear relationship between signal and response Means Available for static taguchi analysis. Identify which factors significantly affect the average response. Standard Deviations Measures variability at each experimental run
Fit Linear Model	Chooses which response metric to use when fitting the linear model to the control factors. The same three options (Signal to Noise Ratios, Slopes/Means, Standard Deviations) are available. Three tables are included in the results of fit linear model for each response metric (Coefficients Table, Statistics and ANOVA)
Coefficients Table	Controls which regression coefficients appear in the output. Refer to the interpreting results page for details of the statistics Coefficients Standard Error Confidence Limits t-Value Prob>\|t\|
ANOVA Table	When enabled, displays the Analysis of Variance table, which partitions the total variation into model, residual, and lack-of-fit components. It provides the overall F-test and p-value to assess whether the model explains a significant portion of the variation.
Fit Statistics	These metrics summarize how well the model fits the data. Refer to the interpreting results page for details of the fit statistics Root Mean Square Error R-Sqaure Adj.R-Sqaure

Response Summary

Control which statistics to be reported in the response summary worksheet. Refer to response summary section of the interpreting reuslts page for more details of the statistics.

Signal to Noise Ratios	Displays the S/N ratios for the experimental runs
Means	Available only for Static Taguchi Design. Displays the mean response for each combination of control-factor levels
Coefficients of Variation	Available only for Static Taguchi Design. Compute and store the coefficient of variation for each experimental run
Slopes	Available only for Dynamic Taguchi Design. Displays the slopes of the fitted response-versus-signal relationships.
Intercepts	Available only for Dynamic Taguchi Design. Displays the intercepts of the fitted response-versus-signal relationships.
Standard Deviations	Displays the standard deviation of the response for each combination of control-factor levels.
Ln of Standard Deviations	Displays the natural logarithm of the standard deviation.
Design Matrix	Displays the design matrix used for the analysis, including the factor settings and corresponding experimental runs.

Diagnotics

The Diagnostics tab controls which residual and fitted-value outputs are generated in the DOEFittedResult worksheet , for checking model assumptions and spotting unusual observations.

Refer to the diagnotics section in the interpreting results page for details of the fitted results and residuals

Fitted Values	When enabled, reports the predicted response value for each run based on the fitted model. These are the values the model expects, used to compare against actual observations.
Residuals	Select which type of residual values to be output Regular Standardized Deleted
Hi (Leverage)	How far a run's factor settings are from the design center. Higher values = more potential to pull the fit.
Cook's Distance	How much the fitted values change when that run is removed.
DFITS	Combines leverage and residual size to measure overall influence on the fit.

Prediction

The Prediction tab specifies which response characteristics are included in the DOEFindYfromX sheet, which contains prediction results for the selected factor settings.

Refer to the Model Prediction - Find Y from X page for details on the generated worksheet.

Note: Only the response characteristics selected for output in the Quantities tab can be selected for prediction

Signal to Noise Ratios	Toggles the prediction calculation on or off. When enabled, a worksheet named DOEFindYfromX is generated. In the worksheet, enter factor values into the respective columns, the predicted response (Y) are calculated automatically.
Means	Available only for Static Taguchi Design. Toggle to predict the mean response for each combination of control-factor levels
Slopes	Available only for Dynamic Taguchi Design. Toggle to predict the slopes of the fitted response-versus-signal relationships.
Standard Deviations	Toggle to predict the standard deviation of the response for each combination of control-factor levels.
Ln of Standard Deviations	Toggle to predict the natural logarithm of the standard deviation.

Plots

The Plots tab lets you select which diagnostic and exploratory graphs to generate from the fitted model.

Note: The available Plots For options depend on the response characteristics selected in the Quantities tab.

Plots	Select the plots to generate from the fitted model. Refer to the Plots in DOE page for details of the plots Main Effects Plots Residial Plot Interaction Plots Scatter Plots with Fitted Lines (available only for dynamic taguchi design)
Plots For	Specifies the response characteristic for which the selected plots are generated. The available characteristics can include: Signal to Noise Ratios Slopes/Means Standard Deviations
Residual Type	Choose the residual type to be used for the residual plot. Refer to the diagnotics section in the interpreting results page for details of the residuals Regular Standardized Deleted

Dialog Theme

Save and load the settings of the dialog. Use this to store frequently used factor configurations, design options, or output preferences, then recall them for future designs without re-entering all values.