# Response table for Analyze Taguchi Design

Find definitions and interpretation guidance for every statistic in the Response table.
Use the response tables to select the best level for each factor. Usually you have the following objectives with a Taguchi design:
• Minimize the standard deviation
• Maximize the S/N ratio
• Meet a target with the mean (static design)
• Meet a target with the slope (dynamic design)

Use the delta and rank values to identify the factors that have the largest effect on each response characteristic. Then, determine which levels of these factors meet your objectives. Sometimes, the best level of a factor for one response characteristic is different from the best level for a different response characteristic. To resolve this issue, it may help to predict the results for several combinations of factors levels to see which one produces the best result.

## Interpretation

Average response characteristics
For each factor, Minitab calculates the average of the response characteristic at each level of the factor. For example, the design includes factor A at 2 levels (1 and 2) and 4 measurements at each level. Minitab calculates the mean of the 4 S/N ratios at level 1 and the mean of the other 4 S/N ratios at level 2. For more information, go to Methods and formulas for Analyze Taguchi Design.
Signal-to-Noise Ratio
Minitab calculates a separate signal-to-noise ratio (S/N) for each combination of control factor levels in the design. You can choose from different S/N ratios, depending on the goal of your experiment. In all cases, you want to maximize the S/N ratio.
Means (for static designs)
Minitab calculates a separate mean for each combination of control factor levels in the design.
Slopes (for dynamic designs)
Minitab calculates a separate slope for each combination of control factor levels in the design.
Standard deviations
Minitab calculates a separate standard deviation for each combination of control factor levels in the design.
Delta
Measures the size of the effect by taking the difference between the highest and lowest characteristic average for a factor.
Rank
The ranks in a response table help you quickly identify which factors have the largest effect. The factor with the largest delta value is given rank 1, the factor with the second largest delta is given rank 2, and so on.
In these results, the response tables show the following:
• For the Signal to Noise Ratios, B is ranked 1, followed by D, A, and C.
• For the Means, B is ranked 1, followed by A, C, and D.
• For the Standard Deviations, C is ranked 1, followed by B, A, and D.
Suppose you want to choose factors levels that minimize the standard deviation and maximize the S/N ratio and the mean. For example, for factor B, the average S/N ratio for all runs with level 1 is 42.15 and the average for runs with level 2 is 34.21. This indicates that level 1 maximizes the signal-to-noise ratio.
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