Note: Figure 8.4 illustrates some of these options.
Tip: To set the default behavior of these options, select File > Preferences > Platforms > Variability Chart.
Shows or hides the separator lines between levels of the X, Grouping variables.
(Available only if you have specified a Standard variable) Shows or hides the mean of the standard column.
Estimates the variance components for a specific model. Variance components are computed for these models: main effects, crossed, nested, crossed then nested (three factors only), and nested then crossed (three factors only). See Variance Components.
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Gauge R&R interprets the first factors as grouping columns and the last factor as Part, and creates a gauge R&R report using the estimated variance components. (Note that there is also a Part field in the launch window). See Gauge R&R Option.
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Discrimination Ratio characterizes the relative usefulness of a given measurement for a specific product. It compares the total variance of the measurement with the variance of the measurement error. See Discrimination Ratio.
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Misclassification Probabilities show probabilities for rejecting good parts and accepting bad parts. See Misclassification Probabilities.
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Bias Report shows the average difference between the observed values and the standard. A graph of the average biases and a summary table appears. This option is available only when you specify a Standard variable in the launch window. See Bias Report.
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Linearity Study performs a regression using the standard values as the X variable and the bias as the Y variable. This analysis examines the relationship between bias and the size of the part. Ideally, you want the slope to equal 0. A nonzero slope indicates that your gauge performs differently with different sized parts. This option is available only when you specify a Standard variable in the launch window. See Linearity Study.
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Gauge R&R Plots shows or hides Mean Plots (the mean response by each main effect in the model) and Std Dev plots. If the model is purely nested, the graphs appear with a nesting structure. If the model is purely crossed, interaction graphs appear. Otherwise, the graphs plot independently at each effect. For the standard deviation plots, the red lines connect
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AIAG Labels enables you to specify that quality statistics should be labeled in accordance with the AIAG standard, which is used extensively in automotive analyses.
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See Local Data Filter, Redo Menus, and Save Script Menus in the Using JMP book for more information about the following options: