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Quality and Process Methods > Variability Gauge Charts > Variability Gauge Analysis Report Options
Publication date: 06/21/2023

Variability Gauge Analysis Report Options

Each Variability Gauge Analysis report red triangle menu contains options to modify the appearance of the chart, perform Gauge R&R analysis, and compute variance components.

Vertical Charts

Changes the layout to horizontal or vertical.

Variability Chart

Shows or hides the variability chart.

Show Points

Shows or hides the points for individual rows.

Show Range Bars

Shows or hides the bars indicating the minimum and the maximum value of each cell.

Show Cell Means

Shows or hides the mean mark for each cell.

Connect Cell Means

Connects or disconnects cell means within a group of cells.

Show Separators

Shows or hides the separator lines between levels of the X, Grouping variables.

Show Group Means

(Available only if you have two or more X, Grouping variables or one X, Grouping variable and one Part, Sample ID variable.) Shows or hides the mean for groups of cells, represented by a horizontal solid line. A window appears, prompting you to select one of the grouping variables.

Show Grand Mean

Shows or hides the overall mean, represented by a gray dotted line across the entire graph.

Show Grand Median

Shows or hides the overall median, represented by a blue dotted line across the entire graph.

Show Box Plots

Shows or hides box plots.

Mean Diamonds

Shows or hides mean diamonds. The confidence intervals use the within-group standard deviation for each cell.

XBar Control Limits

Shows or hides lines at the UCL and LCL on the variability chart. For more information about the calculations of these limits, see “Statistical Details for Control Chart Builder”.

Points Jittered

Adds some random noise to the plotted points so that coincident points do not plot on top of one another.

Show Standard Mean

(Available only if you have specified a Standard variable.) Shows or hides the mean of the standard column.

Variability Summary Report

Shows or hides a report that gives the mean, standard deviation, coefficient of variation (CV), standard error of the mean, lower and upper confidence intervals, and the minimum, maximum, and number of observations.

Std Dev Chart

Shows or hides a separate graph that shows cell standard deviations across category cells.

Mean of Std Dev

Shows or hides a line at the mean standard deviation on the Std Dev chart.

S Control Limits

Shows or hides lines showing the LCL and UCL in the Std Dev chart. For more information about the calculations of these limits, see “Statistical Details for Control Chart Builder”.

Group Means of Std Dev

Shows or hides the mean lines on the Std Dev chart.

Heterogeneity of Variance Tests

Performs a test for comparing variances across groups. See Heterogeneity of Variance Tests.

Variance Components

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.

Gauge Studies

Contains the following options:

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 Report.

If you select the Gauge R&R option and you have not already selected a model type or entered MSA metadata, you are prompted to do so. If you want to modify your metadata specifications, click the Variability Gauge Analysis red triangle and select Gauge Studies > Edit MSA Metadata. See Show MSA Metadata Entry Dialog.

Note: The Platform preferences for Variability include the Gauge R&R Specification Dialog option. The preference is selected by default. Deselect the preference to use the spec limits that are defined in the data table.

Discrimination Ratio

Shows or hides the Discrimination Ratio report. The discrimination ratio compares the total variance of the measurement with the variance of the measurement error and characterizes the relative usefulness of a given measurement for a specific product. Generally, when the discrimination ratio is less than 2, the measurement cannot detect product variation, implying that the measurement process needs improvement. A discrimination ratio greater than 4 adequately detects unacceptable product variation, implying that the production process needs improvement. See Statistical Details for the Discrimination Ratio.

Misclassification Probabilities

(Available only if lower and upper tolerance values are specified for the response in the MSA Metadata.) Shows or hides a report of probabilities for rejecting good parts and accepting bad parts. See Misclassification Probabilities.

Bias Report

(Available only if a Standard column is specified in the launch window.) Shows the average difference between the observed values and the standard. A graph of the average biases and a summary table appears. See Bias Report.

Linearity Study

(Available only if a Standard column is specified in the launch window.) 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. A nonzero slope indicates that your gauge performs differently with different sized parts. See Linearity Study.

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 Equation shown here for each effect.

Edit MSA Metadata

Opens a window that enables you to add or edit the tolerance range, tolerance limits, historical mean, and historical process sigma. See Show MSA Metadata Entry Dialog.

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.

Want more information? Have questions? Get answers in the JMP User Community (community.jmp.com).