1.
Open the 2 Factors Crossed.jmp sample data table, located in the Variability Data folder.
2.
Select Analyze > Quality and Process > Variability / Attribute Gauge Chart.
3.
Select Measurement and click Y, Response.
4.
Select Operator and click X, Grouping.
5.
Select part# and click Part, Sample ID.
6.
Set the Chart Type to Variability.
7.
8.
From the red triangle menu, select Heterogeneity of Variance Tests.
9.
Select Crossed.
10.
Click OK.
Heterogeneity of Variances Tests Report
Note: This data comes from the Automotive Industry Action Group (AIAG) (2002), Measurement Systems Analysis Reference Manual, 3rd edition, 94.
1.
Open the MSALinearity.jmp sample data table, located in the Variability Data folder.
2.
Select Analyze > Quality and Process > Variability / Attribute Gauge Chart.
3.
Select Response and click Y, Response.
4.
Select Standard and click Standard.
5.
Select Part and click X, Grouping.
6.
Set the Chart Type to Variability.
7.
8.
From the red triangle menu, select Gauge Studies > Bias Report.
Measurement Bias Report
The bias (Response minus Standard) is calculated for every measurement. The Overall Measurement Bias Report shows a histogram of the bias and a t-test to see whether the average bias is equal to 0. You can see that the Average Bias is not zero, it is -0.0533. However, zero is contained within the confidence interval (-0.1152,0.0085), which means that the Average Bias is not significantly different from 0. Using a significance level of 0.05, you can see that the p-value is greater than 0.05, which also shows that the Average Bias is not significantly different from 0.
Using the same data and scenario as the Bias Report option, you can now examine the linearity to determine whether there is a significant relationship between the size of the parts and the operator’s ability to measure them.
1.
Open the MSALinearity.jmp sample data table, located in the Variability Data folder.
2.
Select Analyze > Quality and Process > Variability / Attribute Gauge Chart.
3.
Select Response and click Y, Response.
4.
Select Standard and click Standard.
5.
Select Part and click X, Grouping.
6.
Set the Chart Type to Variability.
7.
8.
From the red triangle menu, select Gauge Studies > Linearity Study.
Linearity Study
The p-value associated with the test on the slope is quite small, <.0001. The t test for the slope is testing whether the bias changes with the standard value.
Because the p-value is small, you can conclude that there is a significant linear relationship between the size of the parts and the operator’s ability to measure them. You can also see this in the graph. If the part or standard value is small, the bias is high, and vice versa.