Interpret JMP Bias & Linearity Report

[#1]

Hello Experts,

I would like to ask about the interpretation of JMP 17 Bias & Linearity Report.

I'm checking the measurement bias & linearity across different operating range for a new calibrated system. I want to know is the bias & linearity is good or not.

I was a bit confused on how to interpret the JMP result. JMP document states that;

https://www.jmp.com/support/help/en/17.1/index.shtml#page/jmp/linearity-and-bias-results-report.shtm...

- Results from an ANOVA test that tests if the slope of the line is equal to zero.

- The parameter estimates and tests for the intercept and the slope. The intercept tests the bias and the slope tests the linearity. The test for the intercept is useful only if the test on the slope fails to reject the hypothesis that the slope is equal to 0. 

It means the null hypothesis is slope of the line is equal to zero right?

So, alternative hypothesis is slope of the line is not equal to zero. In this case, the p-value is 0.9974 & my alpha is 0.05.

Means, I fail to reject the null hypothesis that the slope is equal to 0. And therefore, this equipment fail bias & linearity study?

Thank you.

[#2 · Accepted solution]

Hello @WebDesignesCrow ,

I think following page is much usefull to understand your result. This page is for Variability Gauge Analysis Report, but basically you can get the same result. https://www.jmp.com/support/help/en/17.1/index.shtml#page/jmp/linearity-study.shtml 
It says if the slope is significantly different from zero, you can conclude that there is a significant relationship between the size of the part or variable measured as standard and the ability to measure. I think most of the time the ideal situation is no relationship between the part and the ability to measure. It means when the slope is small, the gage linearity is good.

I hope it will help.

[#3]

Thanks @yuichi_katsumur . This page is much clearer to understand my result.