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MichaelR1
Level II

Counting outliers for the purpose of improving a process

JMP 17.2

We analyze data distributions from our devices and may see outliers below the 1st quartile and above the 3rd quartile. We wish to improve the manufacturing process to reduce the number of outliers. Is there a function or application that counts the outliers? For example, the output I wish to see is as follows:

Test

Distribution

No. of outliers below 1st quartile

No. of outliers above 3rd quartile

A

1

4

9

A

2

8

0

 

 

 

A

n

n1

n2

 

Does the function allow us to define an outlier, or must we use the default definition as given in the Outlier Box Plot.

1 ACCEPTED SOLUTION

Accepted Solutions
Victor_G
Super User

Re: Counting outliers for the purpose of improving a process

Hi @MichaelR1,

 

I think the platform "Explore Outliers" may be relevant and helpful for your use case (available in menu "Analyze", "Screening", and then "Explore Outliers").

When opening the platform, you can select all the columns where you want to screen outliers :

Victor_G_0-1700639897935.png

And from them, you have multiple choices on how to detect outliers :

Victor_G_1-1700639929034.png

In your case, if you're only interested in Quantile Range Outliers, clicking on the associated button will screen the outliers in the columns selected, and will provide you a summary of the analysis with numerous options to highlight these points :

Victor_G_2-1700640019333.png

Note that you can create a summary datatable from this panel, by right-clicking on the summary table, and then choose "Make Combined Data Table", to have the informations displayed in a new JMP table (for further processing/analysis) :

Victor_G_3-1700640070913.png

 

Hope that this first answer may help you,

Victor GUILLER
L'Oréal Data & Analytics

"It is not unusual for a well-designed experiment to analyze itself" (Box, Hunter and Hunter)

View solution in original post

1 REPLY 1
Victor_G
Super User

Re: Counting outliers for the purpose of improving a process

Hi @MichaelR1,

 

I think the platform "Explore Outliers" may be relevant and helpful for your use case (available in menu "Analyze", "Screening", and then "Explore Outliers").

When opening the platform, you can select all the columns where you want to screen outliers :

Victor_G_0-1700639897935.png

And from them, you have multiple choices on how to detect outliers :

Victor_G_1-1700639929034.png

In your case, if you're only interested in Quantile Range Outliers, clicking on the associated button will screen the outliers in the columns selected, and will provide you a summary of the analysis with numerous options to highlight these points :

Victor_G_2-1700640019333.png

Note that you can create a summary datatable from this panel, by right-clicking on the summary table, and then choose "Make Combined Data Table", to have the informations displayed in a new JMP table (for further processing/analysis) :

Victor_G_3-1700640070913.png

 

Hope that this first answer may help you,

Victor GUILLER
L'Oréal Data & Analytics

"It is not unusual for a well-designed experiment to analyze itself" (Box, Hunter and Hunter)