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Statistical Stratification With Count Data, Part 1

What is your area of opportunity?

Davis Balestracci
Thu, 09/11/2014 - 12:51
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My last column, “Dealing With Count Data and Variation,” showed how a matrix presentation of stratified count data could be quite effective as a common-cause strategy. I’ll use this column to review some key concepts of count data as well as to demonstrate the first of two common statistical techniques that can be useful for further analysis. Obtaining the counts themselves is only half of the job.

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First, make sure the operational definition is clear: What’s the threshold whereby something goes from a “nonincident” (i.e., a value of 0) to an “incident” (i.e., a value of 1)? Would two or more people assessing the situation concur that the “incident” had occurred?

In addition, all count data have an implicit denominator that’s defined by the “area of opportunity” for that count. It depends on what's being counted, how it’s being counted, and what possible restrictions there might be upon the count.

 …

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Comments

Submitted by Pierre A. on Thu, 09/11/2014 - 02:46

Variable areas of opportunity

Hi,

This answers the question from my post against your previous column.

In other cases the binomial distribution may be more appropriate and we would then use the p chart.

Thanks for your pragmatic insights.

Looking forward to the next!

Best regards

Pierre

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Submitted by michaelwittke@… on Fri, 09/12/2014 - 18:37

In reply to Variable areas of opportunity by Pierre A.

I may be missing something, however

Greetings!

I need (please & thank you) an explanation of the "u avg". The reason I am asking is that when I try to average the infection rates/1,000 days (via calculator, excel or minitab) the average I keep arriving at is 13.1, not 12.2

Thank you and have an awesome weekend!

Michael Wittke,

Fort Worth, TX

  • Reply

Submitted by Davis Balestracci on Mon, 09/15/2014 - 17:51

In reply to I may be missing something, however by michaelwittke@…

Careful how you calculate the average

Hi, Michael,

Thanks for your comment.

I think you took the average of the six individual calculated rates. Your result gives each of the individual rates equal weight, which is NOT true because each is based on unequal number of hours in the denominator.

The 12.2 is a result of summing ALL of the infections divided by the sum of ALL the individual hours, i.e., (77 / 6.311 -- the numbers in the TOTAL row of the table). That is the correct overall average to use because it is based on SYSTEM performance.

I hope this clarified it for you.

Kind regards,

Davis

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Submitted by michaelwittke@… on Mon, 09/15/2014 - 18:46

In reply to Careful how you calculate the average by Davis Balestracci

calculate the average

Thank you, that makes sense!

Michael

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Submitted by Davis Balestracci on Mon, 09/15/2014 - 17:53

How to calculate average

See answer to question below
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