OK,
The 0.09 Ppm example was only an example. I am dealing with theory. My
question is how to ensure the improvement is statistically significant.
If I run a t-test, I can use the tables and/or p value to determine if
the difference in means is significant. i want to do that with ppm
values. Better is defined (for this question) as less variation and
closer to the target. Saving money is im****tant. If we can perform a
test with less variation and closer to the target, we are providing more
accurate data to our customers. Supplying this data allows the internal
customer to improve their process to reduce waste and save money so
essentially it does save money.
Deming and others have proposed increasing quality will save money.
Saving money is always better as you mentioned, but saving money is
often more involved than just looking at the initial costs and return.
"Nitpicking numbers" is what I want to avoid. Is comparing means
nitpicking? Not if you compare statistically using a t-test or ANOVA or
ANOM. Is comparing Ppm values nitpicking? Not if I can compare
statistically. This is the question I am asking. Nothing more.
Raymond J. Johnson Jr. wrote:
> gn228169 wrote:
>
>> Raymond J. Johnson Jr. wrote:
>>
>>> gn228169 wrote:
>>>
>>>> When analyzing a new method or process, we usually use a t-test to
>>>> see if the new method is equivalent. If it is not, we look at the
>>>> variance and target values to see if it failed because it was
>>>> "better" Is there a statistical test to check for "better" without
>>>> checking first for equivalence and then for variance and target?
>>>> Thanks, Jim
>>>
>>>
>>>
>>> You've got some 'splainin' to do. What's the difference between a
>>> "process" and a "method"? You put "better" in scare quotes,
>>> apparently because you understand that it's a relative concept, but
>>> you don't tell us about what makes "better" better. What are your
>>> criteria? Are you considering only output values? Are there fiscal
>>> considerations (i.e., given equivalent output, is one process better
>>> because it's less costly)? What, exactly, are you trying to do?
>>
>>
>> A process and a method are the same thing, sorry. Better is less
>> variation and closer to target. A one sided t-test will not tell me if
>> the new method has less variation and is closer to the target as one
>> person suggested.
>> I think cpk,ppk,cpm etc. will work but I still have a question. If a
>> cpk, cpm score is greater using the new method, I would assume the new
>> method is "better". My question is, How much of an increase in Ppm is
>> significant? Example: If my Ppm value was a 0.90 and increased to a
>> 0.99 using the new method, is this due to common noise or is this a
>> truly "better"?
>
>
> It's only "better" if it saves money. Nitpicking the numbers *wastes*
> money. It's not clear whether you're trying to solve a particular
> problem or just dealing with theory, but if you're talking about a
> difference of .09 PPM, it's hard to believe it's worth worrying about.
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