Three Kinds of Sample Size Determination
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- This topic has 3 replies, 3 voices, and was last updated 19 years, 2 months ago by
Robert Butler.
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April 6, 2003 at 3:37 am #31903
Can anybody give me some hits to understand the applications for below 3 types of sample size determination? I’m a bit confused on when to use them.
1. For continuous parameters: N=(1.96S/Delta)^2
2. Minitab Tool: Power and sample size Macro
3. AQL Sampling plan like MIL-STD-105E
One more question is what sample size should be used in correlation analysis.
Many thanks.
Daya @April 6, 030April 7, 2003 at 11:57 pm #84618Anyone can help?
0April 8, 2003 at 7:00 pm #84671The sample size depends on several input factors, including the type of test being used for the analysis.
Minitab is right for the use (test) specified. The others are right for certain uses that may not be specified.0April 8, 2003 at 9:17 pm #84678
Robert ButlerParticipant@rbutlerInclude @rbutler in your post and this person will
be notified via email.When running a correlation analysis the main question is data quality and not sample size. There are many issues connected with data quality. Some of them are questions like – Is the data representative? Does the data span the region of interest? Has the data been gathered in such a manner that the various “independent” variables are in fact independent?
The last question plays a crucial role in correlation analysis and it is one that often brings to a halt analysis efforts involving “lots of data”. For example, if you have two variables X1 and X2 that you wish to correlate with a given response and your measurements were such that every time you increased X1 you increased X2 and every time you decreased X1 you decreased X2 you will have “lots of data” and the confounding of X1 and X2 will be such that you cannot separate their effects. In such a case, four data points from a two level factorial design coupled with two replicates on the centerpoint will provide more information than all of the data points gathered in the manner first described.0 -
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