Monetary Unit Sample - Poisson
Dear sir/madame,
I am currently working with JASP and using the poisson
distribution and i need to fill in some parameters.
For example:
1. population size: 50.000.000
2. performance materiality: 5.000.000
3. expected error in % between 0-100%
4. Risk of material misstatement (Low/medium/High)
When i enter these numbers JASP creates a sample size,
expected errors and max errors (k=0-xx)
a. When i change the numbers in % from 0% i get K=0
sample size equals 24.
b. When i change this to 50% the max errors change
from K=4. Sample
size equals 80.
1. Could somebody explain me how the percentages in step 3/a/b relates to the max errors of k=0 with 0% expected error or k=4 with excepted error of 50%?
2. Does this % mean that i expect 50% of errors in my sample size of?
Many thanks!
Regards,
Johan
Comments
Hi Johan,
It seems to me like you want to be able to state after your sample that the misstatement in the population is lower than 5,000,000 (10 percent of the population size/value). If you want to make this statement with a certain amount of confidence (say 90%) you will need at least 24 samples provided that you tolerate zero (0%) errors in these 24 samples. The expected errors setting determines the number of tolerable errors k in the sample of n items.
Planning for zero errors is efficient but the assumption that you find zero errors in the sample might not hold. Therefore you can adjust the number or percentage of expected errors to increase your sample size, mitigating the risk that you find more errors than you have planned for initially, which would imply that insufficient work has been done in the end. By setting the expected errors to absolute and choosing 1, you now tolerate 1 error in the sample and will require a larger sample size.
by setting the expected errors to relative, (5%) for example, you set k as a fraction of n. This means that you expect 5% of your sample to contain an error, which in the case of 80 samples amounts to 80x0,05=4 errors.
Hope this clarifies.
Two suggestions:
Best,
Koen
I'll forward this to Koen, our expert for this analysis
E.J.