# You are defining the quality standards

You are defining the quality standards for the project to create a new microchip that has the capacity to contain more instructions than any prior chip. You have defined which variables are to be measured. You have also determined what attributes are important to you. Although the product is not expensive, it is expected to bring a steady income stream to the company because it is integral to the production of animmatronic toys and robots which are tremendiously popular.

Which testing method will you use and why?

A: Population testing, because the product is so crucial to the company's success

B: Sample testing, because the cost of population testing is prohibitive

C: Sample testing, because the product is so crucial t the company's success

D: Population testing, because the cost of population testing is prohibitive

Are we supposed to know the difference btw sample & population testing?

### Not a PMP question.

Not a PMP question.

### Cyes you should have a

C

yes you should have a knowledge of popu and sam testing.

P198 8.1.2.6

### I'll go with B? My thoughts..

I'll go with B? My thoughts.. just thinking out loud.

Option A: Population testing, because the product is so crucial to the company's success
You can't sit testing each and every microchip this is coming out of the factor, that is just not possible, even if the CEO has billions in stake on it (think AAPL)

Option B: Sample testing, because the cost of population testing is prohibitive

The very reason, we test out few samples and not the whole population is that the population testing just kills the time, needs a lot of effort and cost. So this could be it. Also half of the work is already done - to find the important parameters to test. So you just have to pick one from the batch of 100 and test those parameters out.

Option C: Sample testing, because the product is so crucial t the company's success

If the product is so damm important for the company's success then check each and every microchip this is coming out of the assembly line - which is population testing.

Option D: Population testing, because the cost of population testing is prohibitive

Option does not even make coherent sense!

### Does "population testing"

Does "population testing" even exist? Never heard of such a thing. Couldn't find anything on the internet. sspawar, care to explain where the PMBOK describes this term?

Generally speaking, sample testing is less expensive - especially in production environments such as the one described in the caselet. I would pick C, assuming "population testing" is some made up term!

### I have given reference -

I have already given references in my earlier reply - pmbok P198

Statistical Sampling

### sspawar, OK I concede. Lets

sspawar, OK I concede. Lets assume Statistical Sampling = Population Testing. Could you then explain what is "Sample Testing"? There is no mention of the term "Sample Testing" or "Population Testing" on pg. 198 of PMBOK. PMBOK explicitly uses the term "Statistical Sampling", refering to the process of chosing a part (sample) of the population of interest for inspection.

read relevant stuff from related sources

in brief

population - means all

sample -- means selected few (part)

now read again - statistical sampling.

hope you have got my apprehension.

--------------------------------------

if 7 litre blood is there

the population blood count -is 7 litres

while for testing medical will take only few mls for testing it is sample testing

if whole blood - you will test what happen

it is the same

population testing

and

sample testing

### I understand what you mean to

I understand what you mean to say here. However, I feel this is a poorly worded question and the answer (option C) is not convincing. I do not see how sample testing is "so crucial" to the company's success. The caselet merely says that the product is expected to bring "steady income" to the company. I would go with crushPMP on this one and select option B because it aptly describes the inherent benefit of using statistical sampling as a method of testing.