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Acceptance Testing Homework Help
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Acceptance Testing Definition
Acceptance Testing can be defined as a functional trial that is performed on a product before it is put on the market or delivered to the purchaser and so the acceptance testing procedure is designed to replicate the anticipated realistic use of the data product. This is to ensure that what the consumer or end-user receives is fully functional and meets their needs as well as their expectations. The acceptance testing process acts as a form of quality control to identify problems as well as defects at a stage where any issues can still be corrected relatively painlessly.
There are various statistical hypothesis tests for acceptance testing that is, for example, it is required to measure the thickness of a plate at N widely separated points: x1, . . . , xN, these measurements differ from one another due to random measurement error in the local thickness.
A random sample is a set of independent measurements made on the same population and a random sample is a set of independent and identically distributed (i.i.d.) random variables and so the sample mean of a random sample is defined.
A hypothesis test is used where the null hypothesis is
H0 : µ = T
T = desired thickness which is a known value and µ = true thickness which is an unknown value. The alternative hypothesis
H1: µ ≠ T is known as a two-tailed test.
Acceptance Testing Assignment Help
In order to test two sample means, two dimensions are measured repeatedly with a measuring device that has random errors, then the random sample of the inner dimension is x1, . . . , xN, and the random sample of the outer dimension is y1, . . . , yM The sample sizes are not assumed as N and M and the values N and M are the same.
The true mean values of these two samples, which are the true dimensions, are µ1 which is true but unknown which is an inner dimension, and µ2 which is true but unknown is an outer dimension. It is assumed that these two sets of measurements are normally distributed, each with known variance σ, and the null hypothesis is tested
H0 : µ1 = µ2
against one of the alternative hypotheses such that
H1: µ1 ≠ µ2
or:
H1 : µ1 > µ2
or
H1 : µ1 < µ2
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