Question

Historically, a factory has been able to produce a very specialized nano-technology component with 35% reliability, i.e., 35% of the components passed its quality assurance test. They have now changed their manufacturing process and hope that this has improved the reliability. To test this, they took a random sample of 24 components produced using the new process and found that 13 components passed the test. If you do a hypothesis test to see if the new manufacturing process is more reliable, does this observation give you enough evidence to reject the null hypothesis at 5% level of significance? (Suggestion: Use Microsoft Excel for your calculations.)The table below shows the probability of observing number of components (X) passing the test out of 24 components, if the reliability is 35%.X Probability0 0.00001 0.00042 0.00263 0.01024 0.02895 0.06226 0.10617 0.14708 0.16829 0.161010 0.130011 0.089112 0.052013 0.025814 0.010915 0.003916 0.001217 or more 0.0004A) NoB) Yes

Answer 1

Yes

Step-by-step explanation:

From the given output

The Probability of getting 13 or more passed

when the reliability = 0.35. can be calculated as follows

=0.0258+0.0109+0.0039+.0012+0.0004 = 0.0422 ≈ 4.2%

Since the probability is less than the 5% level we will therefore reject the Null hypothesis

answer : YES