Here's the question you clicked on:
KonradZuse
An inspector inspects large truckloads of potatoes to determine the proportion p in the shipment with major defects prior to using the potatoes to make potato chips. Unless there is clear evidence that this proportion, p, is less than 0.10, he will reject the shipment. He will test the hypotheses H0: p = 0.10, Ha: p < 0.10. e selects an SRS of 100 potatoes from the over 2000 potatoes on the truck. Suppose that six of the potatoes sampled are found to have major defects. Reference: Ref 18-6 The P-value of this test is A. 0.4082. B. 0.0912. C. 0.0400. D. less than 0.0002. A 95% confidence interval for the true proportion of potatoes in the truck that have major defects is A. 0.034 to 0.086. B. 0.013 to 0.107. C. 0.051 to 0.103. D. 0.026 to 0.128. Which of the following is true? A. The inspector will decide to reject the shipment because there's weak evidence that the proportion of potatoes with serious defects is less than 0.10. B. The inspector might reach the wrong conclusion about the lot of potatoes, whether he returns the shipment or not. C. Strictly speaking, the inspector should take a larger sample in order to more safely apply the large sample significance test for proportion. D. All of the above.
I'm going to say C, A, and C?
@CliffSedge @kropot72
the first two are incorrect, the last one is B because it states that "The population is at least 10 times as large as the sample" in the link below and that's true in this case, so no need to do a larger sample http://math.etsu.edu/1530/testing_proportion.pdf
oh i meant to add in, A and D are false because A is false
Yeah A made no sense.... B I wasn't sure about, and C sounded logical.