Three points each: FALSE FALSE FALSE TRUE TRUE True False A p-value of 0.05 is m

Question

Three points each: FALSE FALSE FALSE TRUE TRUE True False A p-value of 0.05 is more evidence against the null hypothesis tharn a p-value of 0.01. True False You and your roommate separately investigate a claim that the average cadet APFT score is 270. You obtained a sample average of 280 for a sample size of 30, and your roommate obtained a sample average of 280 for a sample size of 50. The two results possess the same strength of evidence against the null hypothesis (H: = 270) If you get a p-value of 0.1, it rneans there is a 10% chance that the sample average equals the population average. True False A steel manufacturer might calculate a confidence interval for true standard deviation of the strength of her factory's steel in order to assess the precision of her factory's manufacturing processes. True False True False Even though you reject the null hypothesis, it might still be true.

Explanation / Answer

a) The lesser the p-value, more significant is the test and more evidence to reject the null hypothesis. Therefore a p-value of 0.05 is less evidence against the null hypothesis than a p-value of 0.01. Therefore the given statement is false here.

b) For a greater sample size, we get a more evident test, therefore for n= 50 we will have more evidence against the null hypothesis than for n = 30, note this is only true in case the sample average are same in the two samples. Therefore the given statement is false here.

c) A p-value of 0.1 means that there is only a 0.1 probability that the test is not significant that is the sample average is equal to the population average. Therefore the given statement is true here.

d) Precision is the quality of being accurate about a given figure. Therefore it is given by the measure of dispersion that is standard deviation here. Therefore the given statement is true here.

e) We reject the null hypothesis only at a particular confidence level for example at 95% confidence level but this stay mean that there is a 5% probability that the null hypothesis is still true. Therefore the given statement is true here.

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