Question

Which one of the following statements is FALSE?

	a.	The p-value gives an indication of how close our estimate is to the hypothesized value of the parameter.
	b.	Assume the level of significance for a test and the effect size of interest are both fixed. Then, increasing the sample size will decrease P[Type2 error].
	c.	When the null hypothesis is TRUE, P[Type 1 error] = the level of significance of the test (alpha)
	d.	The p-value is a conditional probability.
	e.	The p-value is the probability of getting our sample result.

Answer 1

The p-value is the probability that a result at least as extreme as that which was actually observed would occur given that the null hypothesis is true.

a) False

d) FALSE. A p-value is a conditional probability—given the null hypothesis is true, it’s the probability of getting a test statistic as extreme or more extreme than the calculated test statistic.

e) False,  The p-value is the probability that a result at least as extreme as that which was actually observed would occur given that the null hypothesis is true.