Using the sign test, if the null hypothesis is false, then P (the probability of a plus) ____.
equals 0.50
equals alpha
equals beta
is not equals to 0.50
if the null hypothesis is false, then P (the probability of a plus) is not equals to 0.50
Using the sign test, if the null hypothesis is false, then P (the probability of a...
The power of a test is the probability of accepting a null hypothesis that is false. true or false?
45. If a sign test is applied, what is the null hypothesis for a two-tailed test? B. H is not equal to 0.50 A H, = 0.50 CH, : > 0.50 pH, 11 <0.50
Which of the following best represents the null hypothesis for a sign test? a. p + q = 1.00 b. p – q c. p = q d. p = 0
When the null hypothesis is rejected: Op< alpha p > beta p < beta p > alpha
The power of a test is the probability that we _____ the null hypothesis when the alternative hypothesis is _____. ? A) reject, true B) accept, true C) accept, false D) reject, false (IT IS NOT D)
The calculated p-value for a One Sample Sign test is 0.246. Using the conventional value for p, the null hypothesis cannot be rejected. True False
Test the hypothesis using the P-value approach. Be sure to verify the requirements of the test. Upper H 0: p equals=0.5 versus Upper H 1: p greater than>0.5 n equals=250 x equals=135, alpha equals=0.05
Which of the following statements is FALSE? a.) The power of a hypothesis test is the probability of not making a Type II error. b.) Alpha (α) is equal to the probability of making a Type I error. c.) The probability of rejecting the null hypothesis when the null hypothesis is true is called a Type I Error. d.) A smaller sample size would increase the effectiveness of a hypothesis test.
In hypothesis testing, the probability of accepting a null hypothesis when it is false is referred as a. the operating characteristics curve b Type I error c. The power of the test d. Type II error
The probability that a statistical test will reject the null when the null is actually false is known as: a) Power b) Confidence c) Hypothesis testing