C. In the binomial distribution, as the probability of a\"+\"or \"-\" outcome di

Question

C. In the binomial distribution, as the probability of a"+"or "-" outcome differs more and more from .5, the distribution of probabilities for all possible outcomes always becomes more and more symmetrical. D. In the sign test, the p value associated with a given number of "+" outcomes will be the same as the p value associated with the same number of "+" outcomes will be the same as the p value associated with the same number of "-" outcomes, when the test is two-tailed. E. In the test, when the obtained result is exactly what would be expected by chance (like 9 successes out of 18 trials when P = .50), the p value (assuming you're doing a two-tailed test) can sometimes be greater than 1.00. F. In the sign test, if N increases from 15 to 20 and alpha is made less stringent (like from .01 to .05), the number of distinct possible outcomes (e.g., number of heads out of N) that allow rejection of H_0 must decrease. G. In the sign test, if N decreases and the size of the effect of the independent variable decreases in strength, the probability of a Type II error decreases. H. In sign test, as the numerical value of P_real decreases, the power of an experiment must always decrease. I. As power decreases, the probability of correctly rejecting the null hypothesis increases. J. If a researcher fails to reject the null hypothesis, then she must "accept" the null hypothesis. K. A researcher will always know for sure when she has made a Type I error L. If the obtained p value is less than the alpha level, the null hypothesis should be rejected. M. It is impossible to make a Type II error when you reject the null hypothesis. N. If a researcher uses a one-tailed test, it will be easier for her to reject the null hypothesis than if she uses a two-tailed test, assuming the effect is in the predicted direction. O. If a researcher uses a one-tailed test, it will be easier for her to reject the null hypothesis than if she uses a two-tailed test, if the effect is in not the predicted direction.

Explanation / Answer

Hi,

Please post the answers in blocks of 5, according to forum rules:

The right statement is also given with the answers:

J - FALSE. It is "failed to reject" and not "accept"

K - FALSe. The researcher never knows for sure whether she or he has made a Type 1 error

L - TRUE. alpha is critical value set

M - False. A Type II error can only occur if the null hypothesis is false.

N - False. It is tougher to reject a 1 sided hypothesis

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