(a) In formulating hypotheses for a statistical test of significance, the null hypothesis is often A. the probability of observing the data you actually obtained B. a statement that the data are all 0. C. a statement of ''no effect'' or ''no difference''. D. 0.05 (b) In testing hypotheses, which of the following would be strong evidence against the null hypothesis? A. Using a small level of significance. B. Obtaining data with a large P -value. C. Obtaining data with a small P -value. D. Using a large level of significance. (c) The P -value of a test of a null hypothesis is A. the probability, assuming the null hypothesis is false, that the test statistic will take a value at least as extreme as that actually observed. B. the probability the null hypothesis is false. C. the probability the null hypothesis is true. D. the probability, assuming the null hypothesis is true, that the test statistic will take a value at least as extreme as that actually observed.
(a) In formulating hypotheses for a statistical test of significance, the null hypothesis is often
A. the
B. a statement that the data are all 0.
C. a statement of ''no effect'' or ''no difference''.
D. 0.05
(b) In testing hypotheses, which of the following would be strong evidence against the null hypothesis?
A. Using a small level of significance.
B. Obtaining data with a large P -value.
C. Obtaining data with a small P -value.
D. Using a large level of significance.
(c) The P -value of a test of a null hypothesis is
A. the probability, assuming the null hypothesis is false, that the test statistic will take a value at least as extreme as that actually observed.
B. the probability the null hypothesis is false.
C. the probability the null hypothesis is true.
D. the probability, assuming the null hypothesis is true, that the test statistic will take a value at least as extreme as that actually observed.
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