One of the required conditions of the sign test is that the number of nonzero differences n must be greater than or equal to 30.
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Q. 2The sign test is employed to compare two populations when the experimental design is matched pairs, and the data are ordinal but not normally distributed.
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Q. 3In a normal approximation to the sign test, the standardized test statistic is calculated as z = 2.17 . If the alternative hypothesis states that the location of population 1 is to the right of the location of population 2, then the p-value of the test is 0.015.
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Q. 4The sign test is always to be preferred to the t test.
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Q. 5The Sign test or Wilcoxon Signed-Rank test are nonparametric tests that can be used to compare two dependent samples when the assumptions for a t-test are invalid.
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Q. 6When the direction (and not the magnitude) of the difference within each matched paired in a paired experiment is known, the sign test can be used while the Wilcoxon Signed-Rank test cannot be used.
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Q. 7Which of the following correctly describes the Wilcoxon rank-sum test?
a. It is a nonparametric test based on two independent simple random samples.
b. It is designed to determine whether the relative frequency distributions of two statistical populations of continuous values are identical to or different from one another.
c. It is equivalent to a parametric t-test of the difference between two means.
d. All of these.
e. None of these.
Q. 8Inferential procedures that are free from restrictive assumptions about the sampled populations are known as:
a. distribution-free tests (because no assumption about the nature of the population distribution is being made)
b. distribution-free tests (because no assumption about the nature of the sampling distributions of test statistics is being made)
c. parametric tests
d. all of these
e. none of these
Q. 9The Wilcoxon rank sum test (like most of the nonparametric tests presented in your book) actually tests to determine whether the population distributions have:
a. identical locations
b. identical spreads (variances)
c. identical shapes
d. all of these
e. none of these