"quantity"exercise: A nonparametric test
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Questions 1:
A parametric test is most likely preferred to a non-parametric test when:
A 、the data are given in ratio or ordinal scale.
B 、defined sets of assumptions are given.
C 、the population is heavily skewed.
Questions 2:
The conditional expected value of a random variable is best described as the:
A、 expected value of a random variable given an event or scenario.
B 、probability-weighted average of the possible outcomes of the random variable.
C 、weighted average of the probabilities of an event given all possible scenarios.
B is correct. A parametric test is more appropriate than a non-parametric one when an analyst is concerned with parameters whose validity depends on a definite set of assumptions—for example, assumptions about the distribution of the population producing the sample.
A is incorrect. A nonparametric test is suitable for this case.
C is incorrect. A nonparametric test is also suitable for this.
A is correct. The conditional expected value of a random variable is the expected value of a random variable given an event or scenario.
B is incorrect because an expected value (not a conditional expected value) is defined as the probability-weighted average of the possible outcomes of the random variable.
C is incorrect because an expected value is not a probability. This answer defines the total probability rule, which is the weighted average of the probabilities of an event given all possible scenarios.
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