"quantity"exercise: A nonparametric test

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來源: 正保會(huì)計(jì)網(wǎng)校編輯：小鞠橘桔 2020/11/10 14:06:59　字體：大小

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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.

View answer resolution

【Answer to question 1】B

【analysis】

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.

【Answer to question 2】A

【analysis】

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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