"quantity"exercise: Hypothesis Testing

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來(lái)源: 正保會(huì)計(jì)網(wǎng)校編輯：小鞠橘桔 2020/09/09 16:28:09　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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