R7 练习: 估计与推断

考纲范围

  • Compare and contrast simple random, stratified random, cluster, convenience, and judgmental sampling and their implications for sampling error in an investment problem.
  • Explain the central limit theorem and its importance for the distribution and standard error of the sample mean.
  • Describe the use of resampling (bootstrap, jackknife) to estimate the sampling distribution of a statistic.

Q1.

The stratified random sampling means to:

A. divide the population into subpopulations and draw data evenly from them.

B. divide the population into subpopulations and draw data in sizes proportional to each subpopulation.

C. select samples randomly from the population.


Q2.

An analyst is studying the net income (NI) of technology stocks globally. She uses all the data in the internal database that she has established when researching dozens of representative stocks in the technology sector. This sampling method is an example of:

A. stratified random sampling.

B. judgmental sampling.

C. convenience sampling.


Q3.

Jiang, a risk control manager, is checking last year’s transactions of the overseas derivative trading department through sampling. Based on his expertise and profession, Jiang checks mostly the over-the-counter (OTC) derivative instruments. Which of the following statements best describes Jiang’s sampling method? His method:

A. may result in a non-representative sample.

B. can cover each transaction with equal probability.

C. is time-efficient and cost-effective.


Q4.

An analyst calculates the bond returns of 125 firms in the US market. If the sample mean is 7.2% while the mean of the entire US bond returns is 7.9%, the difference between 7.9% and 7.2% is best described as:

A. the standard error of sampling distribution.

B. the data snooping bias.

C. the sampling error.


Q5.

Which of the following statements about the sampling methods is incorrect?

A. Compared with simple random sampling, stratified random sampling ensures that the sample includes the subpopulations of interest.

B. In systematic sampling, the sample can be drawn by selecting every kth observation until reaching the desired size.

C. In contrast to other probability sampling methods, keeping the same sample size, cluster sampling usually yields higher accuracy.


Q6.

Which of the following statements about the central limit theorem is least accurate? To conclude the sample mean is normally distributed:

A. the population should follow a normal distribution.

B. the population must have a finite variance.

C. the sample size has to be large enough, generally larger than 30.


Q7.

The sample mean follows a normal distribution with a standard error of 1.5, and the population variance is 144. The sample size is closest to:

A. 8.

B. 64.

C. 96.


Q8.

With regard to the central limit theorem, which of the following statements is most likely correct?

A. If the population distribution is lognormal, the sample mean will follow a normal distribution with any sample size.

B. The standard error of the sample mean may be greater than the standard deviation of the population.

C. Even if the population distribution is unknown, the central limit theorem can be used to construct the confidence interval for the population mean when the sample size is large.


Q9.

Which of the following statements regarding the distinction between jackknife resampling and bootstrap resampling is most likely accurate?

A. Jackknife resampling is done with replacement, while bootstrap resampling is not.

B. Jackknife resampling usually requires that the number of repetitions equals the sample size, while bootstrap resampling does not.

C. Jackknife resampling is particularly useful when the analytical formula such as z-statistic or t-statistic is not available, while bootstrap resampling is not.


Q10.

Compared with jackknife resampling, bootstrap resampling:

A. uses an analytical formula such as a z-statistic or t-statistic.

B. requires that each resample is of the same size as the original sample.

C. usually requires n repetitions for a sample of size n.


Q11.

Resampling (bootstrap, jackknife) is widely used to estimate the sampling distribution of a statistic. Which of the following is (are) true about resampling?

I. Bootstrap method mimics the random sampling process by regarding the randomly selected sample as if it were the population. II. Jackknife resampling usually requires n repetitions for a sample of size n. III. Bootstrap usually produces similar results, whereas Jackknife gives different results for every run.

A. I only.

B. I and II only.

C. I, II, and III.