Reading 10: Sampling and Estimation-LOS b 习题精选 2011, between, stocks, simple

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Session 3: Quantitative Methods: Application
Reading 10: Sampling and Estimation

LOS b: Distinguish between simple random and stratified random sampling.

 

 

An equity analyst needs to select a representative sample of manufacturing stocks. Starting with the population of all publicly traded manufacturing stocks, she classifies each stock into one of the 20 industry groups that form the Index of Industrial Production for the manufacturing industry. She then selects a number of stocks from each industry based on its weight in the index. The sampling method the analyst is using is best characterized as:

A) data mining.

B) stratified random sampling.

C) nonrandom sampling.

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In stratified random sampling, a researcher classifies a population into smaller groups based on one or more characteristics, takes a simple random sample from each subgroup based on the size of the subgroup, and pools the results.

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Thomas Merton, a car industry analyst, wants to investigate a relationship between the types of ads used in advertising campaigns and sales to customers in certain age groups. In order to make sure he includes manufacturers of all sizes, Merton divides the industry into four size groups and draws random samples from each group. What sampling method is Merton using?

A) Cross-sectional sampling.

B) Simple random sampling.

C) Stratified random sampling.

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In stratified random sampling, we first divide the population into subgroups based on some relevant characteristic(s) and then make random draws from each group.

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An analyst divides the population of U.S. stocks into 10 equally sized sub-samples based on market value of equity. Then he takes a random sample of 50 from each of the 10 sub-samples and pools the data to create a sample of 500. This is an example of:

A) simple random sampling.

B) systematic cross-sectional sampling.

C) stratified random sampling.

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In stratified random sampling we first divide the population into subgroups, called strata, based on some classification scheme. Then we randomly select a sample from each stratum and pool the results. The size of the samples from each strata is based on the relative size of the strata relative to the population. Simple random sampling is a method of selecting a sample in such a way that each item or person in the population being studied has the same (non-zero) likelihood of being included in the sample.

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Which of the following is least likely a step in stratified random sampling?

A) The population is divided into strata based on some classification scheme.

B) The size of each sub-sample is selected to be the same across strata.

C) The sub-samples are pooled to create the complete sample.

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In stratified random sampling we first divide the population into subgroups, called strata, based on some classification scheme. Then we randomly select a sample from each stratum and pool the results. The size of the samples from each strata is based on the relative size of the strata relative to the population and are not necessarily the same across strata.

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