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    Sampling, central limit theorem, normal distribution

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    Question 1
    All of the following are reasons to sample except for:

    a) Reduce sampling error
    b) The research process is sometimes destructive.
    c) Save time
    d) For given resources, broaden the scope of the study.

    Question 2
    Sampling in which every unit of the population has the same probability of being selected into the sample is sometimes referred to as:

    a) representative sampling
    b) fair sampling
    c) random sampling
    d) nonrandom sampling

    Question 3
    The most elementary random sampling technique is:

    a) simple random sampling
    b) stratified random sampling
    c) systematic random sampling
    d) area random sampling

    Question 4
    In which of the following sampling techniques does the researcher number every item of the population before taking the sample?

    a) systematic sampling
    b) quota sampling
    c) cluster sampling
    d) simple random sampling

    Question 5
    The main reason for using stratified random sampling is to:

    a) reduce costs
    b) make certain that every kth item is selected
    c) reduce sampling error
    d) reduce non sampling error

    Question 6
    Fifty percent of a population possesses attribute X, thirty percent possesses attribute Y, and twenty percent possesses attribute Z. A researcher decides to include some people with attribute X, some with attribute Y, and some with attribute Z in her sample. Her sample consists of 80 people with attribute X, 70 people with attribute Y, and 50 people with attribute Z. The researcher has most likely done what type of sampling?

    a) systematic sampling
    b) simple random sampling
    c) proportionate stratified sampling
    d) disproportionate stratified sampling

    Question 7
    Another name for cluster sampling is:

    a) stratified sampling
    b) quota sampling
    c) snowball sampling
    d) area sampling

    Question 8
    Test markets are probably closest to which type of sampling?

    a) cluster sampling
    b) quota sampling
    c) stratified sampling
    d) snowball sampling

    Question 9
    In using judgment sampling, the researcher attempts to sample elements from the population by using her judgment. However, the researcher tends to make errors of judgment in one direction. These systematic errors are called:

    a) consistencies
    b) directional errors
    c) biases
    d) tendencies

    Question 10
    Which of the following sampling techniques is based on referral?

    a) stratified
    b) quota
    c) area
    d) snowball

    Question 11
    The central limit theorem states that which of the following is true:

    Question 12
    The central limit theorem states that for a given large sample size, if the shape of the population is unknown, the distribution of sample means is:

    a) unknown
    b) normal
    c) platykurtic
    d) skewed

    Question 13
    Suppose a population has a mean of 75 and a standard deviation of 14. If a researcher randomly samples 35 values from this population, the probability that >= 72 is:

    a) 0.102
    b) 0.5832
    c) 0.398
    d) 0.898

    Question 14
    Suppose a population has a mean of 84 and a standard deviation of 18. If a researcher randomly samples 37 values from this population, the probability that 80 <= <= 89 is:

    a) 0.866
    b) 0.043
    c) 0.1331
    d) 0.3669

    Question 15
    Suppose a population has a mean of 152 and a standard deviation of 22. If a researcher is randomly taking samples of size 42 from the population, 63% of the sample means are greater than what value?

    a) 153.12
    b) 151.56
    c) 150.88
    d) 154.64

    Question 16
    The Central Limit Theorem applies to sample proportions if sample size is large enough relative to the population proportion. How large of a sample size is needed?

    a) n? p = .25
    b) n? p> 5 and n? q> 5
    c) n >= 30
    d) n? p> 7 and n< 20

    Question 17
    Fifty-seven percent of the population has heard of brand x batteries. If 340 people are randomly selected from the population, what is the probability that the sample proportion who have heard of brand x batteries is greater than sixty percent?

    a) 0.1314
    b) 0.2755
    c) 0.3686
    d) 0.8686

    Question 18
    Suppose that 78% of all prerecorded music shoppers are under age 30. If a random sample of 250 prerecorded music shoppers is randomly taken, what is the probability that the sample proportion that is under age 30 is more than 76%?

    a) 0.2764
    b) 0.7764
    c) 0.2236
    d) 0.8131

    Question 19
    Suppose that 42% of all consumers who purchase bottled water from a supermarket prefer brand x. If a random sample of 425 such consumers is taken, what is the probability that between 35% and 38% prefer brand x?

    a) 0.0457
    b) 0.1056
    c) 0.3944
    d) 0.9507

    Question 20
    Suppose .27 of all workers would switch jobs if they had an opportunity. If 292 workers are randomly selected, what is the probability that between 82 and 90 would switch jobs if they had an opportunity?

    a) 0.1628
    b) 0.2651
    c) 0.4279
    d) 0.5907

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    Solution Preview

    Please see the attached file.

    Question 1 Multiple Choice
    All of the following are reasons to sample except for:
    Reduce sampling error
    The research process is sometimes destructive.
    Save time
    For given resources, broaden the scope of the study.

    Answer: Reduce sampling error

    Question 2 Multiple Choice
    Sampling in which every unit of the population has the same probability of being selected into the sample is sometimes referred to as:
    representative sampling
    fair sampling
    random sampling
    nonrandom sampling

    Answer: random sampling

    Question 3 Multiple Choice
    The most elementary random sampling technique is:
    simple random sampling
    stratified random sampling
    systematic random sampling
    area random sampling

    Answer: simple random sampling

    Question 4 Multiple Choice
    In which of the following sampling techniques does the researcher number every item of the population before taking the sample?
    systematic sampling
    quota sampling
    cluster sampling
    simple random sampling

    Answer: systematic sampling

    Question 5 Multiple Choice
    The main reason for using stratified random sampling is to:
    reduce costs
    make certain that every kth item is selected
    reduce sampling error
    reduce non sampling error

    Answer: reduce costs

    Question 6 Multiple Choice
    Fifty percent of a population possesses attribute X, thirty percent possesses attribute Y, and twenty percent possesses attribute Z. A researcher decides to include some people with attribute X, some with attribute Y, and some with attribute Z in her sample. Her sample consists of 80 people with attribute X, 70 people with attribute Y, and 50 people with attribute Z. The researcher has most likely done what type of sampling?
    systematic sampling
    simple random sampling
    proportionate stratified sampling
    disproportionate stratified sampling

    Answer: disproportionate stratified sampling

    X= 80 40% 50%
    Y= 70 35% 30%
    Z= 50 25% 20%
    200
    Therefore, disproportionate stratified sampling

    Question 7 Multiple Choice
    Another name for cluster sampling is:
    stratified sampling
    quota sampling
    snowball sampling
    area ...

    Solution Summary

    Answers Multiple choice questions on sampling, central limit theorem, normal distribution

    $2.19