Chapter 11
Sampling Procedures
a. a sample.
b. a census.
c. a sampling frame.
d. a universe.
e. none of the above.
a. asking 100 owners their attitude toward a new truck style would be an example of
example of a consensus.
b. asking 80 owners their attitude toward a new gun rack design would be an
example of a sample.
c. asking all owners their attitude toward a new truck style would be an example of
universal testing.
d. asking only owners listed in the telephone directory would be an example of a
sampling frame.
e. None of the above are true.
the population itself because
a. they are typically cheaper than complete counts.
b. they are typically faster than complete counts.
c. they are typically more accurate than complete counts.
d. a and b.
e. a, b, and c.
for making inferences about population, except
a. a census may not be plausible.
b. samples are less expensive.
c. a census has less nonsampling error.
d. a census is less accurate.
e. All of the above are reasons to choose a sample over a census.
a. determine the sample size.
b. define the population.
c. select a sampling procedure.
d. select the sample elements.
e. identify the sampling frame.
a. the geographic boundaries of the population.
b. which elements are not of interest.
c. the time period for the study.
d. a and b.
e. a, b, and c.
a. A low incidence means that a high percentage of the population of interest
qualifies for inclusion in the study.
b. A low incidence means that a low percentage of the population of interest is
expected to respond to the study.
c. A low incidence means that a low percentage of the population of interest
qualifies for inclusion in the study.
d. A low incidence means that a low percentage of the target population will
participate in the study.
e. None of the above are true statements.
proper order for this procedure.
A. Collect the data from the designated elements.
B. Identify the sampling frame.
C. Define the population.
D. Determine the sample size.
E. Select a sampling procedure.
F. Select the sample elements.
a. C,B,D,E,F,A
b. B,C,D,E,F,A
c. F,D,B,E,C,A
d. C,B,E,D,F,A
e. D,C,B,E,F,A
a. is a list of population elements from which the sample will be drawn.
b. is the list of population elements actually included in the sample.
c. usually provides biased statistics.
d. is a form of probability sampling.
e. is a form of nonprobability sampling.
frame?
a. unlisted phone numbers
b. not all homes have phones
c. double counting homes with multiple phone numbers
d. the phone book is always outdated
e. all of the above are true
a. they involve personal judgment somewhere in the selection of sample elements.
b. each population element has an equal chance of being included in the sample.
c. each population element has an equal chance of being included in the sample and
every combination of n population elements is a sample possibility.
d. each population element has a known chance of being included in the sample.
e. they will always be more representative of the population than nonprobability
samples.
a. known
b. unequal
c. equal
d. known and equal
e. known and unequal
a. probability
b. area
c. nonprobability
d. a and b
e. a and c
a. quota
b. area
c. cluster
d. disproportionate stratified
e. systematic
a. nonprobability sample
b. sequential sample
c. fixed sample
d. probability sample
e. all of the above
evidence to draw a conclusion. He then makes additional observations and finds this
evidence inconclusive. He continues making observations until a conclusion can be
drawn. He is using
a. random sampling
b. fixed sampling
c. sequential sampling
d. the principle of diminishing utility
e. nonprobability sampling
a. quota
b. convenience
c. cluster
d. judgment
e. All of the above are nonprobability samples.
a. they allow an assessment of sampling error
b. they are not as representative of the population as probability samples
c. they involve personal judgement somewhere in the selection of sample elements
d. there is only one basic type of nonprobability sample while there are several types
of probability samples
e. they tend to be more expensive than probability samples
to interview every tenth customer entering a K mart store at the following key sites.”
This is an example of ____ sampling.
a. judgement
b. quota
c. sequential
d. simple random
e. convenience.
minimize this, a researcher decides to limit the sample to his personal friends from
whom he is sure to get replies. This is an example of a
a. probability sample.
b. nonprobability sample.
c. random sample.
d. sequential sample.
e. quota sample.
a. the proportion of those possessing a given characteristic are balanced against the
proportion of the population possessing the characteristic.
b. those entering the sample happen to be where the study is being done when it is
being done.
c. each field worker is allowed to judge whether any given respondent would be a
good representative of the population.
d. the sample elements are handpicked by the investigator because it is expected
they can offer the contributions sought.
e. they are superior to other forms of sampling for descriptive studies.
a. convenience sampling.
b. judgement sampling.
c. quota sampling.
d. simple random sampling.
e. stratified sampling.
characteristics in the sample matches the distribution of these same characteristic(s) in
the population. With respect to the representativeness of quota samples, it can thus be
said that
a. a quota sample may be very far off the mark with respect to other important
characteristics likely to influence the result but that were not used as controls
when selecting the sample.
b. the fact that the distribution of the characteristic in the sample parallels the
distribution in the population does not guarantee that the sample is representative.
c. the quota assigned each field worker should exactly mirror the distribution of the
control characteristic(s) in the population.
d. a and b are true.
e. a, b, and c are true.
establishes three different categories of social class in terms of amount of income. He
then assigns each field worker a specified number of interviews with people in each
income category although the interviewers are allowed to select whom they interview.
This is an example of
a. random sampling.
b. systematic sampling.
c. area sampling.
d. quota sampling.
e. probability sampling.
a. the sample could be skewed with respect to a noncontrol characteristic that is
likely to affect the observed variable.
b. interviewers are allowed to choose their subjects and interview locations.
c. it is difficult to verify whether the sample chosen is representative of the
population.
d. b and c.
e. a, b, and c.
a. The controls for a quota sample are usually chosen on the basis that (1) they are
believed to be correlated with the characteristic to be studied, and (2) reasonably
up-to-date information on their distribution within the universe is available.
b. To validate a quota sample, various characteristics of the sample are compared to
known universe values. If the differences in these characteristics are small in the
comparison, this constitutes proof that the sample corresponds to the universe.
c. Quota sampling is the most common kind of probability sampling used in
marketing research.
d. Quota sampling is the only nonprobability sampling method that provides some
measure of the sampling error associated with the sample estimate.
e. All of the above statements are true.
an estimate. Which of the following sampling methods would you recommend he use?
a. convenience
b. quota
c. nonprobability
d. probability
e. judgment
a. Evaluation of the precision of a sample result is important to most researchers and
therefore they seek to use probability samples whenever possible.
b. In general, probability sampling requires personnel who are more skilled and
experienced than nonprobability sampling.
c. A probability sample will usually cost substantially more than a nonprobability
sample of the same size on a per observation basis.
d. One real advantage that probability samples have over nonprobability samples is
their greater economic efficiency.
e. Nonprobability samples can be more accurate than probability samples.
a. they are always more representative than nonprobability samples.
b. one cannot assess the amount of sampling error likely to occur.
c. there is no problem with using nonprobability samples
d. a and b are both true statements.
e. none of the above statements are true.
a. Each element has a known chance of being selected.
b. Each element has a non-zero chance of being selected.
c. Each element has an equal chance of being selected.
d. Each combination of n population elements has an equal chance of being selected.
e. All of the above are true statements.
a. each population element has a known chance of being selected.
b. each population element has an equal chance of being selected.
c. every combination of n population elements is a sample possibility.
d. a and b.
e. a, b, and c.
a. the distribution of all possible sample values of the statistic that could be drawn
from the parent population under the specified sampling plan.
b. the distribution of the variable in the parent population.
c. the distribution of the variable in a particular sample.
d. the spread of the variable in the parent population.
e. the unbiased nature of most sample statistics.
the sampling plan is equal to the parameter it estimates.
a. biased; median
b. efficient; average
c. unbiased; mean
d. sample; biased
e. unbiased; extreme
a. A sampling distribution is the probability distribution of elements from a
particular sample.
b. The standard error of the mean is the standard deviation of the sampling
distribution of sample means.
c. The sampling distribution of the mean is another name for the frequency
distribution that results from a single sample.
d. The sampling distribution of the mean is another name for the distribution of
means corresponding to the samples that could be drawn under the specified
sampling plan.
e. Both b and d are true.
parent population with a mean, u, and variance σ2; he should realize that n is ___, the
sample mean x is ___ distributed with mean x and variance σ 2/n (assuming the sample
represents a small proportion of the population).
a. small; normally
b. large; normally
c. small; binominally
d. large; binominally
e. none of the above
population mean?
a. a confidence level
b. a point estimate of the population mean
c. an estimate of the sampling error associated with the sample mean
d. all of the above
e. a and b above
following expressions when sampling without replacement from a finite population?
a. σ_2 = (σ 2/n)[(N-n)/(N-1)]
x
b. σ_2 = (σ 2/n)
x
c. σ_2 = (σ 2/n)N
x
d. σ_2 = σ 2
x
e. None of the above are true.
population mean when which of the following conditions is true? Choose the best
possible answer.
a. Sampling is with replacement.
b. Sampling is with or without replacement.
c. Sampling is from an infinite population.
d. Sampling is from a finite population.
e. Sampling is with or without replacement and from an infinite or finite population.
formula, x – σ < µ > x + z σ _. The interval means that
x x
a. there is a 95 percent probability that the population mean is within the established
interval.
b. 95 percent of the sample values lie within the established interval.
c. 95 percent of the population values lie within the established intervals.
d. 95 percent of the intervals constructed employing this procedure would contain
the true population mean and this interval is hopefully one of those 95 out of 100.
e. none of the above.
sampling is that
a. only stratified samples involve partitioning the parent population into mutually
exclusive and exhaustive subsets.
b. only stratified samples allow the a priori determination of the probability that any
population element will be included in the sample.
c. only stratified samples make the probability of selection of any population
element equal.
d. only stratified samples involve partitioning the parent population into mutually
exclusive and exhaustive subsets and selecting a simple random sample from each
subset.
e. none of the above.
a. A stratified random sample is drawn by dividing the parent population into
mutually exclusive and exhaustive subsets and by then taking a random sample of
these subsets.
b. The basic rule by which we stratify suggests the resulting strata should be as
homogeneous as possible.
c. When sampling from a population that is highly skewed, a stratified sample
generally provides the most representative sample.
d. A market researcher needs information about parts of the universe, as well as the
total universe. He should therefore plan on using a stratified random sample.
e. Stratified sampels are more statistically efficient than simple random samples.
users. He then chooses a random sample independently from each group. This is an
example of ___ sampling.
a. nonprobability
b. random
c. judgmental
d. stratified
e. quota
a. stratified sampling ensures adequate representation from each stratum of interest.
b. stratified sampling can produce more precise sample statistics.
c. stratified sampling allows for the comparison of variables between strata.
d. b and c.
e. all of the above.
stratified sample and that constructed employing a simple random sampling is that
with the stratified sample
a. a point estimate of the population mean is not required.
b. determination of the estimate of the mean and standard error of estimate involves
the use of weights.
c. the strata results are appropriately weighted by a method of curvilinear estimation.
d. inferences are drawn on the basis of the known population mean and variance.
e. the researcher does not need to specify the degree of confidence.
a. When sampling from a population that is highly skewed, a cluster sample
generally provides the most representative sample.
b. Stratified sampling is a very useful sampling technique. It allows closer
examination of the characteristics of particular subgroups. It also lowers the
chance of error by ensuring that subgroups are adequately represented in the
sample. However, this method generally produces less precise estimates of
population values than simple random samples.
c. In calculating the standard error of the mean when using a stratified sample, one
finds that differences among strata means do not enter the estimate.
d. When using proportional allocation in stratified random sampling, one samples
from each of the strata in proportion to their respective variabilities.
e. All of the above statements are true.
a. income
b. age
c. gender
d. occupation
e. education
error employing a stratified sample?
a. when the population is partitioned so that the number of elements in each stratum
is proportional to size of the sample to be taken from each stratum.
b. when the population is partitioned so that the elements in each stratum are equal
c. when the population is partitioned in such a way that the variances within strata
are equal
d. when the population is partitioned so that the elements in each stratum are
normally distributed
e. none of the above
sampling is that
a. the within-strata variability does not enter into the calculation of the standard
error of estimate.
b. the between-strata variability does not enter into the calculation of the standard
error of estimate.
c. neither the within-strata variability nor the between-strata variability enters into
the calculation of the standard error of estimate.
d. the confidence interval is wider than that established employing simple random
sampling.
e. the sample mean provides a biased estimate of the population mean.
stratum
a. is in direct proportion to the relative number of elements in each stratum in the
population.
b. is in direct proportion to the relative variability of the characteristic in each
stratum in the population.
c. varies directly with the heterogeneity of each stratum.
d. varies directly with the homogeneity of each stratum.
e. is none of the above.
sample are
a. strata size.
b. strata heterogeneity.
c. strata variances on the variable of interest.
d. a and b.
e. a, b, and c.
consumption of a given good than those with low incomes. What type of sample
would produce the most efficient estimate of the average consumption per individual?
a. simple random sample
b. disproportionate stratified sample
c. proportionate stratified sample
d. quota sample
e. systematic sample
stratified sampling, elements are selected ____, while with quota sampling they are
selected ____.
a. statistically; deterministically
b. probabilistically; judgmentally
c. judgmentally; probabilistically
d. probabilistically; randomly
e. empirically; deterministically
consumers are
a. perform a census of two systematically chosen strata.
b. divide the consumers into separate groups on the basis of age categories (e.g.,
<18, 19-24, 25-34, 35-44, 45-64, 65+).
c. perform simple random sampling in all the strata.
d. randomly choose two age categories and interview all or some of those
consumers.
e. b and d.
equal populations. He then selects a random sample of blocks and sends interviewers
to each block. The interviewers are instructed to interview every eighth dwelling unit.
This is ___ sampling.
a. one-stage cluster
b. two-stage cluster
c. quota
d. two-stage systematic
e. stratified
sampling plans is that
a. cluster samples provide each population element with an equal chance of being
included in the sample.
b. cluster samples provide each population element with a known chance of being
included in the sample.
c. cluster samples involve the partitioning of the parent population into mutually
exclusive and exhaustive subsets.
d. cluster samples involve the partitioning of the parent population into mutually
exclusive and exhaustive subsets and the probabilistic selection of elements from
each subset.
e. none of the above.
a. In cluster sampling, the parent population is broken into mutually exclusive and
exhaustive subgroups and a simple random sample is selected from each
subgroup.
b. Cluster samples are most statistically efficient when the clusters are internally
homogeneous.
c. In order to yield high statistical efficiency, each cluster in a cluster sample should
include as many diverse universe values as possible.
d. One of the main advantages of cluster sampling over simple random sampling is
its greater statistical efficiency for the same size sample.
e. All of the above statements are false.
a. is often traded off for increased economic efficiency.
b. is apparent if one samples 50 population elements instead of 20.
c. is the same as the overall efficiency of a sampling plan.
d. can be offset by observational efficiency.
e. b and d.
a. cluster sampling.
b. stratified sampling.
c. quota sampling.
d. convenience sampling.
e. simple random sampling.
population elements by name in order to draw a sample?
a. stratified sample
b. systematic sample
c. simple random sample
d. cluster sample
e. quota sample
efficiency which suggests ____ and economic considerations which suggest ____.
a. the need for accuracy; that benefits be considered
b. a small number of areas be used; few areas be used
c. a large number of areas be used; few areas be used
d. that a small sample size can be used to predict accurately; possible losses due to
faulty predictions can be costly
e. that a large number of areas be used; a large number of observations within each
area be collected
each. He requires a sample of 400 households. He then selects his sample by
choosing 100 blocks and 4 households per block. This is an example of ____.
a. systematic sampling
b. two-stage area sampling
c. probability-proportional-to-size sampling
d. one-stage area sampling
e. sequential sampling
households per block. The second stage sampling fraction is ____.
a. 8/10
b. 1/8
c. 1/10
d. 1/2
e. indeterminate
a. a certain proportion of second-stage units be selected from each first-stage unit.
b. a fixed number of second-stage units be selected from each first-stage unit
selected.
c. a variable ratio of first-stage units be selected.
d. a variable proportion of first-stage units be selected.
e. none of the above.
five households for each block designated for inclusion in the sample. The blocks
themselves are to be selected with variable probabilities depending on their size. This
is an example of
a. one-stage area sampling.
b. quota sampling.
c. simple two-stage area sampling.
d. probability-proportional-to-size area sampling.
e. systematic sampling.
a) there may exist sampling biases in internet research
b) larger samples are always better for surveys
c) small samples suffice for focus groups
d) convenience samples can, on occasion, be used to generalize to the target population
e) larger samples are necessary for greater confidence levels (as z goes from 1.96 to 2.58)