45) When using ________, sample size is unrelated to accuracy, so cost-benefit considerations
must be used.
A) nonprobability sampling
B) probability sampling
C) cluster sampling
D) stratified sampling
46) It is common practice for marketing researchers, particularly the do–it–yourselfers, to
consider ________ to be a random sample.
A) a mall intercept sample
B) a panel sample
C) a telephone sample
D) a group sample
47) The accuracy of a sample is a measure of how closely it reports the true values of the
population it represents.
48) Only a non-probability sample, typically referred to as a random sample, is truly
representative of the population and, second, the size of that random sample determines the
sample’s accuracy of findings.
49) Sample accuracy refers to how close a random sample’s statistic is to the population’s value it
represents.
50) The selection method and the size of the sample determines a sample’s representativeness.
51) Researchers are concerned with sample size because a significant cost savings occurs when
the correct sample size is calculated and used.
52) Thousands of consumers have joined online panels, which are mega-populations that
represent consumer markets of many types.
53) A sample size decision is usually a compromise between what is theoretically perfect and
what is practically feasible.
54) The size of a sample has everything to do with its representativeness. Sample size affects the
sample accuracy.
55) The confidence interval approach is not the correct method by which to determine sample
size.
56) Confidence interval approach applies the concepts of accuracy (margin of sample error),
variability, and confidence interval to create a “correct” sample size.
57) The only perfectly accurate sample is a census.
58) Sampling error pertains to all sources of error other than the sample selection method and
sample size, including problem specification mistakes, question bias, data recording errors, or
incorrect analysis.
59) A random sample will always have some inaccuracy, which is referred to as margin of
sample error or simply sample error.
60) The larger a random sample, the more inaccurate, meaning the less margin of sample error.
61) Margin of sample error can be calculated with a simple formula and expressed as a ±%
number.
62) With a sample size of 1,000 or more, there is a significant gain in accuracy especially when
doubling or tripling the sample size.
63) When researchers find a wide dispersion of responses-that is, when they do not find one
response option accounting for a large number of respondents relative to the other items–
researchers say that the results have much variability.
64) If most respondents indicate the same answer on the response scale, the distribution has
much variability because respondents are highly similar.
65) If respondents are evenly spread across the question’s response options, there is much
variability because respondents are quite dissimilar.
66) A 90/10 split in response signifies maximum variability (dissimilarity) in the population,
whereas a 50/50 split signifies little variability.
67) You can take any finding in the survey, replicate the survey with a random sample of the
same size, and be “very likely” to find the same finding within the ±% range of the original
sample’s finding.
68) A confidence interval is based on the normal, or bell–shaped, curve commonly found in
statistics.
69) In almost all situations, the sample size and the size of the population are related to each
other.
70) A random sample size can be a very tiny percent of the population size and still have a small
margin of sample error.
71) The only time the population size is a consideration in sample size determination is in the
case of a “small population,”
72) The variability believed to be in the population, the acceptable margin of sample error, and
the level of confidence required in your estimates of the population values describe the basic
elements of the central limit theorem.
73) A researcher can calculate sample size using either a percentage or a mean.
74) The amount of sample error the researcher will permit to be associated with the survey is
relational margin of sample error.
75) When applying the standard sample size formula using percentages, there are two
alternatives: (1) expect the worst case or (2) guesstimate the actual variability.
76) Any p/q combination other than 50%/50% will result in a higher calculated sample size
because p times q is in the numerator of the formula.
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77) A lower sample size means less effort, time, and cost, so there are good reasons for a
researcher to try to estimate p rather than to take the worst case.
78) If the project director has conflicting information or is worried about the timeliness or some
other aspect of the information about the population’s variability, he or she may begin the full
study early so he or she can estimate p more confidently.
79) The marketing manager intuitively knows that small samples are less accurate, on average,
than are large samples. But it is rare for a marketing manager to think in terms of sample error.
80) Because the sampling process is imperfect, it is inappropriate to use an estimate of sampling
error in the calculation of this range.
81) The final agreed-to sample size is a trade-off between acceptable error and research cost.
82) Arbitrary sample size approaches rely on erroneous rules of thumb.
83) “Percent rule of thumb” methods lose sight of some of the accuracy aspects of sampling; but
are cost-effective when the population under study is large.
84) The conventional sample size approach ignores the circumstances surrounding the study at
hand and may well prove to be much more costly than would be the case if the sample size were
determined correctly.
85) Sample sizes based on statistical analysis criteria can be quite small.
86) On occasion, a research objective is to perform subgroup analysis, which is an investigation
of subsegments within the population. The effort to gain knowledge about subgroups has direct
implications for sample size.
87) Focus on budget factors usually ignores the value of the survey’s results to management and
does not consider sample accuracy at all.
88) As a general rule, a small population situation is one in which the sample exceeds 15% of the
total population size.
89) Sample size determines the accuracy, not the representativeness, of the sample.
90) For probability sampling, sample size is a judgment based almost exclusively on the value of
the biased information to the manager, rather than desired precision, relative to cost.
91) Most panel companies claim random selection of some sort, so there is the appearance of a
random sample of the population.
92) Using a panel company is inexpensive, expedient, and guarantees delivery of the specified
number of completed surveys.
93) The statement “a sample size decision is usually a compromise between what is theoretically
perfect and what is practically feasible” underscores the importance of why a marketing
researcher should have a basic understanding of sample size determinations. List and describe
the two primary reasons why a marketing researcher should have this basic understanding.
94) Define the terms variability, confidence interval, and acceptable margin of sample error.
95) In practice, a number of different methods are used to determine sample size including those
described as “other methods of size determination.” Most of the other methods have limitations
that make them undesirable. Define and describe “rule of thumb,” “conventional sample size,”
and amount of allocated budget sample approaches. List one major drawback of each.
96) How does a researcher calculate variability in the population?
97) How does a researcher determine the amount of acceptable sample error? What is the role of
marketing research director in determining the amount of acceptable sample error?
98) Describe how a marketer decides on the level of confidence in a study. What is the typical
approach in marketing research?
99) The researcher must take cost into consideration when determining sample size. What are the
factors involved in balancing sample size with cost of data collection?
100) Two sampling situations raise special considerations–sampling from small populations and
sample size when using a nonprobability sampling method. Describe each of these two situations
and the way these sampling situations are best approached.