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Marketing Research > Chapter 9: Selecting the Sample > Flashcards

Chapter 9: Selecting the Sample Flashcards

1
Q

Define: Population

A

Population is defined as the entire group under study as specified by the objective of the research project.

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2
Q

_______ tend to have a less specific definition of the population than do researchers, because they use it in a more general way.

A

Managers tend to have a less specific definition of the population than do researchers, because they use it in a more general way.

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3
Q

Define: Census

A

Census is defined as an accounting of the complete population.

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4
Q

True or False: Conducting a census is a practical way to collect data.

A

False: Conducting a census is a very impractical way to collect data. It is virtually impossible to obtain information from every single US household

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5
Q

Define: Sample

A

Sample is defined as a subset of the population that suitably represents that entire group.

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6
Q

Define: Sample Unit

A

Sample Unit is defined as the basic level of investigation.

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7
Q

The sample is a ______ of the population, and the sample unit pertains to the __________.

A

The sample is a subset of the population, and the sample unit pertains to the basic level of investigation.

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8
Q

Define: Sample Frame

A

A sample frame is a master source of sample units in the population.

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9
Q

True or False: The sample frame does not always correspond perfectly to the sample.

A

True: The sample frame does not always correspond perfectly to the sample.

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10
Q

Define: Sample Frame Error

A

Sample frame error is defined as the degree to which the sample frame fails to account for all of the population

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11
Q

What is a good way to envision sample frame error?

A

A good way to envision sample frame error is by comparing the list with the population and seeing to what degree the list adequately matches the targeted population.

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12
Q

Has the booming social media marketing phenomenon given marketing researchers an easier task or harder task?

A

The booming social media marketing phenomenon has given marketing researchers immense challenges because users of social media are difficult to identify.

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13
Q

Define: Sampling Error

A

Sampling error is any error in a survey that occurs because a sample is used.

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14
Q

Sampling error is caused by _____ factors.

A

Sampling error is caused by two factors: a) the method of sample selection, which includes sample frame error and b) the size of the sample

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15
Q

Explain two general reasons why a sample is almost always more desirable than a census.

A

Taking a sample is less costly and more practical, making a sample more desirable than a census. The typical researcher cannot analyze the huge amounts of data generated by a census.

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16
Q

Before researchers consider the size of computer or tabulation equipment to be used, they must consider the various _______ involved in handling the questionnaires and responses and transferring these responses into computer files.

A

Before researchers consider the size of computer or tabulation equipment to be used, they must consider the various data preparation procedures involved in handling the questionnaires or responses and transferring these responses into computer files.

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17
Q

All sample designs fall into one of two categories….

A

All sample designs fall into one of two categories: probability or nonprobability.

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18
Q

Define: Probability Samples

A

Probability samples are defined as samples in which members of the population have a known chance (probability) of being selected into the sample.

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19
Q

Define: Nonprobability Samples

A

Non-probability samples are defined as samples where the chances (probability) of selecting members from the population into the sample are unknown.

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20
Q

Unfortunately, the terms known and unknown are misleading… why?

A

The terms known and unknown are misleading; to calculate a precise probability, one would need to know the exact size of the population , and it is impossible to known the exact size of the population in most marketing research studies.

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21
Q

True or false: In most cases, the population size is known and stable enough to be associated with an exact number

A

False. In most cases, the population size is unknown and is not stable enough to be associated with an exact number.

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22
Q

Is the probability value calculated?

A

In reality, the probability value is never really calculated, but we are assured by the sample method that the chances of any one population member being selected into the sample could be computed.

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23
Q

Is the nonprobability value calculated?

A

There is no way to determine the probability with nonprobability methods even if the population size is known because the selection technique is subjective.

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24
Q

Nonprobability sampling uses __________, whereas probability sampling does not.

A

Nonprobability sampling uses human intervention, whereas probability sampling does not.

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25
Q

Nonprobability sampling is sometimes called __________ because it is prone to human error and even subconscious biases.

A

Nonprobability sampling is sometimes called “haphazard sampling” because it is prone to human error and even subconscious biases.

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26
Q

Name the four probability sampling methods.

A

The four probability sampling methods are simple random sampling, systematic sampling, cluster sampling and stratified sampling.

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27
Q

Define Simple Random Sampling.

A

Simple random sampling is defined as the probability of being selected into the sample is equal for all members of the population

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28
Q

What is the formula for simple random sample selection probability?

A

probability of selection = sample size/population size

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29
Q

Define the Random Device Method

A

The random device method involves using an apparatus of some sort to ensure that every member of the population has the same chance of being selected into the sample .

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30
Q

What is a familiar example of the random device method?

A

A familiar example of the random device method is flipping a coin to decide heads or tails.

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31
Q

True or false: In every case, every member of the population has the same probability of being selected as every other member of that population in the random device method.

A

True. Using the random device method, every member of the population has the same probability of being selected into the sample in every case.

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32
Q

Define systematic sampling

A

Using a sample frame that lists members of the population, the researcher selects a random starting point for the first sample member. A constant skip interval is used to select every other sample member from the sample frame.

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33
Q

Does systematic sampling have the same end result as simple random sampling?

A

Yes, systematic sampling has the same end result as simple random sampling, but it is more efficient.

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34
Q

Define: Cluster Sampling

A

Cluster sampling is when the sample frame is divided into groups, called clusters, each of which must be considered to be similar to the others. The researcher randomly selects a few clusters and performs a census of each one (one stage) or randomly selects more clusters and takes samples from each one (two stage).

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35
Q

When is cluster sampling desirable?

A

Cluster sampling is desirable when highly similar clusters can be easily identified.

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36
Q

Define: Stratified Sampling

A

Stratified sampling is when the population is believed to have a skewed distribution for one or more of its distinguishing factors - the researcher identifies subpopulations in the sample frame called strata. A simple random sample is then taken of each stratum. Weighting procedures may be applied to estimate population values, such as the mean.

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37
Q

When is stratified sampling better suited?

A

Stratified sampling is better suited than other probability sampling methods for populations that are not distributed in a bell-shaped pattern.

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38
Q

Define: Blind Draw

A

An example of a blind draw is writing the name of every student on an index card, placing the cards in a container, shaking the container, and ask another person to draw the sample.

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39
Q

Define: Random Numbers

A

Random numbers are numbers whose chance nature is assured.

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40
Q

Why is simple random sampling appealing?

A

Simple random sampling is an appealing sampling method simply because it embodies the requirements necessary to obtain a probability sample and, therefore, to derive unbiased estimates of the population’ characteristics. Simple random sampling guarantees that every member of the population has an equal chance of being selected into the sample. Therefore, the resulting sample will be a valud representation of the population.

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41
Q

What are the disadvantages of using simple random sampling?

A

Some disadvantages of using simple random sampling is the necessity to predesignate each population member. Complete listings are sometimes incomplete or inaccurate listings of populations and contain sample frame error. If the sample frame does not exist electronically, it can be cumbersome to manually provide unique designations for each population member.

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42
Q

What are the two practical applications in which simple random sample designs are employed quite successfully.

A

The two practical applications in which simple random sampling designs are employed successfully are random digit dialing and computer based random samples.

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43
Q

Define: Random Digit Dialing (RDD)

A

Random digit dialing is used in telephone surveys to overcome the problems of unlisted and new telephone numbers.

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44
Q

Define: Plus-one Dialing Procedure

A

Plus-one dialing procedure is a convenient variation of random digit dialing, in which numbers are selected from a telephone directory and a digit, such as “1” is added to each number to determine which telephone number is then dialed.

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45
Q

Which types of companies have the greatest opportunity to use RDD and plus-one dialing procedure?

A

Companies with credit files, subscription lists, or marketing information systems have the greatest opportunity to use this approach.

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46
Q

Which type of sampling has fallen in popularity since computerized databases and generated random number features have become widely available?

A

Systematic sampling has fallen in popularity since computerized databases and generated random number features have become widely available.

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47
Q

When would systematic sampling be chosen over simple random sampling?

A

In the special case of a physical listing of a population, systematic sampling is often chosen over simple random sampling based primarily on the economic efficiency it represents.

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48
Q

True or False: To use systematic sampling, it is necessary to obtain a hard-copy listing of the population.

A

True. To use systematic sampling, it is necessary to obtain a hard-copy listing of the population.

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49
Q

Define: Skip Interval

A

A skip interval is calculated by dividing the number of names on the list by the sample size, as can be seen in the following formula:

Skip interval = population list size/sample size

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50
Q

Systematic sampling is probability sampling because it employs a _________, which ensures there is sufficient randomness in the systematic sample to approximate an equal probability of any member of the population being selected into the sample.

A

Systematic sampling is probability sampling because it employs a random starting point, which ensures there is sufficient randomness in the systematic sample to approximate an equal probability of any member of the population being selected into the sample.

51
Q

In systematic sampling, the random starting point guarantees that the selected sample is selected _______.

A

In systematic sampling, the random starting point guarantees that the selected sample is selected randomly.

52
Q

What is the essential difference between systematic sampling and simple random sampling?

A

The essential difference between systematic sampling is the system used in systematic sampling is the skip interval, whereas the randomness in simple random sampling is determined through the use of successive random draws.

53
Q

The efficiency in systematic sampling is gained by two features, what are they?

A

The efficiency in systematic sampling is gained by two features: the skip interval aspect and the need to use random numbers only at the beginning.

54
Q

What is the greatest danger in the use of systematic sampling?

A

The greatest danger in the use of systematic sampling lies in the listing of the population (sample frame).

55
Q

A cluster sampling method divides the population into groups, any one of which can be considered _________.

A

A cluster sampling method divides the population into groups, any one of which can be considered a representative sample.

56
Q

The ____ concept behind cluster sampling is similar to the one described for systematic sampling, but the _______ differs.

A

The basic concept behind cluster sampling is similar to the one described for systematic sampling, but the implementation differs.

57
Q

Which is more efficient: cluster sampling or systematic sampling?

A

Cluster sampling goes a step further in striving to gain economic efficiency over systematic sampling by simplifying the sampling procedure used.

58
Q

Define: Area Sampling

A

In area sampling, the researcher subdivides the population to be surveyed into geographic areas.

59
Q

Define: One-Step Area Sample

A

With the one-step area sample, the researcher may believe the various geographic areas (clusters) to be sufficiently identical to allow concentrating his or her attention on just one area and then generalizing the results to the full population.

60
Q

Which step area sample requires the researcher to select an area randomly and perform a census of its members?

A

The one-step area sample requires the researcher to select an area randomly and perform a census of its members.

61
Q

Define: Two-Step Area Sample

A

The two-step area sample requires for the first step, the researcher could select a random sample of areas, and then for the second step, he or she could decide on a probability method to sample individuals within the chosen areas.

62
Q

Why is the two-step area approach preferable to the one-step area approach?

A

The two-step area approach is preferable to the one-step area approach because there is always the possibility that a single cluster may be less representative than the researcher believes.

63
Q

Which step area approach is more costly?

A

The two-step area approach is more costly because ore areas and time are involved.

64
Q

What is a variation of the area sampling method?

A

Area grid sampling is a variation of the area sampling method.

65
Q

Describe area grid sampling.

A

In area grid sampling, the researcher imposes a grid over a map of the area to be surveyed. Each cell within the grid then becomes a cluster.

66
Q

What is the difference between area grid sampling and area sampling?

A

The difference between area grid sampling and area sampling is the grid framework, which cuts across natural or artificial boundaries, such as streets, rivers, city limits, or other separations normally used in area sampling.

67
Q

___________ has been used to describe the demographic profiles of the various clusters.

A

Geodemography has been used to describe the demographic profiles of the various clusters.

68
Q

What is the greatest danger in cluster sampling?

A

The greatest danger in cluster sampling is cluster specification error that occurs when the clusters are not homogeneous.

69
Q

Most researchers encounter a population that is not distributed symmetrically across a normal curve. Unless adjustments are made, the sample will be __________ or inaccurate.

A

Most researchers encounter a population that is not distributed symmetrically across a normal cure. Unless adjustments are made, the sample will be statistically inefficient, or inaccurate.

70
Q

Define: Stratified Sampling

A

Stratified Sampling separates the population into different subgroups and then samples all of these subgroups.

71
Q

True or False: Stratified sampling is a solution to statistically inefficient data

A

True: Stratified sampling is a solution to statistically inefficient data.

72
Q

Define: Skewed Population

A

Skewed populations deviate greatly from the bell-shaped distribution that is assumed to be the case in the use of simple random, systematic or cluster sampling.

73
Q

True or False: If simple random, systematic, or cluster sampling were used to draw the sample from a skewed distribution, it most certainly would be accurate.

A

False: If simple random, systematic, or cluster sampling were used to draw the sample from a skewed distribution, it most certainly would be inaccurate.

74
Q

With stratified random sampling, one takes a skewed population and identifies the subgroups, or ______, contained within it.

A

With stratified random sampling, one takes a skewed population and identifies the subgroups, or strata, contained within it.

75
Q

Define: Strata

A

Strata is defined as the subgroups contained within a skewed population.

76
Q

When is stratified sampling appropriate?

A

Stratified sampling is appropriate when we expect that responses will vary across strata, or groups in the population.

77
Q

Once strata are identified within the skewed population, ______ sampling is used to draw a sample from each stratum because we typically believe that the individual strata have bell-shaped distribution.

A

Once strata are identified within the skewed population, probability sampling is used to draw a sample from each stratum because we typically believe that the individual strata have bell-shaped distribution.

78
Q

How does stratified sampling result in a more accurate overall sample?

A

Stratified sampling results in a more accurate overall sample by allowing for explicit analysis of each stratum and there is a procedure that allows for the estimation of the overall sample mean by use of a weighted mean.

79
Q

Define: Weighted Mean

A

Weighted mean takes into consideration the sizes of the strata relative to the total population size and applies those proportions to the strata’s means.

80
Q

What is the formula for the weighted mean?

A

Mean = (mean)(proportion) + (mean)(proportion)

81
Q

When is stratified sampling useful

A

When marketing researchers encounter skewed populations

82
Q

When is it advantageous to preserve the diversity of the various subgroups by applying stratified sampling?

A

When the population is not normally distributed

83
Q

Define: Surrogate measure

A

some observable or easily determined characteristic of each population member

84
Q

What is a surrogate measure used for?

A

to help partition or separate the population members into their various subgroupings

85
Q

Researchers may divide the population into as many relevant _____ as necessary to capture different subpopulations

A

Strata

86
Q

The key issue is that researchers should use some basis for dividing the population into strata that results in _________

A

different responses across strata.

87
Q

There should be some ____ or ______ to the stratification system

A

There should be some logic or usefullness to the stratification system

88
Q

If the strata sample sizes are faithful to their relative sizes in the population, the research design reflects a _____________

A

Proortionate stratified sample

89
Q

In a proportionate stratified sample, you do not need to use the _____________ because each stratum’s weight is automatically accounted for by its sample size.

A

In a proportionate stratified sample, you do not need to use the weighted formula because each stratum’s weight is automatically accounted for by its sample size.

90
Q

Some researchers opt to use the _______ rather than the relative size as a factor in deciding stratum sample size

A

Some researchers opt to use the stratum relative variability rather than the relative size, as a factor in deciding stratum sample size

91
Q

If a stratum has low variability, precise estimates of that stratum may be obtained with a ______

A

small sample size

92
Q

Define: statistical efficiency

A

For the sample size, researchers may obtin equivalent precision among the strata

93
Q

Define: disproportionate stratified sampling

A

a weighted formula needs to be used because the strata sizes do not reflect their relative proportions in the population

94
Q

With _______________, selection is not based on chance or randomness. It is based on an inherently biased selection process, typically to reduce the cost of sampling

A

nonprobability sampling method

95
Q

With nonprobability sampling, the researcher has some savings, but at the expense of

A

using a sample that is not truly representative of the population

96
Q

What are the four nonprobability sampling methods:

A

convenience samples, purposive samples, referral samples, and quota samples

97
Q

Define: convenience samples

A

the most convenient areas to a researcher in terms of reduced time and effort turn out to be high-traffic areas, such as shopping malls or busy pedestrian intersections

98
Q

True or false: in convenience sampling, certain members of the population are automatically eliminated form the sampling process

A

True

99
Q

To reduce convenience sample selection error, the researcher could use a _____

A

quota system

100
Q

Convenience samples disallow members of the population from

A

being represented in the sample.

101
Q

Define: purposive samples

A

require a jdugement or an “educated guess” as to who should represent the population.

102
Q

Purposive samples are sometimes called

A

judgement samples or exemplar samples

103
Q

Purposive samples are highly subjective and

A

prone to much error

104
Q

______ studies use purposive sampling rather than probability sampling

A

focus group studies

105
Q

Define: referral samples

A

require respondents to provide the names of prospective respondents

106
Q

referral samples are sometimes known as

A

“snowball samples”

107
Q

Referral samples are most appropriate when

A

there is a limited or disappointingly short sample frame and when respondents can provide the names of others who would qualify for the survey

108
Q

True or false: Referral samples do not rely heavily on social networks

A

False

109
Q

Define: quota samples

A

specified percentages of the total sample for various types of individuals to be interviewed

110
Q

Quota samples are commonly used by marketing researchers who rely on mall intercepts, a _________ sample method

A

convenience

111
Q

Qhotas are determined through application of the research objectives and are defined by

A

key characteristics used to identify the population

112
Q

A quota sample ____ some of the nonrepresentativeness inherent in convenience samples

A

reduces

113
Q

When done conscientiously and with a firm understanding of the population’s characteristics, quota sampling can rival _______ in the minds of researchers

A

probability sampling

114
Q

Three types of samples used with online surveys

A

online panels, river samples, and list samples

115
Q

Define: online samples

A

large numbers of individuals who have agreed to participate in online surveys.

116
Q

Normally, online panel participants have registered with a _______ and have agreed to participate in surveys with some sort of compensation

A

panel company

117
Q

True or false: there are no concerns about the representativeness of samples provided by panel companies

A

false

118
Q

Define: river sample

A

created via the use of banners, pop-ups, or other online devices that invite website visitors to take part in the survey. the “river” is the steady stream of website visitors

119
Q

What is the sample frame of a river sample?

A

The stream of visitors visiting the site issuing the invitation

120
Q

Are river samples considered random samples of sample frames?

A

Yes, as long as the invitations are not unusual in duration, appearance, or relevance.

121
Q

Define: email list samples

A

purchased or otherwise procured from someone or some company that has compiled email addresses of opt-in members of the population of interest

122
Q

Define: sample plan

A

the researcher goes through to draw and ultimately arrives at the final sample

123
Q

What are the 6 steps in a sample plan?

A
  1. define the population
  2. obtain a sample frame
  3. decide on the sample method
  4. decide on the sample size
  5. draw the sample
  6. validate the sample

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