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MARK 302 > CH05 Sample Design > Flashcards

CH05 Sample Design Flashcards

1
Q

define sampling

A

sampling: the process of obtaining information from a subset of a larger group

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2
Q

what is the main goal of sampling?

A

to be able to make these estimates more quickly and at a much lower cost than would be possible by other means

it has been shown time and again that sampling a small percentage of a population can produce very accurate estimates about the population

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3
Q

what is the key to making accurate predictions about the characteristics or behavior of a large population?

A
  • the sample must be selected in a scientific manner, ensuring that the sample is representative, that it is a true miniature of the population
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4
Q

what is a population?

A

population: an entire group of people about whom information is needed

also called ‘universe’ or ‘population of interest’

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5
Q

what is a census?

A

census: collection of data obtained from or about every member of the population of interest

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6
Q

what is a sample?

A

sample: a subset of all the members of the population of interest

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7
Q

true or false: a census provides more accurate results than a sample

A

false: the researcher may not be able to obtain a complete and accurate list of the entire population, or certain members of the population may refuse to provide information or be difficult to find

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8
Q

name the 7 steps to developing a sampling plan (exhibit 5.1)

A

developing a sampling plan:
1. define the population of interest
2. choose a data-collection method
3. identity a sampling frame
4. select a sampling method
5. determine the sample size
6. develop operational procedures for selecting sample elements
7. execute the operational sampling plan

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9
Q

what is the first thing to consider when creating a sampling plan?

A

to clearly define the qualities or features of the people or things (like customers, companies, or stores) from whom we need information in order to achieve our research goals

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10
Q

the population of interest is often specified in terms of what? (exhibit 5.2)

A
  • geographic area
  • demographic characteristics
  • product or service usage characteristics
  • brand awareness measures
  • or other factors …
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11
Q

why must researchers exclude some individuals from completing a survey? (exhibit 5.3)

A

some individuals should be excluded for security reasons; those who work in the industries in question (eg. a family member working in marketing or advertising) are viewed as security risks

they may be competitors or work for competitors, and managers do not want to give them any indication of what their company may be planning to do

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12
Q

how are researchers selecting data-collection methods today?

A

increasingly, researchers are turning to methodologies that involve blending sample based on interviews collected by different means such as mail-telephone-internet panel-, internet panel-SMS (text), internet panel-social media, etc.

as respondents become more difficult to reach by the old standbys, we have to offer new means of responding that are engaging and convenient. in the process, we need to make sure samples are still representative and results are still accurate.

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13
Q

define a sampling frame

A

sampling frame: a list of population elements from which unites to be sampled can be selected or a specified procedure for generating such a list

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14
Q

developing a sampling method depends on what elements?

A

developing a sampling method depends on
- the objectives of the study
- the financial resources available
- time limitations
- the nature of the problem under investigation

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15
Q

the major alternatives in sampling methods can be grouped under which 2 subheadings?

A

probability and non-probability sampling methods (see exhibit 5.4)

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16
Q

define probability samples

A

probability samples: samples in which every element of the population has a known, nonzero likelihood of selection

anyone/anything could be selected

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17
Q

which is the best-known and most widely used probability sampling method?

A

simple random sampling = best known and most widely used and probability sampling method

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18
Q

define sampling error

A

sampling error occurs when the procedures are followed strictly, the laws of probability hold, and it allows calculation of the extent to which a sample value can be expected to differ from a population value

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19
Q

how can the sampling methods be classified (exhibit 5.4)

A

sampling methods include:
probability sampling:
- systematic
- stratified
- cluster
- simple random
OR
non-probability sampling
- convenience
- judgment
- snowball
- quota

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20
Q

what are some of the questions you should ask when selecting an online panel provider?

A
  • what recruitment methods do you use?
  • do they really have an effective opting in process?
  • what sources do they use?
  • is this a panel that is actively managed or database driven?
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21
Q

define nonprobability sampling

A

nonprobability sampling: samples in which specific elements from the population have been selected in a nonrandom manner

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22
Q

define purposeful nonrandomness

A

purposeful nonrandomness occurs when a sampling plan systematically excludes or overrepresents certain subsets of the population

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23
Q

list some of the advantages of probability sampling over nonprobability sampling

A
  • the researcher can be sure of obtaining information from a representative cross-section of the population of interest
  • sampling error can be computed
  • the survey results can be projected to the total population
    eg. if 5% of the individuals in a probability sample give a particular response, the researcher can project this percentage, plus or minus the sampling error, to the total population
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24
Q

what are some of the disadvantages of probability sampling?

A

the most important one being
- they are usually more expensive to implement than a nonprobability sample of the same size

the rules for selection increase interviewing costs and professional time spent in designing and executing the sample design

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25
Q

define sample size

A

sample size: the identified and selected population subset for the survey, chosen because it represents the entire group

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26
Q

what is the acceptable error?

A

acceptable error: the acceptable difference between sample result and population value

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27
Q

define the levels of confidence

A

levels of confidence: the likelihood that the confidence interval–sample result plus or minus the acceptable error–will take in the true population value

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28
Q

define a population parameter

A

population parameter: a value that accurately portrays or typifies a factor of a complete population, such as average age or income

29
Q

the accuracy of sample results is affected by which 2 general types of error?

A

sampling error and nonsampling (measurement) error

30
Q

what is a sampling error?

A

sampling error: an error that occurs because the sample selected is not perfectly representative of the population

31
Q

what are the 2 types of sampling error?

A

2 types of sampling error: administrative and random

  • administrative error relates to the problems in the execution of the sample plan, that is, flaws in the design or execution of the sample that cause it to be unrepresentative of the population. these types of errors can be avoided or minimized by careful attention to the design and execution of the sample.
  • random sampling error is due to chance and cannot be avoided. this type of error can be reduced, but never totally eliminated, by increasing the sample size.
32
Q

what is a nonsampling error?

A

nonsampling error: all errors other than sampling error that may cause inaccuracy and bias in the survey results

also called ‘measurement error’

33
Q

how do you compute the known and equal probability for a simple random sample?

A

probability of selection = sample size / population size

eg. if the population size is 10,000 and the sample size is 400, the probability of selection is 4%:
0.04 = 400 / 10,000

34
Q

what are the 4 types of probability sampling methods?

A
  1. simple random sampling
  2. systematic sampling
  3. stratified sampling
  4. cluster sampling
35
Q

define a simple random sample

A

simple random sample: probability sample selected by assigning a number to every element of the population and then using a table of random numbers to select specific elements for inclusion in the sample

36
Q

define systematic sampling

A

systematic sampling: probability sampling in which the entire population is numbered and elements are selected using a skip interval

37
Q

how can a skip interval be computed?

A

skip interval = population size / sample size

38
Q

what is the main advantage of systematic sampling over simple random sampling?

A

systematic sampling is often simpler, less time-consuming, and less expensive to execute than simple random sampling

39
Q

define stratified sample

A

stratified sample: probability sample that is forced to be more representative through simple random sampling of mutually exclusive and exhaustive subsets

40
Q

if stratified samples are statistically more efficient, why are they not used all the time?

A
  1. the information necessary to properly stratify the sample frequently may not be available
  2. even if the necessary information is available, the potential value of the information may not warrant the time and costs associated with stratification
41
Q

what is cluster sampling?

A

cluster sampling: probability sample in which the sampling units are selected from a number of small geographic areas to reduce data-collection costs

42
Q

which 4 nonprobability samples are frequently used?

A
  1. convenience samples
  2. judgment samples
  3. quota samples
  4. snowball samples
43
Q

what is convenience sampling?

A

convenience sampling: nonprobability samples based on using people who are easily accessible

44
Q

what is judgment sampling?

A

judgment sampling: nonprobability samples in which the selection criteria are based on the researcher’s judgment about representativeness of the population under study

45
Q

what are quota samples?

A

quota samples: nonprobability samples in which quotas, based on demographic or classification factors selected by the researcher, are established for population subgroups

46
Q

what is snowball sampling?

A

snowball sampling: nonprobability samples in which additional respondents are selected based on referrals from initial respondents

47
Q

what is the main advantage of snowball sampling?

A

snowball sampling’s main advantage: a dramatic reduction in search costs

48
Q

list the advantages of internet sampling

A

advantages of internet sampling:
- target respondents can complete the survey when it is convenient for them
- data collection is relatively inexpensive
- the interview can be administered under software control
- the survey can be completed quickly

49
Q

what factors are involved in determining the sample size for a research study?

A

the sample size for a research studied is determining by considering financial, statistical, and managerial factors

it involves balancing the need for smaller sampling error with the available resources and budget constraints

50
Q

why is it important to have a random sample when calculating sample size and sampling error

A

calculations for sample size and sampling error assume that the sample is random. if the sample is not random, these calculations become invalid. It is essential to have a random sample to accurately estimate sampling error and determine the appropriate sample size

51
Q

how does the budget available impact the sample size determination?

A

the budget available for a research project often determines the sample size indirectly. after deducting other project costs, the remaining budget determines the size of the sample.

financial constraints may require exploring cost-effective data collection methods and considering the value of information relative to its cost

52
Q

is there a rule of thumb for determining the sample size?

A

some clients may specify a specific sample size based on past experience or desired sampling error. however, if the researcher determines that the requested sample size is inadequate, they have a professional responsibility to present arguments for a larger sample size. The final decision is made by the client

53
Q

what should be considered when analyzing subgroups within the sample?

A

the number and size of various subgroups within the total sample should be considered. if different subgroups need to be analyzed separately, the sample size for each subgroup must be sufficient for making meaningful statistical inferences.

generally, a sample should have at least 100 respondents in each major subgroup and 20-50 respondents in each less important subgroup

54
Q

what information is needed for traditional statistical methods to determine the sample size

A

traditional approaches for determining sample size require three pieces of information: an estimate of the population standard deviation, the acceptable level of sampling error, and the desired level of confidence in the sample result falling within a certain range of true population values. these factors are used to calculate the size of the required sample

55
Q

define the central limit theorem

A

central limit theorem: idea that a distribution of a large number of sample means or sample proportions will approximate a normal distribution, regardless of the distribution of the population from which they were drawn

56
Q

what is a normal distribution

A

normal distribution: continuous distribution that is bell-shaped and symmetric about the mean; the mean, median, and mode are equal

57
Q

list the general properties of a normal distribution

A
  1. normal distribution is bell-shaped and has only 1 mode
  2. the normal distribution is symmetric about its mean
  3. a particular normal distribution is uniquely defined by its mean and standard deviation
  4. the total area under a normal curve is equal to one, meaning that it takes in all observations
  5. the area under the normal distribution curve is translated into the empirical rule
  6. the area between the mean and a given number of SDs from the mean is the same for all normal distribution
58
Q

what is the proportional property of the normal distribution?

A

proportional property of the normal distribution: a feature that the number of observations falling between the mean and a given number of standard deviations from the mean is the same for all normal distribution

59
Q

what are the basic concepts of a normal distribution?

A
  • the distribution is a normal distribution
  • the distribution has a mean equal to the population mean
  • the distribution has a standard deviation, the standard error of the mean
60
Q

what is a point estimate?

A

point estimate: a particular estimate of a population value

61
Q

define interval estimate

A

interval estimate: interval or range of values within which the true population value is estimated to fall

62
Q

define confidence level

A

confidence level: the probability that a particular interval will include true population value

also called the ‘confidence coefficient’

63
Q

define confidence interval

A

confidence interval: interval that, at the specific confidence level, includes the true population value

64
Q

what is the sampling distribution of the proportion?

A

sampling distribution of the proportion: relative frequency distribution of the sample proportions of many random samples of a given size drawn from a particular population; it is normally distributed

65
Q

what is an allowable sampling error?

A

allowable sampling error: the amount of sampling error the researcher is willing to accept

66
Q

what is the population standard deviation?

A

population standard deviation: standard deviation of a variable for the entire population

67
Q

what methods can be used to deal with estimating the population’s standard deviatio/n

A
  1. use results from a prior survey
  2. conduct a pilot survey
  3. use secondary data
  4. use judgment
68
Q

what is an interdependence assumption?

A

interdependence assumption: assumption that sample elements are drawn independently

69
Q

what is a finite population correction factor (FPC)?

A

finite population correction factor (FPC): an adjustment to the required sample size that it made in cases where the sample is expected to be equal to 5% or more of the total population

MARK 302 (14 decks)

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