Sampling Fundamentals - Target Population
Sampling Fundamentals - Target Population
Sampling is intended to gain information about a population. Thus, it is critical at the outset to identify the population properly and accurately. If the population is defined in a fuzzy way, the results also will be fuzzy. If the
population is defined improperly, the research probably will answer the wrong question as a result. For example, if some research questions involve prospective car buyers and the population contains all adults with driver's licenses, the research output will be unlikely to provide the relevant information.
Although the definition of the target population is important, it often is neglected because it seems obvious and noncontroversial. But considerable effort in identifying the target population usually will pay off. The following guidelines should be considered.
Look to the Research Objectives
If the research objectives are well thought out, the target population definition will be clear as well. Recall from Chapter 2 that the research objectives include the research question, the research hypothesis, and a statement of the research boundaries. Each of these elements contribute to refining the definition of the target population. For example, the research question might involve how business firms in Chicago would react to a particular pricing method for advertising in the yellow pages of the telephone directory. The hypothesis might indicate that retailers of different types needed to be sampled. The consideration of the research boundary could restrict the population to metropolitan Chicago. Thus, the target population would be retail business firms in metropolitan Chicago.
Consider Alternatives
It is a rare study for which there are no alternative, reasonable, target population definitions. The task is really to identify and evaluate several of the alternatives instead of simply assuming that the first one mentioned is appropriate. For example, suppose the task was to determine the relative importance of such features as compactors, saunas, patios, and the like in medium-priced homes. The target population could be present owners of medium-priced homes, shoppers in middle-income shopping centers, those in a region that might upgrade their homes, or clients of real estate firms. The choice will depend on the research objectives. The key point is to recognize that alternative definitions exist.
Know Your Market^
If the research objective is to learn about the market response to some element of the marketing program, it is necessary to know something about the market. One may hope that some previous research will provide this type of information. Without it, the population definition will have to be unnecessarily broad and, therefore, unnecessarily expensive. For example, if a shopping center were considering whether restaurants should be added to the center, the opinions of customers and potential customers would be desired. A key question for the population definition, especially if potential customers were to be reached, would be how large an area the shopping center draws. If previous studies show, for instance, that the center draws from a three-mile radius, that information will help in defining the target population.
Consider the Appropriate Sampling Unit
The target population consists of sampling units. A sampling unit may
containjjeople, stores, households, organization transactions, products, or whatever. One task is to specify which sampling unit is appropriate. Is the iritere¥rin museums or in museum directors? Sometimes the choice is not clear. Should a study of banking activity or of leisure time activities use individuals or households? The choice will depend on the purpose of the study and perhaps on some judgments about consumer behavior. For example, if decisions about banking or leisure activities are thought to be family decisions, then the household might be the appropriate sampling unit. A respondent would report for the family. The assumption would be that family members are enough alike that responses within a family would tend to be similar. If, however, the decisions are assumed to be relatively independent among household members, then the sampling unit would be individuals instead of households.
Specify Clearly What Is Excluded
The specification of the target population should make clear what is excluded. A study of voting intentions on certain candidates and issues might restrict the sampling population to those of voting age and even to those who intend to vote or those who voted in the last election. If the election were in Cook County, for instance, it would be reasonable to restrict the population to those eligible to vote in Cook County.
Don't Overdefine
The population, of course, should be compatible with the study purpose and the research questions; however, the researcher should not arbitrarily overdefine the population. For example, a population of working wives between the ages of 25 and 30, earning more than $15,000 may be artificially restrictive. Such a restrictive population can generate a very costly design, because so many people need to be screened out to obtain the desired sample.
Consider Convenience
When there is a choice, preference should be given to populations that are convenient to sample. Suppose that the population was to include those who are bothered by airplane noise. One population compatible with the research purpose might be those who live within one mile of an airport. This population would be easy and convenient to sample. Of course, the population should not be distorted for the sake of creating a convenient sample. A population of subscribers to Sports Illustrated may be convenient to sample, but it may not be appropriate for the research purpose.
Sampling Frame
It is Important to distinguish between the pqrxilation and the_sampling , frame. The sampling frame is usually a list of population members used to" obtain a sampTejThere might be a list ofniagazine subscribers, retail hafd-ware~"sibrei. or college students. Actually, the description of a sampling frame does not have to enumerate all population members. It may be sufficient to specify the procedure by which each sampling unit can be located. For instance, a member of a probability sample of school children could be obtained by randomly selecting a school district, a school, a classroom, and, finally, a pupil. The probability of picking any given pupil could be determined, even if a physical list were not created that included all students in the population.
Sometimes it is possible to define the population to match exactly the sampling frame. Usually, however, an exact match is not possible and the task is to consider what portions of the population are excluded by the sampling frame and what biases are therefore created. For example, a list of residents of a city will exclude those in new housing developments. The question is: how many are in this category, and will their responses to the survey be different than the others? The existence of such biases usually will not affect the usefulness of the study, as long as they are identified and the interpretation of the results takes them into consideration.
Sampling is intended to gain information about a population. Thus, it is critical at the outset to identify the population properly and accurately. If the population is defined in a fuzzy way, the results also will be fuzzy. If the
population is defined improperly, the research probably will answer the wrong question as a result. For example, if some research questions involve prospective car buyers and the population contains all adults with driver's licenses, the research output will be unlikely to provide the relevant information.
Although the definition of the target population is important, it often is neglected because it seems obvious and noncontroversial. But considerable effort in identifying the target population usually will pay off. The following guidelines should be considered.
Look to the Research Objectives
If the research objectives are well thought out, the target population definition will be clear as well. Recall from Chapter 2 that the research objectives include the research question, the research hypothesis, and a statement of the research boundaries. Each of these elements contribute to refining the definition of the target population. For example, the research question might involve how business firms in Chicago would react to a particular pricing method for advertising in the yellow pages of the telephone directory. The hypothesis might indicate that retailers of different types needed to be sampled. The consideration of the research boundary could restrict the population to metropolitan Chicago. Thus, the target population would be retail business firms in metropolitan Chicago.
Consider Alternatives
It is a rare study for which there are no alternative, reasonable, target population definitions. The task is really to identify and evaluate several of the alternatives instead of simply assuming that the first one mentioned is appropriate. For example, suppose the task was to determine the relative importance of such features as compactors, saunas, patios, and the like in medium-priced homes. The target population could be present owners of medium-priced homes, shoppers in middle-income shopping centers, those in a region that might upgrade their homes, or clients of real estate firms. The choice will depend on the research objectives. The key point is to recognize that alternative definitions exist.
Know Your Market^
If the research objective is to learn about the market response to some element of the marketing program, it is necessary to know something about the market. One may hope that some previous research will provide this type of information. Without it, the population definition will have to be unnecessarily broad and, therefore, unnecessarily expensive. For example, if a shopping center were considering whether restaurants should be added to the center, the opinions of customers and potential customers would be desired. A key question for the population definition, especially if potential customers were to be reached, would be how large an area the shopping center draws. If previous studies show, for instance, that the center draws from a three-mile radius, that information will help in defining the target population.
Consider the Appropriate Sampling Unit
The target population consists of sampling units. A sampling unit may
containjjeople, stores, households, organization transactions, products, or whatever. One task is to specify which sampling unit is appropriate. Is the iritere¥rin museums or in museum directors? Sometimes the choice is not clear. Should a study of banking activity or of leisure time activities use individuals or households? The choice will depend on the purpose of the study and perhaps on some judgments about consumer behavior. For example, if decisions about banking or leisure activities are thought to be family decisions, then the household might be the appropriate sampling unit. A respondent would report for the family. The assumption would be that family members are enough alike that responses within a family would tend to be similar. If, however, the decisions are assumed to be relatively independent among household members, then the sampling unit would be individuals instead of households.
Specify Clearly What Is Excluded
The specification of the target population should make clear what is excluded. A study of voting intentions on certain candidates and issues might restrict the sampling population to those of voting age and even to those who intend to vote or those who voted in the last election. If the election were in Cook County, for instance, it would be reasonable to restrict the population to those eligible to vote in Cook County.
Don't Overdefine
The population, of course, should be compatible with the study purpose and the research questions; however, the researcher should not arbitrarily overdefine the population. For example, a population of working wives between the ages of 25 and 30, earning more than $15,000 may be artificially restrictive. Such a restrictive population can generate a very costly design, because so many people need to be screened out to obtain the desired sample.
Consider Convenience
When there is a choice, preference should be given to populations that are convenient to sample. Suppose that the population was to include those who are bothered by airplane noise. One population compatible with the research purpose might be those who live within one mile of an airport. This population would be easy and convenient to sample. Of course, the population should not be distorted for the sake of creating a convenient sample. A population of subscribers to Sports Illustrated may be convenient to sample, but it may not be appropriate for the research purpose.
Sampling Frame
It is Important to distinguish between the pqrxilation and the_sampling , frame. The sampling frame is usually a list of population members used to" obtain a sampTejThere might be a list ofniagazine subscribers, retail hafd-ware~"sibrei. or college students. Actually, the description of a sampling frame does not have to enumerate all population members. It may be sufficient to specify the procedure by which each sampling unit can be located. For instance, a member of a probability sample of school children could be obtained by randomly selecting a school district, a school, a classroom, and, finally, a pupil. The probability of picking any given pupil could be determined, even if a physical list were not created that included all students in the population.
Sometimes it is possible to define the population to match exactly the sampling frame. Usually, however, an exact match is not possible and the task is to consider what portions of the population are excluded by the sampling frame and what biases are therefore created. For example, a list of residents of a city will exclude those in new housing developments. The question is: how many are in this category, and will their responses to the survey be different than the others? The existence of such biases usually will not affect the usefulness of the study, as long as they are identified and the interpretation of the results takes them into consideration.
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