Sampling Terminology and Concepts
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What is meant by 'Population' in sampling terminology?

  • A specific set of individuals undergoing treatment in a study.
  • Any group of entities sharing common characteristics. (correct)
  • A single individual within a group.
  • The results gathered from a survey of participants.

Which of the following statements about samples is true?

  • Sampling is suitable only for small populations.
  • Samples cannot provide accurate information.
  • A sample includes every element of a population.
  • Sampling can be more accurate than conducting a census. (correct)

What is a 'sampling frame'?

  • A database of all potential participants for a study.
  • A list of elements from which a sample may be drawn. (correct)
  • A conceptual model for understanding sampling techniques.
  • The complete list of a population that must be surveyed.

Why might researchers choose to use sampling instead of a full census?

<p>It is less costly and more time-efficient. (C)</p> Signup and view all the answers

What would constitute a 'census' in sampling terminology?

<p>An investigation of all individual elements of a population. (B)</p> Signup and view all the answers

What is a key benefit of sampling in research?

<p>It provides accurate data without involving the entire population. (C)</p> Signup and view all the answers

What type of sampling technique guarantees that every member of the population has a known, nonzero probability of selection?

<p>Probability Sampling (D)</p> Signup and view all the answers

Which of the following best explains the concept of 'population element'?

<p>An individual member of a population. (B)</p> Signup and view all the answers

Which sampling method involves selecting units based on convenience?

<p>Convenience Sampling (B)</p> Signup and view all the answers

What type of sampling ensures representation of various subgroups to the desired extent by the investigator?

<p>Quota Sampling (A)</p> Signup and view all the answers

What are 'strong similarities in population elements' important for in sampling?

<p>To facilitate more accurate sampling results. (B)</p> Signup and view all the answers

Systematic errors associated with the sampling process can lead to a sample that is:

<p>Less than perfectly representative (C)</p> Signup and view all the answers

In which type of sampling is the probability of selection for a member of the population unknown?

<p>Nonprobability Sampling (C)</p> Signup and view all the answers

Judgment sampling is also known as which type of sampling?

<p>Purposive Sampling (D)</p> Signup and view all the answers

Which sampling method limits selection based on an individual's convenience, potentially introducing bias?

<p>Nonprobability Sampling (D)</p> Signup and view all the answers

A sampling technique where an experienced individual selects sample members based on their judgment is called:

<p>Judgment Sampling (A)</p> Signup and view all the answers

What is a significant advantage of quota sampling over probability sampling?

<p>Speed of data collection (D)</p> Signup and view all the answers

Which type of sampling ensures each element in the population has an equal chance of being included in the sample?

<p>Simple Random Sampling (B)</p> Signup and view all the answers

What is the main disadvantage of nonprobability sampling methods like quota sampling?

<p>Higher bias potential (A)</p> Signup and view all the answers

What is the primary characteristic of snowball sampling?

<p>Initial respondents help identify further respondents (B)</p> Signup and view all the answers

What is the primary sampling unit in cluster sampling?

<p>A large cluster of elements (C)</p> Signup and view all the answers

In proportional stratified sampling, how are sampling units drawn from each stratum?

<p>In proportion to the population size of that stratum (D)</p> Signup and view all the answers

Which sampling technique combines two or more probability sampling methods?

<p>Multistage area sampling (D)</p> Signup and view all the answers

What is one potential source of bias in nonprobability sampling methods?

<p>Respondents are selected because they share similarities with the interviewer (A)</p> Signup and view all the answers

Disproportional stratified sampling allocates sample size based on what criteria?

<p>Analytical considerations (D)</p> Signup and view all the answers

What is typically the first step in multistage area sampling?

<p>Randomly selecting geographic areas (D)</p> Signup and view all the answers

What is a common characteristic of systematic sampling?

<p>The selection process involves a specific starting point and a fixed interval (D)</p> Signup and view all the answers

What characterizes internet sampling as described in the content?

<p>It employs unrestricted samples that may not be representative (D)</p> Signup and view all the answers

Which factor does NOT affect the choice of the appropriate sample design?

<p>Population size (D)</p> Signup and view all the answers

What is a characteristic of panel samples in internet sampling?

<p>They often result in biased outcomes (C)</p> Signup and view all the answers

What is one potential issue with using opt-in lists in internet sampling?

<p>They can limit the diversity of the sample (C)</p> Signup and view all the answers

In cluster sampling, how are clusters selected?

<p>Randomly (C)</p> Signup and view all the answers

What does sampling frame error refer to?

<p>Inaccurately represented sample elements in a sampling frame (A)</p> Signup and view all the answers

What is a Primary Sampling Unit (PSU)?

<p>A unit selected in the first stage of sampling (D)</p> Signup and view all the answers

Which of the following best describes random sampling error?

<p>Variations due to the chance selection of sample elements (A)</p> Signup and view all the answers

Which type of error results from nonsampling factors?

<p>Systematic Sampling Error (B)</p> Signup and view all the answers

What does a reverse directory contain?

<p>Listings by city, street address, or phone number (C)</p> Signup and view all the answers

What is the key purpose of sampling services or list brokers?

<p>To offer lists of names and contact information of specific populations (D)</p> Signup and view all the answers

Which selection stage follows the Primary Sampling Unit (PSU)?

<p>Secondary Sampling Unit (A)</p> Signup and view all the answers

What primarily causes random sampling error?

<p>Chance variations in selected sample elements (A)</p> Signup and view all the answers

Flashcards

Population (or Universe)

The entire group of individuals or objects that share common characteristics and are the focus of a research study.

Population Element

A single member of a population.

Census

A complete investigation of every single member of a population.

Sample

A subset or a smaller group taken from a population.

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Pragmatic Reasons for Sampling

The practical reasons for using a sample, mostly due to limitations of resources and time.

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Accurate & Reliable Results

Samples can provide accurate and reliable insights about a population even without studying everyone.

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Sampling Frame

The listing or framework of elements from which a sample can be drawn.

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Defining the Target Population

Clearly defining the specific characteristics that identify the population you intend to study.

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Probability Sampling

Sampling technique where every member of the population has a known, nonzero probability of being selected for the sample.

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Nonprobability Sampling

Sampling technique where the probability of selecting a specific member of the population is unknown.

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Convenience Sampling

A type of nonprobability sampling where the researcher selects the most conveniently available units for the sample. Think of the researcher standing outside a university and asking whoever passes by to participate in the study.

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Judgment Sampling

A type of nonprobability sampling where the researcher uses their experience and judgment to select the most representative units for the sample. Think of the researcher choosing only experts in the field for their study.

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Quota Sampling

A type of nonprobability sampling where the researcher ensures that subgroups in the population are represented in the sample proportionally to their actual size in the population. Think of dividing a sample based on age or gender.

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Random Sampling Errors

Errors associated with the sampling process resulting from the inherent randomness in selecting a sample, leading to differences between the sample data and the population.

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Systematic Errors

Errors associated with the sampling process resulting from systematic biases that affect the sample's representativeness of the population. Think of a survey that only asks people in urban areas, leading to a biased view.

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Sampling Frame Error

When certain sample elements are missing or misrepresented in the sampling frame, resulting in an inaccurate sample.

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Reverse Directory

A directory that lists people by their address or phone number, unlike a typical phone book that lists them alphabetically by name.

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Sampling Unit

A single element or group selected for inclusion in a sample.

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Primary Sampling Unit (PSU)

The first level of sampling units selected in a multi-stage sampling process.

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Secondary Sampling Unit

The second level of sampling units selected in a multi-stage sampling process.

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Tertiary Sampling Unit

The third level of sampling units selected in a multi-stage sampling process.

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Systematic Sampling Error

A mistake that occurs because of how you design or conduct your research, not random chance.

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Possible Sources of Bias in Nonprobability Sampling

A sampling method where participants are chosen based on their similarity to the interviewer, ease of accessibility, willingness to participate, or belonging to the middle class.

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Snowball Sampling

This sampling method selects initial participants using probability methods and then obtains additional participants from information provided by the initial group.

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Simple Random Sampling

A sampling method where each element in the population has an equal chance of being selected for the sample.

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Systematic Sampling

A method where a starting point is randomly selected and then every nth element on a list is chosen.

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Stratified Sampling

A method where simple random subsamples are drawn from within each stratum of the population, ensuring homogeneity within each group.

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Proportional Stratified Sample

A stratified sampling method where the number of units selected from each stratum is proportional to the population size of that stratum.

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Disproportional Stratified Sample

A stratified sampling method where the sample size for each stratum is allocated based on analytical need, not necessarily proportionate to the population size.

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Advantages of Quota Sampling over Probability Sampling

Ensures faster data collection, lower costs, and greater convenience compared to probability sampling.

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Cluster Sampling

A sampling technique where researchers randomly select groups of elements from the population, rather than individual elements. These groups are called clusters.

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Multistage Area Sampling

Combines multiple probability sampling techniques to get a more representative sample. Typically involves randomly selecting geographic areas in progressively smaller stages.

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Stratified Random Sampling

A type of sampling where the researchers divide the population into subgroups based on particular characteristics, and then randomly select samples from each subgroup. This ensures proportionate representation of each group.

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Purposive Sampling

A sampling technique where the researchers select individuals who are most likely to provide valuable information on the topic of interest. This is useful when a specific population segment is being studied.

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Disproportional Sampling

A sampling technique where the researchers select a smaller group from the population based on specific characteristics of interest. This can help researchers gain insights into a particular group within the population.

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Study Notes

Sampling Terminology

  • Population (universe): Any complete group of entities sharing common characteristics.
  • Population Element: An individual member of a population.
  • Census: An investigation of all population elements.
  • Sample: A subset of a larger population.

Why Sample?

  • Pragmatic Reasons: Budget and time constraints, limited population access.
  • Accurate and Reliable Results: Samples can provide reasonably accurate information. Strong similarities in population elements make sampling possible. It may be more accurate than a census.
  • Destruction of Test Units: Sampling reduces research costs in finite populations.

Stages in the Selection of a Sample

  • Define the target population.
  • Select a sampling frame.
  • Determine probability or nonprobability sampling method.
  • Plan procedure for selecting sampling units.
  • Determine sample size.
  • Select actual sampling units.
  • Conduct fieldwork.

Practical Sampling Concepts

  • Defining the Target Population: Identification of the relevant population and individuals to be studied, specifying and defining their characteristics precisely.
  • The Sampling Frame: A list of elements from which to draw a sample (also called the working population).
  • Sampling Frame Error: Occurs when sample elements are missing or inaccurately represented in the sampling frame.

Practical Sampling Concepts (continued)

  • Sampling Services (list brokers): Provide lists/databases of names, addresses, phone numbers, and email addresses.
  • Reverse Directory: A directory similar to a phone directory but organized by address or phone number instead of alphabetically by name.

Sampling Units

  • Sampling Unit: A single element or group of elements selected for the sample.
  • Primary Sampling Unit (PSU): The unit selected in the first stage of sampling.
  • Secondary Sampling Unit: The unit selected in the second stage of sampling.
  • Tertiary Sampling Unit: The unit selected in the third stage of sampling.

Random Sampling and Nonsampling Errors

  • Random Sampling Error: The difference between sample results and a census using identical procedures. A statistical fluctuation due to chance variations.
  • Systematic Sampling Error (nonsampling error): Error arising from factors other than simple sampling, focusing on study design and execution accuracy, not random chance fluctuation.

Random Sampling and Nonsampling Errors (continued)

  • Less than Perfectly Representative Samples: Random and systematic errors in a sampling process combine, yielding an imperfect sample representation of the population.

Errors Associated with Sampling

  • Visual representation of sampling frame error, random sampling error, and non-response error. The intended sample vs the actual sample.

Probability versus Nonprobability Sampling

  • Probability Sampling: Every member of the population has a known, non-zero probability of selection.
  • Nonprobability Sampling: Sample units are selected based on personal judgment or convenience; the probability of any one member being selected is unknown.

Nonprobability Sampling

  • Convenience Sampling: Choosing readily available subjects.
  • Judgment (Purposive) Sampling: An experienced individual handpicks the sample based on relevant characteristics.
  • Quota Sampling: Guaranteeing proportionality of subgroups within a population of interest.

Nonprobability Sampling (continued)

  • Possible Sources of Bias: Respondents selected due to similarities with the interviewer, ease of access, willingness to participate, or specific demographic characteristics (e.g., middle-class).
  • Advantages of Quota Sampling over Probability Sampling: Faster data collection, lower costs, and convenience.
  • Snowball Sampling: Initial respondents identify further participants based on provided information.

Probability Sampling

  • Simple Random Sampling: Every population member has an equal chance of inclusion.
  • Systematic Sampling: A random starting point on a list, and every nth member from that point is selected.
  • Stratified Sampling: Creating simple random subsamples with relatively equal characteristics within each stratum of the population.

Proportional versus Disproportional Sampling

  • Proportional Stratified Sample: The number of sampling units from each stratum is directly proportional to the population size within that stratum.
  • Disproportional Stratified Sample: Sampling sizes for strata are allocated according to analytical needs or considerations.

Cluster Sampling

  • Cluster Sampling: An effective sampling method where the primary sampling unit is a complete cluster of elements, not individual elements. Clusters are selected randomly.

Multistage Area Sampling

  • Multistage Area Sampling: Combining multiple probability sampling techniques, typically involving progressively smaller geographic areas until a housing unit is selected (e.g., from a city-to-block-to-household level).

What is the Appropriate Sample Design?

  • Degree of accuracy required, available resources, time constraints, advanced knowledge of the population, national versus local projects.

Internet Sampling is Unique

  • Website Visitors: Internet surveys utilize unrestricted sampling methods, often not representative of the actual population.
  • Panel Samples, Recruited Ad Hoc Samples, Opt-in Lists: These are specific internet-based sampling techniques.

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Sampling Designs and Sampling Procedures PDF

Description

This quiz explores the fundamental terminology and concepts of sampling in research. Learn about populations, samples, and the importance of sampling methods in obtaining accurate results. Test your understanding of the various stages involved in selecting a sample and practical sampling concepts.

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