Sampling Techniques in Research

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Questions and Answers

What is a key characteristic of a representative sample?

  • It must be the largest sample possible.
  • It accurately reflects the characteristics of the target population. (correct)
  • It should be randomly selected from a local community.
  • It should include all demographic groups equally.

Which of the following is a disadvantage of using sampling in research?

  • It may exclude a large proportion of the population. (correct)
  • It ensures that all participants are easy to find.
  • It guarantees accurate generalization to the entire population.
  • It always requires a large budget.

What is cluster sampling primarily used for?

  • To minimize costs by using volunteer participation.
  • To ensure every subset of the population is represented.
  • To gather data from naturally occurring groups within the population. (correct)
  • To analyze detailed responses from individual participants.

In what case is random stratified sampling most effectively used?

<p>When the researcher needs to ensure representation of various subgroups. (B)</p> Signup and view all the answers

Which sampling method is identified as advantageous for its cost-effectiveness?

<p>Random sampling. (C)</p> Signup and view all the answers

What is a major concern when using volunteer samples?

<p>They can introduce selection bias. (C)</p> Signup and view all the answers

What should be considered when defining a target population?

<p>The characteristics relevant to the study's goals. (C)</p> Signup and view all the answers

Which option is NOT a benefit of sampling?

<p>It eliminates the need for statistical analysis. (D)</p> Signup and view all the answers

What is a main advantage of random sampling?

<p>It avoids selection bias by giving equal chances to all. (A)</p> Signup and view all the answers

One disadvantage of random sampling is that:

<p>It can lead to biased results when participants decline. (B)</p> Signup and view all the answers

Which of the following best describes stratified sampling?

<p>A technique that ensures certain subgroups are proportionally represented. (D)</p> Signup and view all the answers

For stratified sampling to be effective, what is required?

<p>Identifying relevant strata to reflect in the sample. (B)</p> Signup and view all the answers

Which statement correctly identifies a disadvantage of using random sampling?

<p>Participants might not be willing to engage in sensitive topics. (D)</p> Signup and view all the answers

What is the primary purpose of using stratified sampling in research?

<p>To enhance accuracy by reflecting the diversity of the population. (C)</p> Signup and view all the answers

In which scenario would random sampling be least effective?

<p>When conducting research on a sensitive issue. (B)</p> Signup and view all the answers

What is an essential requirement for random sampling to be effectively executed?

<p>The availability of a complete list of the target population. (B)</p> Signup and view all the answers

What is the primary advantage of using random sampling in research?

<p>It ensures that every individual in the target population has the same chance of being selected. (A)</p> Signup and view all the answers

What is a potential disadvantage of convenience sampling?

<p>It can lead to a sample that is not representative of the target population. (D)</p> Signup and view all the answers

Which sampling technique involves dividing the population into distinct subgroups and then randomly selecting samples from each of those groups?

<p>Stratified sampling (A)</p> Signup and view all the answers

When identifying the target population for a study, what is the most critical step?

<p>Defining the specific demographic to be researched. (C)</p> Signup and view all the answers

Which sampling method is most likely to produce a biased sample?

<p>Snowball sampling (A)</p> Signup and view all the answers

What is the main purpose of using cluster sampling in research?

<p>To make data collection more cost-effective and efficient. (A)</p> Signup and view all the answers

Which scenario is an example of where stratified sampling is especially useful?

<p>Gathering opinions from a large population with various age groups. (D)</p> Signup and view all the answers

Which statement correctly describes the effectiveness of random and stratified samples?

<p>They provide the most valid results and can accurately reflect the characteristics of the population. (D)</p> Signup and view all the answers

Flashcards

Sample

A smaller group selected from a larger population to represent the characteristics of the whole population.

Representative Sample

A sample accurately reflects the characteristics of the target group, allowing researchers to generalize findings to the whole population.

Quick & Practical

Collecting data from a sample is faster and more practical than studying the entire population.

Economical

Studying a sample is financially more efficient than examining the entire population.

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Easy

Selecting a sample can be easier than collecting data from everyone in the population.

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Limited Representation

Sample results may not accurately represent the entire population due to the limited sample size.

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Potential Biases

Bias in selecting the sample can lead to inaccuracies in the results.

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Difficult to Generalize

Results obtained from a sample may not apply to the entire population due to the limited sample size.

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Target Population

Defining the specific group of people your research focuses on, ensuring a clear focus and avoiding generalizations.

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Random Sampling

A method of selecting participants where everyone in the target population has an equal chance of being chosen.

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Sampling Bias

A biased sample occurs when certain characteristics of the target population are over or under-represented, leading to inaccurate conclusions.

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Stratified Sampling

Dividing the target population into subgroups based on relevant characteristics, then randomly selecting participants from each group.

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Convenience Sampling

When the researcher selects participants based on their availability and ease of access, often leading to bias.

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Purposive Sampling

Selecting participants based on specific characteristics or knowledge relevant to the research question.

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Snowball Sampling

Starting with a few individuals and then expanding the sample by asking them to recommend others who fit the criteria.

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Sampling Frame

The list of all individuals or items in the target population used for random sampling.

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Non-response Bias

A type of bias that occurs when participants who agree to participate in a study differ significantly from those who decline, affecting the representativeness of the sample.

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Stratum (plural: strata)

A category or group within a population that is defined by a shared characteristic (e.g., age, gender, religion).

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Proportionate Stratified Sampling

The proportion of each stratum in the sample must reflect the proportion of that stratum in the target population.

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Disproportionate Stratified Sampling

A stratified sampling method that ensures that certain groups are represented in the sample, even if their proportion in the target population is small.

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Simple Random Sampling

A type of sampling that avoids bias by ensuring that every member of the target population has an equal chance of being selected for the sample. It's ideal for large populations.

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Study Notes

Sampling Techniques

  • Sampling is a method of selecting a portion of a population to study, representing the whole population.
  • A representative sample has similar characteristics to the broader population.

Identifying the Target Population

  • Researchers identify the specific group they're studying (e.g., 13-15-year-old Maltese teenagers).
  • Defining the target population precisely is crucial for valid results.

Random Sampling

  • Ideal for quantitative studies, ensuring every member has an equal chance of selection.
  • Prevents sampling bias, where certain characteristics are over or underrepresented.
  • Random selection methods, like random number generators, are employed.

Stratified Sampling

  • Ensures representation from all relevant subgroups within the population (e.g., age, gender).
  • Ensures proportionate representation from each stratum.

Cluster Sampling

  • Dividing the population into clusters (subgroups).
  • Randomly selecting clusters to study from.

Convenience Sampling

  • Selecting participants based on availability and accessibility.
  • Researcher uses readily available individuals.
  • Might not be representative of the entire population because of the lack of random selection.

Purposive Sampling

  • Selecting participants who could offer valuable insights.
  • Choosing participants with specific characteristics for a qualitative study.
  • Researchers are looking for particular characteristics rather than a large sample.

Snowball Sampling

  • Existing participants refer other suitable individuals for the study.
  • Useful when existing lists are unavailable or when participants are reluctant to be identified.
  • Often used when studying sensitive or stigmatized issues.

Volunteer Sampling

  • Participants volunteer to participate in the study.
  • Relies on self-selection.
  • Often used in research involving specific aspects or issues.
  • Volunteer bias is possible.

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