Podcast
Questions and Answers
What is the main goal of using sampling techniques in research?
What is the main goal of using sampling techniques in research?
To make inferences about a larger population based on a smaller, representative sample.
In simple random sampling, every member of the population has:
In simple random sampling, every member of the population has:
Stratified sampling involves dividing the population into subgroups (strata) and then randomly selecting samples from each stratum.
Stratified sampling involves dividing the population into subgroups (strata) and then randomly selecting samples from each stratum.
True (A)
In systematic sampling, every ____ member of the population is selected, starting from a random point.
In systematic sampling, every ____ member of the population is selected, starting from a random point.
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Which sampling technique involves dividing the population into clusters and randomly selecting clusters to sample?
Which sampling technique involves dividing the population into clusters and randomly selecting clusters to sample?
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Match the following sampling techniques with their descriptions:
Match the following sampling techniques with their descriptions:
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How does convenience sampling differ from probability sampling techniques?
How does convenience sampling differ from probability sampling techniques?
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The company wanting to know if teenagers would buy a new snack product could use any sampling technique, as long as they get enough responses.
The company wanting to know if teenagers would buy a new snack product could use any sampling technique, as long as they get enough responses.
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Which sampling technique involves collecting data from participants over an extended period?
Which sampling technique involves collecting data from participants over an extended period?
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Convenience sampling guarantees a representative sample of the population.
Convenience sampling guarantees a representative sample of the population.
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What is the primary purpose of purposive sampling?
What is the primary purpose of purposive sampling?
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In ___ sampling, participants are recruited through referrals from an initial group.
In ___ sampling, participants are recruited through referrals from an initial group.
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Which of the following is NOT a non-probability sampling technique?
Which of the following is NOT a non-probability sampling technique?
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Match the sampling techniques with their descriptions.
Match the sampling techniques with their descriptions.
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Quota sampling requires the researcher to fill specific demographic quotas.
Quota sampling requires the researcher to fill specific demographic quotas.
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What is the main advantage of using snowball sampling?
What is the main advantage of using snowball sampling?
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Flashcards
Sampling Techniques
Sampling Techniques
Methods used to select a subset from a larger population.
Simple Random Sampling
Simple Random Sampling
Every member of the population has an equal chance of being selected.
Stratified Sampling
Stratified Sampling
Population divided into subgroups; samples are randomly selected from each subgroup.
Systematic Sampling
Systematic Sampling
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Cluster Sampling
Cluster Sampling
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Convenience Sampling
Convenience Sampling
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Role of Representative Sampling
Role of Representative Sampling
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Choosing Sampling Technique
Choosing Sampling Technique
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Purposive Sampling
Purposive Sampling
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Snowball Sampling
Snowball Sampling
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Quota Sampling
Quota Sampling
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Panel Sampling
Panel Sampling
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Defined Characteristics
Defined Characteristics
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High-Traffic Area
High-Traffic Area
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Longitudinal Sampling
Longitudinal Sampling
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Study Notes
Sampling Techniques
- Sampling techniques are methods for selecting a smaller group from a larger population to learn about the whole population.
- Different sampling methods provide varied approaches to accurately represent the population.
Learning Objectives
- Understand various sampling techniques used in research.
- Recognize the importance of representative sampling for accurate data collection.
- Select the best sampling method for a specific research scenario.
Scenario
- A company wants to determine teen interest in a new snack. They need to collect opinions appropriately.
What is Sampling
- Sampling involves selecting a subset (sample) of individuals or data points from a larger group (population). This allows researchers to make conclusions about the larger group.
- Sampling techniques help select a subset that accurately represents the larger population.
Probability Sampling Techniques
- Simple Random Sampling: Every member of the population has an equal chance of being selected.
- Example: A university surveys 100 students from 10,000 by creating a list, using a random number generator to pick IDs, and contacting those students.
- Stratified Sampling: Divide the population into meaningful subgroups (strata) and then randomly select samples from each stratum.
- Example: A company surveys 500 customers out of 50,000 by dividing by age groups (18-24, 25-34, etc.), calculating proportions, and selecting a random sample proportional to each group's size in the total population.
- Systematic Sampling: Select every 'nth' member of the population, starting from a random point.
- Example: A researcher surveys every 10th customer entering a store over a month, beginning with a randomly selected first customer.
- Cluster Sampling: Divide the population into clusters and randomly select clusters to sample.
- Example: A company surveys 100 households by dividing the city into neighborhoods, randomly selecting some neighborhoods, and surveying all households within those selected neighborhoods.
Non-Probability Sampling Techniques
- Convenience Sampling: Select samples based on ease of access.
- Example: A researcher surveys students by setting up a booth in a high-traffic area of a campus.
- Purposive Sampling: Select samples based on specific characteristics or expertise.
- Example: A researcher studies CEOs of Fortune 500 companies by identifying them and contacting them for interviews.
- Snowball Sampling: Start with a small group of individuals and ask them to refer others who meet the criteria.
- Example: A researcher studies people with a rare medical condition by identifying a few individuals and asking for referrals.
- Quota Sampling: Select samples to ensure the sample reflects the population's characteristics.
- Example: A researcher surveys 100 people, ensuring equal representation of different age, gender, and income groups.
Other Sampling Techniques
- Panel Sampling: Select a group of individuals to participate in a study over time.
- Example: A researcher studies consumer purchasing habits over time by recruiting consumers and gathering data at regular intervals (e.g., every 6 months).
- Longitudinal Sampling: Select a sample and study them over an extended period.
- Example: A researcher follows graduates' career development for 10 years by recruiting them, collecting data every 2 years, and analyzing for trends.
- Cross-Sectional Sampling: Select a sample at a single point in time.
- Example: A researcher studies voter attitudes toward a policy by recruiting voters and surveying them.
Factors to Consider When Choosing a Technique
- Population size and complexity
- Research objectives and questions
- Resource constraints (time, budget)
- Desired level of accuracy and precision
Day 1 Quiz Answers
- 1: b) Selecting a subset randomly
- 2: a) Selecting specific groups for targeted analysis
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Description
This quiz explores various sampling techniques used in research. Understand how different methods can provide accurate representations of a larger population and learn to choose the best sampling approach for specific research scenarios. Ideal for students and professionals in research methods.
