Podcast
Questions and Answers
What is the primary difference between census and sampling?
What is the primary difference between census and sampling?
- Census is only conducted every ten years, while sampling can be done anytime.
- Census collects data from every member of the population, while sampling obtains data from a subset. (correct)
- Census samples a subset of the population, while sampling includes the entire population.
- Census is less expensive than sampling and requires fewer resources.
Which of the following scenarios would best illustrate sampling?
Which of the following scenarios would best illustrate sampling?
- Polling a random selection of 1,000 voters to predict election results. (correct)
- Conducting a survey to gather opinions from all citizens of a country.
- Interviewing every employee at a corporation about their job satisfaction.
- Recording the daily activities of every resident in a neighborhood.
During a census, what is the objective typically focused on?
During a census, what is the objective typically focused on?
- Analyzing trends within a specific demographic group.
- Estimating the margin of error in survey results.
- Obtaining data from every member of the population. (correct)
- Gathering data from a representative sample.
Which of the following correctly defines sampling?
Which of the following correctly defines sampling?
What aspect does a census usually check every decade in the United States?
What aspect does a census usually check every decade in the United States?
When is the census approach considered appropriate?
When is the census approach considered appropriate?
What is referred to as a statistic?
What is referred to as a statistic?
What is a parameter in the context of census and sampling?
What is a parameter in the context of census and sampling?
Why might researchers prefer the census method when sampling error is high?
Why might researchers prefer the census method when sampling error is high?
What is one limitation of the census approach?
What is one limitation of the census approach?
When is sampling appropriate to gather information?
When is sampling appropriate to gather information?
What type of error reflects a difference between a sample mean and the true population measure?
What type of error reflects a difference between a sample mean and the true population measure?
What is a consequence of sampling too few participants?
What is a consequence of sampling too few participants?
Which scenario would NOT be suitable for sampling?
Which scenario would NOT be suitable for sampling?
What should be considered when identifying the target population for sampling?
What should be considered when identifying the target population for sampling?
What is the primary function of selecting a sampling procedure?
What is the primary function of selecting a sampling procedure?
Which statement best describes 'non-sampling error'?
Which statement best describes 'non-sampling error'?
Why might it be unfeasible to survey everyone in a large population?
Why might it be unfeasible to survey everyone in a large population?
Why is it important to clearly define the target population in a study?
Why is it important to clearly define the target population in a study?
What is a sampling frame?
What is a sampling frame?
What is a potential consequence of selection bias in a study?
What is a potential consequence of selection bias in a study?
Which aspect is crucial when defining a video game target population?
Which aspect is crucial when defining a video game target population?
What issues can arise from a poorly defined sampling frame?
What issues can arise from a poorly defined sampling frame?
What is the ideal relationship between the sampling frame and the target population?
What is the ideal relationship between the sampling frame and the target population?
Which of the following is a factor that could affect the definition of the target population?
Which of the following is a factor that could affect the definition of the target population?
How can clarity in defining the term 'enjoy' impact research outcomes?
How can clarity in defining the term 'enjoy' impact research outcomes?
What is the primary concern with a sampling frame?
What is the primary concern with a sampling frame?
In probability sampling, which method ensures each member of the population has an equal chance of selection?
In probability sampling, which method ensures each member of the population has an equal chance of selection?
What differentiates cluster sampling from stratified sampling?
What differentiates cluster sampling from stratified sampling?
In stratified sampling, what is the primary requirement for the strata?
In stratified sampling, what is the primary requirement for the strata?
What is true about a disproportional stratified sample?
What is true about a disproportional stratified sample?
What is a systematic random sample?
What is a systematic random sample?
What is meant by 'sampling frame'?
What is meant by 'sampling frame'?
Which of the following statements is correct about strata in sampling?
Which of the following statements is correct about strata in sampling?
Flashcards
Sampling
Sampling
Collecting data from a smaller group within a larger group.
Census
Census
Collecting data from every member of a population.
Census vs. Sampling
Census vs. Sampling
Census gathers data from all, sampling from a portion.
Sampling Objective
Sampling Objective
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Example of Sampling Objective
Example of Sampling Objective
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Census Approach
Census Approach
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Parameter
Parameter
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Statistic
Statistic
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When is census best?
When is census best?
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Sampling Error
Sampling Error
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Non-Sampling Error
Non-Sampling Error
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Target Population
Target Population
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Appropriate Sampling
Appropriate Sampling
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Sampling Decision Criteria
Sampling Decision Criteria
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Sampling Process Steps
Sampling Process Steps
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Unit of Analysis
Unit of Analysis
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Sampling Frame
Sampling Frame
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Sampling Frame Issues
Sampling Frame Issues
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Simple Random Sample
Simple Random Sample
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Systematic Random Sample
Systematic Random Sample
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Cluster Sample
Cluster Sample
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Stratified Sample
Stratified Sample
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Proportionate Stratified Sample
Proportionate Stratified Sample
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Disproportional Stratified Sample
Disproportional Stratified Sample
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Selection Bias
Selection Bias
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Sampling Frame Match
Sampling Frame Match
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Defining Population
Defining Population
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Example of Defining Population
Example of Defining Population
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Ambiguous Definition Example
Ambiguous Definition Example
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Avoiding Selection Bias
Avoiding Selection Bias
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Study Notes
Sampling Fundamentals
- Obtaining data from a subset of a larger group (sample) is referred to as sampling.
- Only part of the population is surveyed.
- A census collects data from every member of a population.
- The U.S. Census occurs every 10 years.
Census vs. Sampling
- Census: Collecting data from every member of the population.
- Sampling: Collecting data from a subset of the population.
When is a Census Appropriate?
- When information is required from every individual in the population.
- When the population is small.
- When the consequences of wrong decisions are costly.
When is Sampling Appropriate?
- When the cost and time of collecting information from the entire population are high.
- When the population is large.
- When quick decisions are needed based on the new information.
Sampling Error
- Difference between a measurement from a sample and the actual population's measurement, which can be only obtained from the complete population.
Non-Sampling Error
- All errors associated with a research project, other than sampling error.
Sampling Process
- Identifying the target population: Defining the group to study.
- Determining the sampling frame: Creating a list of potential participants.
- Selecting a sampling procedure: Choosing how to select participants. (Probability methods like simple random sampling, stratified sampling, cluster sampling, and systematic sampling; Non-probability methods like convenience sampling, judgmental sampling, quota sampling, and snowball sampling).
- Determining the relevant sample size: Calculating the appropriate number of participants.
- Executing sampling: Selecting and collecting data from participants.
- Handling the non-response problem: Addressing missing data.
Step 1: Identifying Target Population
- Ensuring the target population is relevant to research objectives.
- Considering all possible units of analysis (e.g., individuals, households, etc.).
- Defining the population clearly to avoid ambiguity.
Step 2: Determining Sampling Frame
- Creating a list of population members from which to draw a sample.
- Ensuring the sample frame accurately reflects the target population. Considering potential omissions or inclusions that might not meet the criteria for the defined population.
Sampling Frame Issues
- Subset Issue: Sampling frame is smaller than target population.
- Superset Issue: Sampling frame is larger than target population.
- Intersection Issue: Some elements in the sampling frame appear in multiple groups or samples.
Step 3: Choosing a Sampling Procedure
- Selecting between probability sampling (simple random, stratified, cluster, systematic) and non-probability sampling (convenience, judgmental, quota, snowball).
Probability Sampling
- Each population member has a known equal chance of selection.
- Simple random sampling: Every member has an equal probability of being selected.
- Systematic sampling: Members are selected at regular intervals.
- Stratified sampling: Population is divided into subgroups (strata), and random samples are taken from each.
- Cluster sampling: The population is divided into groups (clusters), and a random selection of clusters are used.
Non-Probability Sampling
- No way to calculate the probability of selecting participants.
- Convenience sampling: Participants selected as easily accessible.
- Judgmental sampling: Participants selected based on an expert's judgment.
- Quota sampling: Sample reflects the proportion of characteristics in the population.
- Snowball sampling: Participants recruit other eligible participants.
Advantages & Disadvantages of Sampling Methods
- Probability: Advantages: representativeness, error quantification. Disadvantages: time consuming, expensive.
- Non-probability: Advantages: cost-effective, quicker. Disadvantages: no estimate of error, not generalizable.
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Description
Test your understanding of sampling concepts, including the differences between sampling and census, and when each method is appropriate. This quiz will cover various aspects of obtaining data from populations and the implications of sampling error.
