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This deck focuses on Potential Problems With Sampling, giving you a quick way to review the definitions, rules, and examples that matter most for AP Statistics.
Study Potential Problems With Sampling in AP Statistics with focused flashcards that help you recognize the idea, recall the key rule, and apply it in practice-style prompts.
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What is cluster sampling?
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Dividing population into clusters and randomly selecting clusters. Groups population geographically, then randomly selects entire groups.
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This deck focuses on Potential Problems With Sampling, giving you a quick way to review the definitions, rules, and examples that matter most for AP Statistics.
Work through these flashcards in short sessions. Try to answer each prompt before flipping the card, then revisit any cards you miss until the explanation feels automatic.
Answer: Dividing population into clusters and randomly selecting clusters. Groups population geographically, then randomly selects entire groups.
Answer: Time bias. Excludes people with different daily schedules or availability.
Answer: A list of elements from which a sample is drawn. The complete listing of all potential sample units.
Answer: Bias from influence of interviewer on respondent's answers. Interviewer's presence or characteristics affect participant responses.
Answer: Convenience sampling. Uses easily accessible subjects rather than random selection.
Answer: Error: Income bias. Correction: Sample diverse income areas. Excludes lower-income perspectives and experiences.
Answer: Outliers or non-symmetric distribution. Extreme values or asymmetric distribution patterns.
Answer: Excludes people without phones, leading to bias. Undercoverage of households without landline phones.
Answer: Bias from inaccurate or misleading responses. Responses don't reflect true opinions due to question wording or social pressure.
Answer: The difference between sample statistic and population parameter. Natural variation between any sample and the true population value.
Answer: Use random sampling methods. Randomization eliminates systematic bias in sample selection.
Answer: Changes in behavior due to awareness of being observed. Subjects modify natural behavior when they know they're being studied.
Answer: To reduce bias and ensure a representative sample. Every population member has equal chance of selection.
Answer: Leads to less precise estimates of population parameters. Wide spread in data reduces confidence in population estimates.
Answer: Sampling frame does not accurately reflect current population. List doesn't match current population composition.
Answer: Increased variability and less reliable results. Large sampling error makes conclusions unreliable.
Answer: Error: Location bias. Correction: Use multiple locations. Single location excludes geographic diversity in population.
Answer: Systematic error due to non-random sample selection. Occurs when sample selection method creates unrepresentative results.
Answer: Follow-up with nonrespondents to increase response rate. Multiple contact attempts and incentives improve participation.
Answer: Outliers or non-symmetric distribution. Extreme values or asymmetric distribution patterns.
Answer: Bias from non-random selection of individuals for a sample. Sample doesn't represent population due to flawed selection process.
Answer: May introduce bias if there is a pattern in the population. Regular patterns in population can create unrepresentative samples.
Answer: Leads to biased and unrepresentative samples. Selection process doesn't give all members equal probability.
Answer: To ensure subgroups are represented proportionally. Maintains proper representation of population subgroups in sample.
Answer: Combines multiple sampling methods in stages. Uses different sampling methods at different stages of selection.
Answer: To reduce bias and ensure a representative sample. Every population member has equal chance of selection.
Answer: May not reach unlisted or mobile-only households. Coverage gaps exclude segments without traditional phone service.
Answer: Response bias. Dishonest responses create gap between reported and actual behavior.
Answer: Portion of population is less represented in the sample. Some groups are missed or inadequately included in the sample.
Answer: Bias from self-selected participants with strong opinions. Self-selection creates overrepresentation of extreme viewpoints.
Answer: Stratified sampling. Divides population into homogeneous groups before sampling.
Answer: Leads to incorrect conclusions about the population. Biased samples produce inaccurate generalizations to population.
Answer: Bias due to atypical population behavior. Unusual circumstances create unrepresentative population behavior.
Answer: Voluntary response bias. Self-selection creates samples with extreme or strong opinions.
Answer: Prone to bias as it does not represent the entire population. Easy-to-access samples often exclude important population segments.
Answer: Failure to randomize selection. Non-random selection introduces systematic bias into results.
Answer: Increased cost and complexity without proportional benefit. Diminishing returns make additional data collection inefficient.
Answer: Error: Digital divide bias. Excludes populations without internet access or digital literacy.