Potential Problems with Sampling - AP Statistics
- What is cluster sampling?
- Dividing population into clusters and randomly selecting clusters. Groups population geographically, then randomly selects entire groups.
- Identify the issue: Sampling during only one time of day.
- Time bias. Excludes people with different daily schedules or availability.
- What is a sampling frame?
- A list of elements from which a sample is drawn. The complete listing of all potential sample units.
- Identify an issue with interviewer bias.
- Bias from influence of interviewer on respondent's answers. Interviewer's presence or characteristics affect participant responses.
- Identify a sampling method prone to bias.
- Convenience sampling. Uses easily accessible subjects rather than random selection.
- Find and correct the error: Sampling only high-income areas.
- Error: Income bias. Correction: Sample diverse income areas. Excludes lower-income perspectives and experiences.
- Identify a flaw in using only phone surveys.
- Excludes people without phones, leading to bias. Undercoverage of households without landline phones.
- What is response bias?
- Bias from inaccurate or misleading responses. Responses don't reflect true opinions due to question wording or social pressure.
- What is meant by the term 'sampling error'?
- The difference between sample statistic and population parameter. Natural variation between any sample and the true population value.
- What is the best way to ensure sample representativeness?
- Use random sampling methods. Randomization eliminates systematic bias in sample selection.
- What is the Hawthorne effect in sampling?
- Changes in behavior due to awareness of being observed. Subjects modify natural behavior when they know they're being studied.
- What is the impact of high variability in a sample?
- Leads to less precise estimates of population parameters. Wide spread in data reduces confidence in population estimates.
- What problem arises from using outdated sampling frames?
- Sampling frame does not accurately reflect current population. List doesn't match current population composition.
- What is the main issue with a small sample size?
- Increased variability and less reliable results. Large sampling error makes conclusions unreliable.
- Find and correct the error: Sampling only at one location.
- Error: Location bias. Correction: Use multiple locations. Single location excludes geographic diversity in population.
- What is sampling bias?
- Systematic error due to non-random sample selection. Occurs when sample selection method creates unrepresentative results.
- What is the solution to reduce nonresponse bias?
- Follow-up with nonrespondents to increase response rate. Multiple contact attempts and incentives improve participation.
- What can cause data to be skewed?
- Outliers or non-symmetric distribution. Extreme values or asymmetric distribution patterns.
- Define selection bias.
- Bias from non-random selection of individuals for a sample. Sample doesn't represent population due to flawed selection process.
- Identify a disadvantage of systematic sampling.
- May introduce bias if there is a pattern in the population. Regular patterns in population can create unrepresentative samples.
- What problem arises with non-random sampling?
- Leads to biased and unrepresentative samples. Selection process doesn't give all members equal probability.
- What is the main goal of stratified sampling?
- To ensure subgroups are represented proportionally. Maintains proper representation of population subgroups in sample.
- What is multistage sampling?
- Combines multiple sampling methods in stages. Uses different sampling methods at different stages of selection.
- What is the purpose of random sampling?
- To reduce bias and ensure a representative sample. Every population member has equal chance of selection.
- What is the main challenge in random digit dialing?
- May not reach unlisted or mobile-only households. Coverage gaps exclude segments without traditional phone service.
- Which bias results from survey participants lying?
- Response bias. Dishonest responses create gap between reported and actual behavior.
- Define undercoverage in sampling.
- Portion of population is less represented in the sample. Some groups are missed or inadequately included in the sample.
- What causes voluntary response bias?
- Bias from self-selected participants with strong opinions. Self-selection creates overrepresentation of extreme viewpoints.
- Which sampling method involves dividing population into strata?
- Stratified sampling. Divides population into homogeneous groups before sampling.
- What is the effect of using a biased sample?
- Leads to incorrect conclusions about the population. Biased samples produce inaccurate generalizations to population.
- Identify a problem with sampling during holidays.
- Bias due to atypical population behavior. Unusual circumstances create unrepresentative population behavior.
- Identify an issue with using volunteers in a sample.
- Voluntary response bias. Self-selection creates samples with extreme or strong opinions.
- Identify a problem with convenience sampling.
- Prone to bias as it does not represent the entire population. Easy-to-access samples often exclude important population segments.
- Identify a potential error in sampling process design.
- Failure to randomize selection. Non-random selection introduces systematic bias into results.
- What happens if the sample size is too large?
- Increased cost and complexity without proportional benefit. Diminishing returns make additional data collection inefficient.
- Identify the error in sampling only online users.
- Error: Digital divide bias. Excludes populations without internet access or digital literacy.