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This deck focuses on Understanding Surveys Experiments And Observational Studies, giving you a quick way to review the definitions, rules, and examples that matter most for Statistics.
Study Understanding Surveys Experiments And Observational Studies in 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 the primary purpose of an observational study in statistics?
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Describe associations by observing without assigning treatments. Observational studies measure without intervention or manipulation.
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This deck focuses on Understanding Surveys Experiments And Observational Studies, giving you a quick way to review the definitions, rules, and examples that matter most for 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: Describe associations by observing without assigning treatments. Observational studies measure without intervention or manipulation.
Answer: Confounding by balancing lurking variables across groups. Random assignment distributes unknown factors equally between groups.
Answer: Sample survey. No treatments assigned; just collecting existing preferences.
Answer: Experiment. Only experiments control variables to establish cause-and-effect.
Answer: The researcher assigns treatments in an experiment. Experiments control treatments; observational studies don't.
Answer: Causation (if the experiment is well designed). Random assignment allows causal conclusions.
Answer: Sample survey. Surveys efficiently estimate population parameters from samples.
Answer: Sample survey (random sample). Random selection from voter list indicates a sample survey.
Answer: No random assignment; confounding is likely. Self-selection introduces bias and prevents causal conclusions.
Answer: Random assignment. Coin flip randomly allocates subjects to treatment groups.
Answer: Observational study. No treatment assignment means it's observational.
Answer: Selecting units from a population by chance. Random sampling chooses who participates from the population.
Answer: Test for cause-and-effect by imposing treatments. Experiments manipulate variables to establish causal relationships.
Answer: Data are collected by asking/recording responses, not assigning treatments. Surveys observe existing characteristics without manipulation.
Answer: No; it supports causation for subjects, not broad generalization. Without random sampling, results apply only to study participants.
Answer: Experiment. Researchers actively assign treatments to test effects.
Answer: A randomized experiment. Only experiments with random assignment can establish causation.
Answer: A variable related to both the explanatory and response variables. Confounders create false associations between variables.
Answer: Observational study. Variables observed naturally without researcher intervention.
Answer: Random selection (random sampling). Drawing names randomly creates a representative sample.
Answer: Voluntary response bias (not a random sample). Self-selected respondents don't represent the population.
Answer: An unmeasured variable that affects the response variable. Lurking variables are hidden factors that influence outcomes.
Answer: A sample survey with a random sample. Random sampling ensures the sample represents the population.
Answer: No; observational studies can show association but not causation. Correlation doesn't imply causation without controlled experiments.
Answer: Estimate population characteristics using data from a sample. Surveys use samples to make inferences about larger populations.
Answer: Confounding; it balances lurking variables across treatment groups. Randomization distributes unknown factors evenly between groups.
Answer: They are independent; one does not imply the other. Random sampling and random assignment serve different purposes.
Answer: Assigning subjects to treatment groups by chance. Random assignment determines which treatment each subject receives.
Answer: Random assignment. Randomization controls confounding variables in experiments.
Answer: No; it can generalize estimates but cannot establish causation. Surveys measure associations but can't prove one variable causes another.
Answer: The researcher assigns treatments to subjects. Active manipulation distinguishes experiments from observation.
Answer: Selection bias (unrepresentative samples). Random sampling ensures all population members have equal selection chance.
Answer: A variable related to both explanatory and response variables that distorts conclusions. Third variables can create spurious relationships between studied variables.
Answer: Association only (not causation). Without random assignment, causation cannot be established.
Answer: Random selection (random sampling). Representative samples allow inference to the larger population.
Answer: Randomized experiment. Random assignment to treatments defines an experiment.
Answer: Selection bias; it improves representativeness of the sample. Random sampling ensures all population members have equal selection chance.