Chapter 4 AP Practice Test

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What is a stratified sample?

Back

A stratified sample is a sampling method that involves dividing a population into subgroups (strata) that share similar characteristics and then taking a sample from each stratum to ensure representation of all groups.

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Why is a simple random sample important?

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A simple random sample ensures that every possible sample of the same size has an equal chance of being selected, which helps to eliminate bias and allows for generalization of results to the larger population.

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What is the purpose of random assignment in experiments?

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Random assignment is used to ensure that each experimental unit has an equal chance of receiving any treatment, which helps to control for confounding variables and allows for causal inferences.

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What is the main advantage of experiments over observational studies?

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The main advantage of experiments is that they can provide stronger evidence of causation, as researchers can manipulate variables and control for other factors.

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What is a matched pairs design in experiments?

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A matched pairs design is an experimental design where pairs of experimental units are matched based on similar characteristics, and each unit in the pair receives a different treatment.

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What is the role of random sampling in research?

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Random sampling is used to select a representative sample from a population, which helps to ensure that the results can be generalized to the larger population.

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How does stratified sampling differ from simple random sampling?

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Stratified sampling involves dividing the population into strata and sampling from each stratum, while simple random sampling involves selecting individuals randomly from the entire population without regard to subgroups.

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What is confounding in the context of experiments?

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Confounding occurs when an outside variable influences both the dependent and independent variables, making it difficult to determine the true effect of the treatment.

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What is the significance of using a control group in experiments?

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A control group serves as a baseline to compare the effects of the treatment, helping to isolate the impact of the treatment from other variables.

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What is the difference between qualitative and quantitative data?

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Qualitative data describes characteristics or qualities and is often non-numerical, while quantitative data consists of numerical values that can be measured and analyzed statistically.