AP Stats Unit 4 Review 2024

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What is a Matched Pairs Design in experimental research?

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A Matched Pairs Design is an experimental design where participants are paired based on certain characteristics, and each member of the pair receives a different treatment. This design helps control for variability among participants.

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What is the key distinction between experiments and observational studies?

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An experiment can show a direct cause-and-effect relationship, whereas an observational study cannot.

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What is the purpose of random sampling in research?

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Random sampling ensures that every individual in the population has an equal chance of being selected, which helps to eliminate bias and allows for generalization of results.

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Define 'Cluster Sampling'.

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Cluster Sampling is a sampling method where the population is divided into clusters (groups), and entire clusters are randomly selected to be included in the sample.

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What is the significance of a control group in an experiment?

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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 independent variable.

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Explain the concept of 'confounding variables'.

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Confounding variables are external factors that may affect the outcome of an experiment, making it difficult to determine the true relationship between the independent and dependent 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.

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What is a hypothesis in the context of statistical research?

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A hypothesis is a testable statement or prediction about the relationship between two or more variables.

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What does 'statistical significance' mean?

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Statistical significance indicates that the results observed in a study are unlikely to have occurred by chance, suggesting a real effect or relationship exists.

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What is the purpose of blinding in experiments?

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Blinding reduces bias by preventing participants (single-blind) or both participants and researchers (double-blind) from knowing which treatment is being administered.