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Questions and Answers
What is the difference between a parameter and a statistic?
What is the difference between a parameter and a statistic?
A parameter is a numerical summary of the entire population, while a statistic is a numerical summary based on a sample of that population.
How does a prospective study differ from a retrospective study?
How does a prospective study differ from a retrospective study?
A prospective study follows subjects into the future, while a retrospective study looks backward at past events.
What is sampling bias and how can it affect a study?
What is sampling bias and how can it affect a study?
Sampling bias occurs when certain individuals are systematically excluded from a sample, potentially leading to unrepresentative results.
Define a confounding variable and its significance in a study.
Define a confounding variable and its significance in a study.
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What distinguishes a stratified random sample from a simple random sample?
What distinguishes a stratified random sample from a simple random sample?
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What is the role of the response variable in a study?
What is the role of the response variable in a study?
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Explain the concept of nonresponse bias.
Explain the concept of nonresponse bias.
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What is an observational study, and when is it typically used?
What is an observational study, and when is it typically used?
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Study Notes
Study Notes: Experimental Design
- Individual: A single unit evaluated in a study.
- Population: All individuals of interest in a study.
- Sample: Subset of the population.
- Variable: Characteristic of an individual.
- Statistic: Numerical summary of a sample (e.g., mean, median).
- Parameter: Numerical summary of a population (usually unknown).
- Experiment: Assigns subjects to conditions (treatments) to find causal relationships.
- Observational Study: Observes variables without intervention. Used when experimenting is unethical.
- Prospective Study: Follows subjects into the future.
- Retrospective Study: Examines past events.
- Response Variable: Measures study outcome.
- Explanatory Variable: Influences the response variable.
- Comparative Study: Compares variables and treatments.
- Sampling Procedure: Method for selecting a sample.
- Sampling Bias: Systematic exclusion of certain individuals.
- Nonresponse Bias: Participants not responding.
- Response Bias: Participants giving inaccurate responses.
- Probability Sample: Randomly selected individuals.
- Convenience Sample: Easily accessible sample.
- Simple Random Sample: Every sample has the same chance of selection.
- Stratified Random Sample: Divides the population into groups (strata) and samples from each.
- Cluster Random Sample: Divides the population into groups (clusters) and samples from selected clusters.
- Lurking Variable: Influences other variables but is not included in the study.
- Confounding Variable: Effects of variables cannot be distinguished.
- Randomized Comparative Experiment: Experiment comparing treatments by randomized assignment.
Randomized Comparative Experiments
- Control: Controls lurking variables through comparison.
- Reduced Bias: Random assignment minimizes bias in treatment assignment.
- Treatment Group: Receives the proposed treatment.
- Control Group: Receives a standard treatment or no treatment.
- Blinding: Prevents subject bias (subject doesn't know their group).
- Double-Blind: Neither subject nor researcher knows the group assignment (reduces bias further).
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Description
Dive into the essential concepts of experimental design with this quiz. Explore important terms like individual, population, sample, and types of studies, including observational and comparative methods. Test your knowledge on key definitions and understanding of research methodology.
