Questions and Answers
Which of the following are methods for collecting data?
What is affected by changing the amount of an explanatory variable?
Response variable
Give an example of an explanatory variable.
I punch you
What is a response variable example?
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Describe an observational study.
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What is a designed experiment?
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What is confounding?
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Define a lurking variable.
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Observational studies can claim causation.
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When are designed experiments used?
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What are the three categories of observational studies?
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What defines cross-sectional studies?
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Describe case-control studies.
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What are cohort studies?
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Cohort studies require few individuals and short time periods.
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What is a census?
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Study Notes
Data Collection Methods
- Two primary methods: Observational Studies and Designed Experiments.
Variables
- Explanatory Variable: Changing this variable influences the Response Variable.
- Example of Explanatory Variable: A punch.
- Example of Response Variable: Degree of pain felt.
Observational Studies
- Measure the response variable without influencing any variables.
- Researchers simply observe individuals’ behaviors.
- Cannot establish causation; only association can be claimed (e.g., cannot definitively say "smoking causes lung cancer").
Designed Experiments
- Involve assignment of individuals to groups with intentional changes to the explanatory variable.
- Response variables are measured after manipulation (e.g., drug testing with placebo vs. active drug).
- Useful when control over variables is needed and feasible.
Confounding Variables
- Arise when effects of multiple explanatory variables are mixed.
- May misrepresent relationships between variables (e.g., global warming linked with CO2 levels and other factors).
Lurking Variables
- Unconsidered explanatory variables that influence the response variable.
- Example: In influenza studies, age and health status serve as lurking variables.
Observational Studies Remarks
- Cannot make claims of causation.
- Only shows correlation or association among variables.
Designed Experiments Remarks
- Preferred when control over variables can be maintained.
- Less expensive and quicker to conduct than designed experiments in many cases.
Categories of Observational Studies
- Cross-Sectional Studies: Collect data at a specific point in time.
- Case-Control Studies: Retrospective studies matching individuals with certain characteristics to others without, relying on past information.
- Cohort (Prospective) Studies: Follow a group over time; may take years to see results (e.g., long-term studies on cell phone usage).
Cohort Studies Characteristics
- Require significant participant commitment over extended periods.
- High dropout rates may occur during lengthy studies.
- Considered powerful for establishing associations through long-term observation.
Census
- Comprehensive data collection from every member of a population.
- Example: U.S. decennial census serves as a standard national census.
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Description
This quiz explores the key concepts distinguishing observational studies from designed experiments, including definitions and examples. It covers explanatory and response variables, aiding in understanding their interplay in statistical analysis.
