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Data Collection Via Experiments
Data Collection Via Experiments
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17 Terms
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Subject
Individual on which we are going to measure a variable
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Response variable (y)
Outcome of the experiment
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Explanatory variable (x)
Variable used to explain the response
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Factor
Explanatory variable with a fixed number of values
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Treatment
The condition or conditions applied to a subject or individual in an experiment
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Control
A “treatment” with supposedly zero effect
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Placebo
A fake treatment level to account of psychological effects
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Double-blind study
An experiment where the individual and researcher don’t know which treatment is applied
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Confounding
A situation where a lurking variable, in addition to the explanatory variable, is affecting the response
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Principles of valid experiments
1. Control/comparison
2. Randomization
3. Replication
4. Double blinding (if possible)
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Control/comparison
Control lurking variables by including comparison treatments, using homogeneous subjects; used to measure placebo effect
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Randomization
Neutralize effects of lurking variables by randomly assigning subjects to treatments (to limit bias)
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Replication
Assign more than one subject to each treatment group
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Randomized controlled experiments
Randomly split all subjects into treatment groups
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Randomized block experiment
Separate first, then randomize within each group/block
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Diagnostic Effect
Diagnosis of subjects biased by preconceived notions about the effectiveness of the treatment
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Solution: blind the dignoser
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Hawthorne Effect
People behave differently from how they would normally behave
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Solution: hidden observation (if ethical)