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39 Cards in this Set
- Front
- Back
Actively imposing some treatment in order to observe response
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Experiment
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Part of the population that we examine in order to gather information
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Sample
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Entire group of individuals that we want info about
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Population
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Studying a part in order to get info about the entire group
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Sampling
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Applying the information gained from a sample to the entire population the sammple is supposed to rep
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Statistical Inference
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Method used to choose the sample from the population
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Sample Design
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Two variables' effects on a response variable cannot be distinguished from each other
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Confounded
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A sample created by those who volunteer themselves, responding to general appeal
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Voluntary Response Sample
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Choosing individuals that are easiest to reach
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Convenience Sampling
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A study that systematically favors certain outcomes
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Biased
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Set of individuals chose from the population where every set has an equal chance of being selected
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Simple Random Sample SRS
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Label/Assign values to each individual, then select random labels
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Choosing an SRS
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Gives each member of the population known chance to be selected (greater than zero)
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Probability sample
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Divides population into groups of familiar individuals (strata) then chooses SRS from the strata to do the test
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Stratified Random Sample
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Way of narrowing down a sample to the specific individual you want to study
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Multistage Sample
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When some groups are left out of the sampling choosing
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Undercoverage
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When someone refuses to cooperate in survey
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Nonresponse
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When interviewer can cause problems in gathering data (wording effects)
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Response Bias
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Recalling events from the past
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Telescoping
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List of individuals from which the sample is actually selected
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Sampling Frame
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observes individuals and measures variables of interest (no attempt to influence response)
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observational study
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units are human beings
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Subjects
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Specific experimental condition applied to units
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Treatment
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Explanatory (independent)variables in the experiment
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Factors
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Combining specific values of each factor when conducing experiments that study the joint effects of several factors
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Level
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Dummy treatment with no physical effect
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Placebo
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When patients respond to the dummy treatment
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Placebo effect
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Group of patients receiving sham treatment
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Control Group
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when the experimenter systematically creates similar treatment groups based on statuses
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Matching
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Using chance to divide units into groups
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Randomization
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When all experiemtnal units are allocated at random among all treatments
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Completely randomized
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Effect too large to be of chance
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statistically significant
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repetition of experiment to reduce liklihood of chance
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replication
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when experimenter does not treat all subjects the exact same way
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hidden bias
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where neither of teh subjects or people having contact with them know which treatment is which
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double-blind
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when an experiment does not duplicate the true conditions they study
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Lack of realism
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random assignment of units to treatments separately in each block
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block design
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group of units similar in ways affecting their response to treatment
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block
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block design consisting of two units closely matched
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matched pairs design
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