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39 Cards in this Set

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