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### 39 Cards in this Set

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 Actively imposing some treatment in order to observe response Experiment Part of the population that we examine in order to gather information Sample Entire group of individuals that we want info about Population Studying a part in order to get info about the entire group Sampling 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 Confounded 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 Biased 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 Undercoverage When someone refuses to cooperate in survey Nonresponse When interviewer can cause problems in gathering data (wording effects) Response Bias Recalling events from the past Telescoping 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 Subjects Specific experimental condition applied to units Treatment Explanatory (independent)variables in the experiment Factors Combining specific values of each factor when conducing experiments that study the joint effects of several factors Level Dummy treatment with no physical effect Placebo 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 Matching Using chance to divide units into groups Randomization 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 replication 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 double-blind 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 block design consisting of two units closely matched matched pairs design