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independent variable (IV)
manipulated by the researcher; assumed to cause a change in the response variable
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dependent variable (DV)
measured by the researcher; changes in response to the independent variable
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randomized
randomly divided
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experiment
a method of research used to asses causal relation between two or more variables
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level of independent variable
differing amounts/types of the independent variable
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control group
a group that does not receive treatment
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effect size
the difference in population parameters for two treatment variables; numerically describes the extent to which the IV effects the DV
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error variance
within-group variance; variance in DV that is not due to the IV
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Cohen's d
population standardized mean difference
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independent-samples t-test
- a test of the three hypotheses:
- H0: µ1 = µ2
- H1: µ1 > µ2
H2: µ1 < µ2 - in a two group design
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equivalence test
a form of hypothesis testing in which one of the following decisions is made: 1) H 0:  , 2) H 1:
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nonexperimental design
research design where participants are classified into two groups according to a preexisting characteristic rather than being randomly assigned to two different treatments
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predictor variable
the IV in a nonexperimental design
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homoscedasticity assumption
assumption of equal population variance under each treatment condition
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bar chart
a graphical representation of a set of sample parameters; a bar chart for the sample means in a two-group design has two bars whose heights represent the value of each sample mean
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internal validity
the extent to which an experiment accurately portrays the relation between two variables
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confounding variable
a variable other than the IV that could have produced the observed change in the DV
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differential attrition
when the IV causes participants in one treatment condition to withdraw from treatment with higher probability than participants in another treatment
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experimenter expectancy
when the participants' responses are influenced by what they believe the researcher wants
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double-blind design
an experimental design in which neither the participants nor the people administering treatment know which treatment the participants are getting
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demand characteristics
participants' expectancies
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placebo effect
psychological or physiological change that occurs in response to some treatment simply because the participant truly believes that the treatment will be effective
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placebo control group
a group of participants in an experiment who are given identical appearing treatments that contain inert substances
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external validity
the extent to which the results of a study can be generalized to different types of participants and different types of research settings
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nonrandom attrition
occurs when certain types of participants, regardless of treatment condition, drop out of the study with a higher probability than other participants
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IRB
Institutional Review Board; a group of people in charge of evaluating the costs and benefits of a proposed research project
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informed consent
requirement of the IRB that states participants must be informed of the nature of the study, must explicitly agree to participate, and must be allowed to freely decline to participate or leave any time during the study
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minimal risk
risk that is no greater in probability or severity than ordinarily encountered in daily life or during a routine physical or psychological exam
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debriefing
used to: 1) clarify the nature of the study to the participants, 2) reduce any stress or anxiety to the participants caused by the study, and 3) to obtain feedback from participants about the nature of the study
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scientific misconduct
- three types:
- scientific dishonesty: fabrication or falsicfication of data, plagiarism
- unethical behavior: sexual harrasment, abuse of authority, failure to follow university or government regulations, innappropriately including or excluding authors, providing biased review of manuscript or grant proposal
- questional research practices: failure to report results that are inconsistent with researcher's expectations, reporting significant results of exploratory analysis and excluding nonsignificant results, deleting legitimate data, reporting unexpected finding as if it were predicted, reporting significance results rather than CI results because they look better
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