Independent Variable - the experimental factor that is manipulated; the variable whose effect is being studied.
Dependent Variable - the experimental factor that is being measured; the variable that may change in response to manipulations of the independent variable.
Hypothesis - an idea that isn't yet verified but that if true would explain certain facts or phenomena.
Controls - constraints that the experimenter places on the experiment to ensure that each subject has the exact same control.
Demand Characteristics - refers to participants behaving in a way to meet the demands of the researcher when a cue may lead participants to guess what the experiment is about.
Participant Characteristics - individual differences in participants, in terms of intelligence, age, IQ, etc. that if not controlled, can influence the results of the experiment.
Order Effects - order effects occur with a repeated measure design. They include practice effects (improvement in performance due to repeated practice with a task) and fatigue effects (decline in performances as the research participant becomes tired or bored while performing a sequence of tasks).
Counterbalancing - in order to overcome order effects in a repeated measures design, you might get half the participants to do condition A first, followed by condition B and the other half of participants to do conditions B first, followed by condition A.
Extraneous Variables - any variable other than the independent variable that seem likely to influence the dependent variable in a specific study.
Situational Variables - aspects of the situation that interact with aspects of the person to produce behaviour.
Inferential Statistics - numerical method used to determine whether research data support a hypothesis or whether results were due to chance.
Confounding Variables - an extraneous variable whose presence affects the variable being studied so that the results you get don't reflect the actual relationship between the variables under investigation.
Experimenter Effects - the influence of the experimenter's behaviour, personality traits, or expectancies on the results of their own research. The experimenter's characteristics such as their age group or gender, might affect participants' responses.
Cause & Effect Relationship - you can establish a cause and effect relationship when you know that manipulation of an independent variable has directly led to the change in a dependent variable because extraneous variables have been controlled.
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