- factor or characteristic set by the researcher that is being investigates as a possible cause of a change in behaviour - CAUSE Dependent Variables - factor or characteristic being measures that is thought to be affected by a change in the value of the IV - EFFECT Population - complete set of individuals/participants under consideration from which a sample may be drawn Sample - subset of the population under investigation Random Sample - everyone in population has equal chance of being selected - avoids bias Random Stratified Sample - used when researchers are interested in identifying characteristics that vary between groups of people in the population - divide population into strata and then sample randomly from each strata Opportunity Sample - Participants selected from groups and regions that are readily available - convenience sample - has bias Experimental Group - exposed to treatment (IV present) Control Group - exposed to control condition (IV absent) - provides a point of reference with which to compare experimental group Random Allocation - procedure for assigning participants to various groups in an experiment - all participants have an equal chance of being allocated to either control or experimental group - used to ensure participants in experimental group are similar to those in the control group Placebo and Experimenter Effects Placebo Effect - participant expectation - change in behaviour caused by the belief that one has taken a drug - single blind procedure ? participants do not know if they are in experimental or control group Experimenter Effect - changes in participants behaviour that are caused by the unintended influence of an experimenter - experiment finds what it expects to - Double blind procedure ? neither the participant or the experimenter know what group the person is Research Designs Experimental Design - process of organising and structuring an experiment Extraneous Variables - any potential IV that is of no direct interest to the researcher, but may have an effect on the DV Repeated Measures - participants take part in both experimental and control conditions - each participant is repeatedly tested - positive - no individual differences between participants in each condition, need less participants - negative ? may have order effects, effects of the first condition, may artificially affect the scores of the next condition Matched Participants - researcher attempts to mimic to repeated measures design but different participants are tested in each experimental condition - to minimise participant variables, participants are matched on these variables in an attempt to remove their influence - match participants on a variable and then randomly assign them to experimental or control group - positive ? person only receives on condition so nor order effect - controls for important extraneous variables - negative ? more participants needed may still be other variables that you have not thought of which effects results Independent Groups - researcher randomly allocates each participant to treatment condition - weakest of all reducing effect of individual (participants) differences between conditions - easy to do

However, I would treat all experimental groups the same because that will give more accurate results. If the participants were not treated the same I would not be able to accurately measure how much or how little the caffeine affected the students...

The subjects of the control group usually do not receive treatment or left unaware of some course of action and then at the end of the experiment compared with those who actually got the treatment in order to come to a conclusion...

The experimenters used students and their teachers as the subjects of their study. As part of their experiment, they even chose which grades the students would be in...