# Psychology 242 exam 2

 Describing Relationships Quantitative variable relationships linear: positive, negative, no correlation non-linear: curved Quantifying the relationship correlation coefficient: pearson's r represents the strengthinterval & ratio scalescorrelations are rarely bigge than .30measurement error tends to produce weaker correlations: one way to think about strength is the mean difference Describing relations involving one categorical variable groups differ in mean score?direction?size of the difference? Significance test If probability is low the relation is real Correlation & Causation One variable cause another making infeerences about causality: one variable causes another to occurdirectionality problem 3rd variable problem 3rd variable cause both variables to be correlatedvery commonthere can be more than oneindirect & directnegative & positive Controlled Experiments DV & IV IV has levelsthey both have operational definitions: not a causal statementrandom assignment: different types of people are equally distributed to each conditionmanipulation of the IV: eliminates the 3rd variable problem Confounds & more Internal & external validity internal: confirm in the experimentexternal: confirm outside the experiment Experimental control maximizes internal validitysometimes limits external validityexternal validity matters, but without internal validity we dont know what's causing what in either the lab or the real world Increasing external validity in experiment replicate with many sampleswhen studying abstract variables, ues many concrete instances as feasiblecreate a naturalistic atmosphere, both physically and/or psychologically with deceltion Interpreting "null" results was your manipulation of your IV powerful enough?was your DV sensitive enough to detect differences in the score?: Ceiling effect & floor effectdid you have enough people in your groups to detect a difference?was there a lot of random errorm in the measure of your DV? Units of observation smallest level of data on all variableseach unit if observation can be any defiable unit for which the variable differs from one unit to the next Within-subject manipulation Between subjects different people are assigned to different conditions (or levels) of the IV Within subjects (repeated measure) the same people are exposed to all levels or conditions of the IV Benefits of within-subjects design no random sampling error; only measurementmortality not a confoundrequires half as many subjectsgreater statistical power to eliminate chance as an explanation Weaknesses of within-subject designs order effectshistory effects: event ex. 9/11maturation effectscarryover effects: something about the first condition caries over into the second condition Carryover Effects fatigue effects: people get tired or bored during the study; performance effectspractice effects: more engaging; having praticetesting effects: familiarity; studycontamination effects: what happens in the 1st condition spills over and "contaminates" the 2nd Counterbalancing order effects becaome confounds, if one condition always comes firstconfound is eliminated if each condition comes in each orderlarge order effects can still weaken the observed effect of the IVcomplete: every subject gets every orderincomplete: different subjects get different orders Factorial Design more than one independent variableeach level of the first IV is paired with each level if the second IV ex. 2x2= 4 conditions2 experiments in 1matrix tableinteraction: the difference between the IV's Authormartyr01 ID44627 Card SetPsychology 242 exam 2 DescriptionPsychology and Research Methods Updated2010-10-24T23:15:27Z Show Answers