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Midterm

Midterm Study Sheet

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Department
Psychology
Course
PSY201H1
Professor
Alison Luby
Semester
Fall

Description
Statisticsmathematical procedures organizsummarizinterpret infocommunicate resultsstandardized techs in scientific communityansw qs of studys hypothesisconclusions from resultsIf NoisyMany dif resultCorrelational methodsMeasuring 2 vars for each indiv no explanationdirectionality of causalityExperimentalnonexperimental methods Comparing 2 grps of scores determine ndcauseeffectuse1 var define grpmeasure2 var obtain scores for each grpexpt attempts control ALL other stvarsconfoundsShow changin value of 1manipulatedGrouped Distr Polygon dot ndvar cause change2measured var Iv Antecedent above midpt of Class Intervalconditns manip prior to observin change othr var Iv2 Nom or ord scales Score cats X values not values 1 is alwaysusually controlother exptal Dont continuousbelieve based on 1 study want differently Large pop relative freqs or smooth curves instead of operationalized studies to see if results replicatedabsoluteof indivs for each cat interval or ratio scale Random assignment All participants equal chance of so not exact freq for catsbeing assigned to either grpPercentile Rank for a particular X Nonexperimental or quasiexperimental valuePercentage of indiv w scores equal to or less than studiesexptscompare grps of that X value Ex IQ score of 100 pop mean has a scorespreexistingquasiindep vars not percentile rank of 50 symmetricalmanipulatedcontrolledto create grps of scoresshow Percentilescore identified by its percentile rankEx causeeffect relatnshipsprvde supportcorrelationthScore at the 50 percentile ile for IQ is 100 Xdemonstratedescribe rlnshps wcf column NtopcfCumulative Freqof indivs Constructs mor intangibleInternal scores equal or less ccfN x 100Cumulative attributescharscannot b directly observeduseful to describexplain bhvrmake operational defn identifies measurt proc for measurin external bhvr resultin measurts as defn of hypothetical construct resultin vars disccont Disc separate indivisible cats no Percentage pos skewintermediate values btwn adjacent catsContleast in Each X typically cont so each cPercentile Rank for t
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