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Department
Psychology
Course
PSY201H1
Professor
Gillian Rowe
Semester
Fall

Description
Parameterpop statisticsampleDescriptive statssummarize organize simplify data graphs tables etcInferential statsuse sample data to make general conclusions about the pop generally not perfect reps of pop parametersSampling errorerror bw sample stat and pop parameter relationship between variablesno cause and effect Correlationalmeasures 2 variables ex sleep and academic performance no manipulation just observationExperimentalIV manipulated and DV observed tries controlling other variables that might influence causeeffectNonexperimentalquasiexperimentalcompares preexisting groups ex boysgirls no manipulationcontrol no c and eNominal scalenot quantitative categories with diff names cant determine directiondistance of differencemodeOrdinalranked by size shows direction but not distance cant tell how much bigger something isIntervalintervals of same size zero point is arbitrarylike temperatureshows distance and direction of differenceRatiointerval scale but zero point is an absolute ex heightshows distance and directionfreq dist shows how individuals are distributed on the scale number of indivs in each categoryProportionpfN relative frequency sum should1percentagep100fN100total frequencies equal NGrouped freq dist tables when scores cover wide range group into class intervals no gaps in histogram bars touchScores on xaxis vertical IV and frequencies on yaxis horizontal DV real limits for continuous variables no gapsTo find width for data intervals do highestlowest10 aiming for 10 intervals roughly we get is rangeRelative frequencyfor some populations where exact frequency is unknown use smooth curves to show its an estimateTailwhere scores get less at end skewedtail on rightskewedtail on leftPercentile rankpercent of indivs at or below that score rank refers to percent percentile refers to a scoreCumulative freq cfdetermine percentileconvert to cumulative percentage c ccfN100Stemfirst digit leafother digitsnot noisy datasame values noisy datarandom scoresCentral tendencyfind single score that best reps entire dist central point of distribution average scoreMean XN population and MXn samplebalance point for see sawIf a constant is addedetc to every score same is done to mean mean focuses on distances not scores so influenced greatly by extreme scoresskewed distsWeighted mean MXXnn combine two sets of data to find overall meanMedian divides distribution in half midpoint half of the scores on either side relatively unaffected by extreme scoresMode score with greatest frequency 2 modesbimodal unequal fmajor and minor mode 2 or more multimodalUse medianextreme scoreskewed undeterminedunknown values openended or
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