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Lecture 3

Lecture 3 - Central Tendency Measures: Mean, Median, Mode

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Department
Psychology
Course
PSY201H1
Professor
Alison Luby
Semester
Fall

Description
PSY201 Lecture 3 Sept 29 2011Ex N4 2 2 6 10Two values below mean M5 2 is 3 units from meana total distance of 6 Purpose of descriptive stats is to organizefrom meansummarize a set of scoresTwo other values that above mean 6 is 1 Most common way to describe distr is find unit from mean 10 is 5 units from meanvalue that describes avgtypical scorea total distance of 6 from the meanEx 2 3 3 4 4 4 5 5 6 M4Central tendencyStatistical measure to identify single typicalrepresentative score that defines center of a distrPossible to compare sets of datacomparingby avg score central tendency for one set versus the avg score for another setCentral tendency should be determined by Ex 1 1 2 2 2 3 3 6 7 M3objectivewelldefined statistical procedure so others will understand exactly how avg value obtainedbe able to duplicate processNo single methodmeasure will produce best central representative value in every situationCommon measures of central tendency are mean medianmode3 measures of central tendency all reflect Correct for mean but NOT for median where distr is centered but differ in how much graph rmbr mean is based on distances make of datanot areaEach measure developed to best describe To combine two sets of scores from separatesingle most representative score in specificsamples need to calculate Weighted MeansituationNeedOverall sum of scores for The Arithmetic Meancombined groupArithmetic avg ocombined Total f scores in Sum of scores divided byof scoresgroup ntotMean for the population is XNLarger sample has larger weightMean for the sample is MXninfluence on the mean so weighted mean Computation requires scores that are will be closer to this meannumerical values measured on interval or ratio Add sum of scores for each samplescaledivide by sum of the two nsIntervalratio Distance btwn scores equalAmount of the total for each individual when we divide total equally btwn everyone in sampleConceptually can be defined as balance point of distrSo need to determine sum of X again MnOrWeighted meannnM1tot1nnM2tot2Similar to interpolationAltering the MeanScores on one side equal distance from Calculation of mean involves every score in mean as scores from other sidedistrchanging any score value will change Balanced on fulcrumpivotpoint be mean valuewary of when the mean actually doesnt Discarding scores or by adding new scores will appear as actual score in samplechange mean value unless this score is equal Works because distance from the mean is to Mequal on both sides
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