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Lecture 3

Lecture 3 Jan 24th 2012 SOC202H1 Shirin Montazer

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Measures of VariabilityMeasures of central tendency are an incomplete measures aloneIndex of how scores are distributed around the center is also neededVariation in the distribution of scores important to understand The RangeRangedifference between the highest and lowest scores in a distributionIn equation form RHLRRangeHhighest scoer in a distributionLlowest score in a distributionRange provides a crude measure of variation often uselessOutliers affect interpretationRange11110 The Variance and the Standard DeviationDeviation distance of any given raw score from its mean Need a measure of variability that takes into account every scoreSquaring deviants results in positive calculationsAfterwards divide the squared deviation by the amount of scoresThe result is the measure known as varianceWith variance unit of measurement is alteredDifficult to interpret squared unitsTo return to the original unit of measurement remove squared units by taking the square root of both sides of the equationIn equation form ssqroot of Exx2N The RawScore Formula for Variance and Standard DeviationThere is an easier way using raw scoresIn equation formVariance o S2Ex2Nx2 The Meaning of the Standard DeviationStandard deviation converts the variance to units we can understandBut how do we interpret o Standard deviation represents the average variability in a distribution o It is the average of deviations from the mean o The greater the variabilitythe larger the standard deviation
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