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SOC202H1 (21)

CH 5 textbook notes

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University of Toronto St. George
Scott Schieman

CH5 – MEASURING DISPRESIONS OR SPREAD IN A DISTRIBUTION OF SCORES  DISPERSION – how the scores of an interval/ratio variable are spread out form the lowest to highest and the shape of the distribution inbtwn The Standard Deviation as an Integral Part of Inferential Statistics o Infinite possible distribution shapes for a variable w/ a given mean  Standard deviation & mean useful for getting sense of proportions of  Spread may vary btwn populations individual variables under study o DISPERSION STATISTICS – statistics that describe how the scores of an  Inferential statistics: interest w/ understanding why individual scores of a interval/ratio variable are spread across its distribution dependent variable deviate from its mean  Allows precise description of frequency of cases at any point in a o Entire sample level: interest w/ explain the variation distribution –ex. where cases are concentrated o Individual subject level: deviations scores, standard deviation measure of differences in scores for a variable among the subjects of a THE RANGE – An expression of how the scores of an interval/ratio variable are population distributed from lowest to highest  The distance btwn min. and max. scores found in a sample  Range = (max score – min score) + value of rounding unit  Weaknesses: o 1. Very susceptible to outliers, more so than mean o 2. Narrow informational scope: presents no info about shape of distribution btwn extremes THE STANDARD DEVIATION (S ) –xdescries how scores of an interval/ratio variable are spread across the distribution in relation to the mean score.  A summary measurement of all scores in distribution o Conveys how widely scores cluster around the mean  Focus: distance from the center (mean) towards both directions  Calculated w/ how far each score deviates form the mean ∑ ̅ √  Calculation steps: o 1. Identify givens: Why is it Called the “Standard Deviation”?  = standard deviation  Provides common unit of measure for comparing btwn different observed ̅ units of measure using z-score  = mean of all X  Raw score – subject’s score on an interval/ratio variable in its original,  = sample size o 2. Compute the mean observed units of measure o 3. Computer Deviation Scores ̅  DEVIATION SCORE – ho
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