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SOC202H1 (21)

CH 6 textbook notes

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University of Toronto St. George
Scott Schieman

CH6 – PROBABILITY THEORY AND THE NORMAL PROBABILITY DISTRIBUTION  PROBABILITY THEORY – analysis & understanding of chance occurrences Using the Normal Curve as a Probability Distribution o Physical nature cyclical, follow strict scientific laws  predictable  Z-score – how many standard deviation away from the mean a raw (X- o Human behavior less predictable score) lies  Social/behavioral scientists req. incl. degrees of accuracy  Specific AUC of normal distribution = probability of occurrence of any o Many statistic predication based on normal curve single score falling in its domain  For normal distribution: the follow are equivalent What is a Probability? o 1. Proportion of cases between two scores  A PROBABILITY (p) – a specification of how frequently a particular event of o 2. The AUC between these two scores interest is likely to occur over a large number of trails o 3. Probability of randomly selecting a case between these scores o Probability of Success – probability of this interesting event occurring  WAYS TO INTERPRET P o 1. A distributional interpretation that describes the results in relations ( ) to the distribution of scores in a population or sample o Probability of Failure – probability of this interesting not event o 2. A graphical interpretation that describes the proportion of areas under a normal curve (assuming the distribution is normal shape) occurring o 3. A probabilistic interpretation that describes the probability of a o Observe “outcomes” of large # of trails, identify all possible outcomes single random drawing of a subject from this population  Probability can be considered as proportions  PARTITIONING AREAS UNDER THE NORMAL CURVE – to identify part of the curve and compute the proportion (p) of the total curve this part Basic Rules of Probability Theory represents  Rule 1: probability in range between 0 and 1 o Using statistical table & Z-score o 0 = event
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