POLS 3650 Study Guide - Quiz Guide: Central Limit Theorem, Binomial Distribution, Chi-Squared Distribution

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Overview: definition and relevance, deviations from normality, normality in frequency distributions, normality in probability distributions, normality in sampling distributions, the central limit theorem. Definition and relevance: the normal distribution is a distribution with the shape of a bell or clock. It is symmetrical: mode = median = mean, the further we move from the mean, the lower the frequency. Middle is the mean: mean and standard deviation are needed to draw / know what the distribution looks like. Deviations from normality: three characters are crucial in describing the normality of a distribution. 95% falls within two standard deviations in both directions: leptokurtic larger number 68% falls within one standard deviation (distribution is much more clustered around the mean); Normality in frequency distributions: normal distributions are common in frequency distributions of variables that take on many different values. In particular characteristics of natural objects: of course, they need not be, not all variables are normally distributed.

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