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Stats Symbols & Concepts: Pop. vs Sample, Mean, Variance, Proportion, CLT, & Normal Approx, Study notes of Data Analysis & Statistical Methods

Definitions and explanations of various statistical symbols and concepts, including population vs sample, mean, variance, proportion, central limit theorem, and normal approximation to binomial. It covers the meanings and formulas for population and sample means, population and sample variances, population proportion, and the central limit theorem and its conditions. Additionally, it explains the normal approximation to the binomial distribution.

Typology: Study notes

Pre 2010

Uploaded on 09/17/2009

koofers-user-986
koofers-user-986 🇺🇸

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Download Stats Symbols & Concepts: Pop. vs Sample, Mean, Variance, Proportion, CLT, & Normal Approx and more Study notes Data Analysis & Statistical Methods in PDF only on Docsity! Definition of some symbols Please note the similarities and differences N = Population size = Number of elements in the population1 N = Sample size = Number of units in the sample  = Mean of the population (of X’s = X ) 2 = E(X) ( ) ( ) all x X X xP X x if X is a discrete rv xf x dx if X is a continuous rv              X = Mean of the sample from the population of X’s = 1 1 n i i X n   X = Mean of the population of sample means = E( X ) [ =  by rule 1] ( ) ( ) all x X X xP X x if X is a discrete rv xf x dx if X is a continuous rv            2 X =Variance of the population of X’s = 2 X 2 2 2 _ ( ) ( ) if X is a discrete rv ( ) ( ) if X is a continuous rv X all x X X X x P X x x f x dx                2 X = Variance of the population of sample means [ = 2 X n  by Rule 2]. 2 2 2 _ ( ) ( ) if X is a discrete rv ( ) ( ) if X is a continuous rv X all x X X X x P X x x f x dx                 = Proportion of “Success”s in the population. = (Number of “Success”s in the population) / N p = Proportion of “Success”s in the sample = (Number of “Success”s in the sample) / n p = Mean of the population of sample proportions = E(p) =  by rule 6 2 p = Variance of the population of sample proportions = (1 ) / n  by rule 9. 1 Assumed to be infinity in many theoretical studies, but finite in almost all real life problems. 2 The subscript indicating the population (X, Y, etc.) will be dropped when there is no possible confusion.
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