Independent and Identically Distributed (i.i.d./IID)  Python for Integrated Circuits   An Online Book  

Python for Integrated Circuits http://www.globalsino.com/ICs/  


Chapter/Index: Introduction  A  B  C  D  E  F  G  H  I  J  K  L  M  N  O  P  Q  R  S  T  U  V  W  X  Y  Z  Appendix  
================================================================================= Independent and Identically Distributed (i.i.d.) is a term commonly used in statistics and probability theory to describe a set of random variables or data points that share two important characteristics:
The formula for the variance of the sample mean ( ) of independent and identically distributed (i.i.d.) random variables with variance can be given by,  [3878b] where, δ^{2} is the variance of each individual random variable is the sample size. Figure 3878a shows the comparison between IID (Independent and Identically Distributed) and DID (Dependent Identically Distributed). The blue histograms represent the distributions of the variables when the variables are Independent and Identically Distributed. The orange histograms represent the distributions of the same variables, but now taking into account the correlation with other variables. The presence of the orange histograms indicate how the variable's distributions are influenced by the correlations with other variables. (a) (b)
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