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Unformatted text preview: EEL 5322 W.R. Eisenstadt STAT, 1 Page 1 of 3 Statistical Analysis for ICs: Review (hopefully) Arithmetic Mean, μ (measure of tendency) & = = 1 ) ( 1 N n n x N m Where x (n) is a sampled data set n= 0, 1, 2, 3, & , N1 Standard Deviation, σ (measure of uncertainty) [ ] & = = 1 2 ) ( 1 N n n x N m s Variance, σ²  square of standard deviation For an IC process with many inputs with different standard deviations, total standard deviation, ﾃ Total becomes: Input 1 = ﾃ 1 Input 2 = ﾃ 2 Input n = ﾃ n Total variance, ﾃ ² Total = ﾃ ² 1 + ﾃ ² 2 + & + ﾃ ² n Total Standard Deviation, ﾃ Total 2 2 2 2 1 ... n Total s s s s + + + = For a signal with the DC component subtracted. [ ] & = = 1 2 ) ( 1 N n n x N RMS Signal EEL 5322 W.R. Eisenstadt STAT, 1 Page 2 of 3 Probabilities and Probability Density Functions Central Limit theorem: Distribution of a set of random variables; statistically independent, becomes large (N>30) tends toward a Gaussian distribution....
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This note was uploaded on 10/24/2011 for the course EEE 5322 taught by Professor W.r.eisenstadt during the Fall '10 term at University of Florida.
 Fall '10
 w.r.eisenstadt

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