Transcription of Chapter 3 Continuous Random Variables
{{id}} {{{paragraph}}}
Example: dental hygienist
Chapter 3 Continuous Random Variables
Chapter 3 Continuous Random IntroductionRather thansummingprobabilities related to discrete Random Variables , here forcontinuous Random Variables , thedensitycurve isintegratedto determine (Introduction)Patient s number of visits,X, and duration of visit, =value of function,F(3) = P(Y < 3) = 5/12x , pmf f(x)probability ( distribution ): cdf F(x)probability less than = sum of probabilityat specific valuesP(X < ) = P(X = 0) + P(X = 1)= + = (X = 2) = , pdf f(y) = y/6, 2 < y < 4probability less than 3 = area under curve,P(Y < 3) = 5/12xprobability at 3,P(Y = 3) = 0probability less than = value of functionF( ) = P(X < ) = : Comparing discrete and Continuous distributions7374 Chapter 3.
(v) Poisson 3. Continuous (a) P(Y = 3) = (i) 0 (ii) 0:25 (iii) 0:50 (iv) 0:75 (b) P(Y 3) = F(3) = R 3 2 x 6 dx= x 2 12 i x=3 x=2 = 3 12 2 12 = 5 12 requires (i) summation (ii) integration and is a value of a (i) probability density function (ii) cumulative distribution func-tion which is a (i) stepwise (ii) smooth increasing function (c) E(Y ...
Tags:
Information
Domain:
Source:
Link to this page:
Please notify us if you found a problem with this document: