class03_11

class03_11 - 1.017/1.010 Class 11 Multivariate Probability...

Info iconThis preview shows pages 1–2. Sign up to view the full content.

View Full Document Right Arrow Icon

Info iconThis preview has intentionally blurred sections. Sign up to view the full version.

View Full DocumentRight Arrow Icon
This is the end of the preview. Sign up to access the rest of the document.

Unformatted text preview: 1.017/1.010 Class 11 Multivariate Probability Multiple Random Variables Recall the dart tossing experiment from Class 4. Treat the 2 dart coordinates as two different scalar random variables x and y . In this experiment the experimental outcome is the location where the dart lands. The random variables x and y both depend on this outcome (they are defined over the same sample space). In this case we can define the following events: AB B A y x C y B x A = = = = = I ] ) ( , ) ( [ ] ) ( [ ] ) ( [ y x y x x and y are independent if A and B are independent events for all x and y : P ( C ) = P ( AB ) = P ( A ) P ( B ) Another example Consider a time series constructing from a sequence of random variables defined at different times (a series of n seismic observations or stream flows x 1 , x 2 , x 3 , , x n .). Each possible time series can be viewed as an outcome of an underlying experiment. Events can be defined as above: j i j i j j i i ij i i i A A A A...
View Full Document

This note was uploaded on 11/29/2011 for the course CIVIL 1.00 taught by Professor Georgekocur during the Spring '05 term at MIT.

Page1 / 3

class03_11 - 1.017/1.010 Class 11 Multivariate Probability...

This preview shows document pages 1 - 2. Sign up to view the full document.

View Full Document Right Arrow Icon
Ask a homework question - tutors are online