1 / 37

Continuous Random Variables

Continuous Random Variables. (most slides borrowed with permission from Andrew Moore of CMU and Google) http://www.cs.cmu.edu/~awm/tutorials. Announcements. CS Welcome event Thursday 3:30, ECCR 265 poster presentations Mozer lab research meeting Wednesdays 11:00-12:30, ECCS 127

yaakov
Télécharger la présentation

Continuous Random Variables

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript


  1. Continuous Random Variables (most slides borrowed with permission from Andrew Moore of CMU and Google) http://www.cs.cmu.edu/~awm/tutorials

  2. Announcements • CS Welcome event • Thursday 3:30, ECCR 265 • poster presentations • Mozer lab research meeting • Wednesdays 11:00-12:30, ECCS 127 • Email me if you’d like to be on our mailing list

  3. Real-Valued Random Variables • Previous lecture on probability focused on discrete random variables • true, false • male, female • freshman, sophomore, junior, senior • Can sometimes quantize real variables to make them discrete • E.g., age, height, distance • Today: how to handle variables that cannot be quantized

  4. Probability Mass Vs. Density • Discreet RVs have a probability mass associated with each value of the variable • P(male)=.7, P(female)=.3 • Imagine if the variablehad an infinitenumber of valuesinstead of a finitenumber…

  5. Probability Mass Vs. Density • Continuous RVs have a probability density associated with each value • Probability density function (PDF) • Density is derivative of mass • Notation: P(…) for mass,p(…) for density

  6. = E[X2] - E[X]2

  7. Density estimate of automobile weight and MPG Note change innotation: Previously used P(x^y) for joint

  8. Covariance Facts Consider 2D case with (X,Y) FALSE TRUE ? ?

  9. Mike’s Basic Advice on Continuous Random Variables • Ignore the fact that p(x) is a probability density function and treat it just as a mass function, and the algebra all works out. • Alternatively, turn densities to masses with dx terms, and they should always cancel out. • Don’t be freaked when you see a probability density >> 1. • Do be freaked if you see a probability mass or density < 0.

More Related