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CHAPTER 4 STOCHASTIC PROCESSES Fvw ( , W ) = Fw (W ) Fvw (V1 , W ) Fvw (V2 , W ) for V1 < V2 Fvw (V, W1 ) Fvw (V, W2 ) for W1 < W2

sort album sort artist sort album artist sort name sort composer sort show size start time track count track number unplayed video kind volume adjustment year

The last two properties state the the joint distribution is nondecreasing in both arguments The joint probability density is de ned as pvw (V, W ) = 2 Fvw (V, W ) V W (418)

The album name to use when sorting the track If present, this property overrides the album property The artist name to use when sorting the track If present, this property overrides the artist property The album artist name to use when sorting the track If present, this property overrides the album artist property The name to use when sorting the track If present, this property overrides the name property The composer name to use when sorting the track If present, this property overrides the composer property The show name to use when sorting the track If present, this property overrides the show property An integer giving the track s size on disk in bytes for example, 3408348 for a 33MB file A real number giving the start time of the track in seconds 00 until you change it The track s time in MM:SS format for example, 4:03 An integer giving the number of tracks on the album this track came from This track s number on the album it came from true if you ve never played this track at all, false if you ve played even part of it The kind of video track: none, movie, music video, or TV show An integer giving the volume adjustment you ve applied to the track You can use from 100 to 100 The year the track or its album was released

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The joint density has the following properties: pvw (V, W ) 0

The commercial success of any product often results in products claiming to mimic its bene t The neurotransmitter-blocking peptides currently incorporated into cosmeceutical products were developed as topical mimics of the

Table 12-1 Properties of the track Object (continued)

In the above, pv (V ) and pw (W ) are referred to as the marginal density of v and w, respectively When the meaning is clear from the context, the subscripts may be dropped on either the distribution or the density Example 46 Let u and v be random variables with the joint probability density 1 (U, V ) [0, T ] [0, T ] T2 puv (U, V ) = 0 otherwise Using the properties above, it is straightforward to show that pu (U ) pv (V ) puv (U, V ) Fuv (U, V ) = =

(U ) [0, T ] otherwise, (V ) [0, T ] otherwise,

Most of these properties are pretty straightforward, but these three things aren t immediately obvious:

= pu (U )pv (V ), = Fu (U )Fv (V )

Ratings In the user interface, you rate a track by assigning it a number of stars, from one star (irredeemably wretched) to five stars (the best thing since vacuum-packed coffee) Until you assign a rating, the track has no stars Internally, iTunes uses an integer from 0 to 100 to represent the stars: 0 is no stars, 20 is one star, 40 is two stars, 60 is three stars, 80 is four stars, and 100 is five stars

Two random vector variables v and w are independent if pvw (V, W) = pv (V)pw (W) (419)

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