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Summary Intro to probability distributions and related concepts R100,00   Add to cart

Summary

Summary Intro to probability distributions and related concepts

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This material covers introductory statistical concepts, such as bivariate distributions and moment-generating functions.

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  • Chapters 4 to 6
  • June 18, 2023
  • 6
  • 2022/2023
  • Summary
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tanweerkola
Whatis a multivariate probability
distribution?

Probabilities involving multiple with
leach
events a distribution occurring together, i.e.


the probability ofthe intersection of events.


For example:P ( Y, y,) and P(Yc
=




yc)
=

and ... and PLYn yn)
=




P(X, y,,yz
=
= =



y2, ..., Yu yn)
=




or more compactly, P(y,y,,..., yn).
* joint probability
distribution.


It'slike calculating multiple individual probabilities simultaneously.


Where would multivariate distributions be used?

When we wantto investigate thatconsist
events ofmultiple individual events

occuring together.

the marginal distributions
given
How do we find the jointdistribution function?Does indepence ofthe random
1
variables
play a role?

In
general, you can't find the jointdistribution from the
marginal distributions,
unless thatthe variables independent, in which
you are
given are case



fxy(x,y) fx(x).fy(y).
=




For
jointdistributions of dependentvariables, see copulas and solar's theorem

, 40,
EX 5.14
by,"y,, 0
y,2y2,y, y22
f(y,,y2)
+




=




elsewhere.




joint density function, ssfleieldyet
(a)To be a valid




Ye 1




:"
Sy-sysyndy,dy, o.
giydyzdy, =




0
(yi (702)?") dy,

6(yp[z(z y,) - 1(3)"]dy,
=




-




6.y?(z(4
=
-


4y, y,)
+ -




typ]dy,


iyi (z
=
-




zy, +

typ -




zyp]dy,

=




6(2y, -
2ypdy,
12fyi y3dy,
=
-

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