6. Roughly, speaking, we can use probability density functions to model the likelihood of an event occurring. Formally, a probability density function on (-o, 0) is a function f such that f(r) 20 and f(2) = = 1. (a) Determine which of the following functions are probability density functions on the (-00, 00). (1 00 (b) We can also use probability density functions to find the expected value of the outcomes of the event - if we repeated a probability experiment many times, the expected value will equal the average of the outcomes of the experiment. (e.g. af(x) dr yields the expected value for a density f(r) with domain on the real numbers.) Find the expected value for one of the valid probability densities above.

Advanced Engineering Mathematics
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Author:Erwin Kreyszig
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Chapter2: Second-order Linear Odes
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6. Roughly, speaking, we can use probability density functions to model the likelihood of an
event occurring. Formally, a probability density function on (-x, o0) is a function f such
that
f(r) 20
and
(2) =
= 1.
(a) Determine which of the following functions are probability density functions on the
(-x0, 00).
fr-1 0<r<e
(i) f(x) =
otherwise
-2
0 < r < 2/2
(ii) f(x) =
(r – V2)3
otherwise
Aedz 0<r<0
(iii) f(2) =
otherwise
where A>0
(b) We can also use probability density functions to find the erpected value of the outcomes
of the event - if we repeated a probability experiment many times, the expected value
will equal the average of the outcomes of the experiment. (e.g. rf(x) dr yields the
expected value for a density f(r) with domain on the real numbers.) Find the expected
value for one of the valid probability densities above.
Transcribed Image Text:6. Roughly, speaking, we can use probability density functions to model the likelihood of an event occurring. Formally, a probability density function on (-x, o0) is a function f such that f(r) 20 and (2) = = 1. (a) Determine which of the following functions are probability density functions on the (-x0, 00). fr-1 0<r<e (i) f(x) = otherwise -2 0 < r < 2/2 (ii) f(x) = (r – V2)3 otherwise Aedz 0<r<0 (iii) f(2) = otherwise where A>0 (b) We can also use probability density functions to find the erpected value of the outcomes of the event - if we repeated a probability experiment many times, the expected value will equal the average of the outcomes of the experiment. (e.g. rf(x) dr yields the expected value for a density f(r) with domain on the real numbers.) Find the expected value for one of the valid probability densities above.
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