oughly, speaking, we can use probability density functions to model the likelihood of an ent occurring. Formally, a probability density function on (-x, 0) is a function f such at f(x) >0 | f(2) = 1. ) Determine which of the following functions are probability density functions on the (-00, 00). x-1 0 0 ) 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. rf(x) d yields the expected value for a density f(x) with domain on the real numbers.) Find the expected value for one of the valid probability densities above.

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Roughly, speaking, we can use probability density functions to model the likelihood of an
event occurring. Formally, a probability density function on (-, 0) is a function f such
that
f(x) > 0
and
| f(x) = 1.
-0-
(a) Determine which of the following functions are probability density functions on the
(-00, 00).
0 < x < e
(i) f(x) =
otherwise
-2
0 < x < 2/2
(ii) f(x) = { (x – v2)3
otherwise
Sledz
0 < x < ∞
(ii) f(x) =
otherwise
where A> 0
(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. S xf (x) dx yields the
expected value for a density f (x) with domain on the real numbers.) Find the expected
value for one of the valid probability densities above.
Transcribed Image Text:Roughly, speaking, we can use probability density functions to model the likelihood of an event occurring. Formally, a probability density function on (-, 0) is a function f such that f(x) > 0 and | f(x) = 1. -0- (a) Determine which of the following functions are probability density functions on the (-00, 00). 0 < x < e (i) f(x) = otherwise -2 0 < x < 2/2 (ii) f(x) = { (x – v2)3 otherwise Sledz 0 < x < ∞ (ii) f(x) = otherwise where A> 0 (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. S xf (x) dx yields the expected value for a density f (x) with domain on the real numbers.) Find the expected value for one of the valid probability densities above.
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