2. Consider the function: ;0sxs1 c(2 - x) ; 1 < xs 2 ; otherwise. Find c to make this the PDF of a R.V. X, then plot/draw the resulting fx. Calculate and express X's CDF Fx(x), the same way fx(x) is expressed cx fx(x) = (a) (b) above, for four regions of x: ;x < 0 ;0sxs1 ;1 m) = ; In this problem X has one such m. Show that this median is the same as the mean of X. Does it always have to be (i.e., for other R.V.s)?

A First Course in Probability (10th Edition)
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Chapter1: Combinatorial Analysis
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2. Consider the function:
;0sxs1
fx(x) = { c(2 - x) ; 1 < xs 2
; otherwise.
Find c to make this the PDF of a R.V. X, then plot/draw the resulting fx.
Calculate and express X's CDF Fx(x), the same way fx(x) is expressed
сх
(a)
(b)
above, for four regions of x:
;x < 0
;0sxs1
;1< xs 2
;x > 2
...
...
Fx(x)
...
...
(c)
What is the mean (expected value) of Xx?
(d)
What is the variance of X?
A median of X is a value m that splits the probability in half:
1
P(X s m) = P (X > m) =
In this problem X has one such m. Show that this median is the same as the
mean of X. Does it always have to be (i.e., for other R.V.s)?
Transcribed Image Text:2. Consider the function: ;0sxs1 fx(x) = { c(2 - x) ; 1 < xs 2 ; otherwise. Find c to make this the PDF of a R.V. X, then plot/draw the resulting fx. Calculate and express X's CDF Fx(x), the same way fx(x) is expressed сх (a) (b) above, for four regions of x: ;x < 0 ;0sxs1 ;1< xs 2 ;x > 2 ... ... Fx(x) ... ... (c) What is the mean (expected value) of Xx? (d) What is the variance of X? A median of X is a value m that splits the probability in half: 1 P(X s m) = P (X > m) = In this problem X has one such m. Show that this median is the same as the mean of X. Does it always have to be (i.e., for other R.V.s)?
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