Exam 2 with Solution - Applied Probability and Statistics | STAT 400, Exams of Probability and Statistics

B. Kellogg Spring 89 Material Type: Exam; Class: APPLIED PROB & STAT I; Subject: Statistics and Probability; University: University of Maryland; Term: Unknown 1989;

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Pre 2010

Uploaded on 05/13/2008

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Sta(r400
Test
2
3-13-89
B.
Kellogg
Section
0401
1.
An
urn
contains
n
~
6
+
w
balls,
6
of
which
are
black
and
w
of
which are
white.
A
ball
is
removed.
Then
a
second
ball
is
removed.
Let
Xi
=
1
if the
»-th
ball
is
black,
0
if
the
t'-th
ball
is
white.
»
=
1,2.
Find
d],
Var(A',),
Cov(A'
1)
A
:!
).
2.
Let
AT
be
a
random
variable
with
density
function
z
<0.
Calculate
P(X
>
a).
Using
Markov's
inequality,
find
an
upper
bound
for
P(X
>
a).
Compare
these
two
quantities
for
large
a.
3.
Let
A"
be
a
random
variable
whose
density
function
is
given
by
0,
x<-a,
^(i-fy).
-a<x<a,
(0,
a<x.
Find
E[X}
and
Var(A').
Find
the
distribution
function
F(x).
Sketch
a
graph
of
f(x)
and
discuss
how
the
graph,
and the
variance,
depend
on
a.
4.
A
door
to
door
salesman
makes
on
the
average
1
sale
every
20
house
calls.
In
a
day
he
mak<:s
50
house
calls.
What
is
the
probability
of
his
making
at
least
2
sales
during
the
day?
5.
A
casino
offers
a
^Hue-game
consisting
of
throwing
a pair
of
dice.
It
costs
So.00
to
play
the
game,
and
if
the
pair
of
dice
show
z.
seven,
the
player
collects
$25.
Is
it
wise
for
the
casino
to
offer
this
payoff?
If
the
game
is
played
1000
times per
day,
what
is
the
expected
daily
profit
or
loss?
&
30
T

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Sta(r400 Test 2 3-13-89 B. Kellogg Section 0401

  1. An urn contains n ~ 6 + w balls, 6 of which are black and w of which are white. A ball is removed. Then a second ball is removed. Let Xi = 1 if the »-th ball is black, 0 if the t'-th ball is white. » = 1,2. Find d], Var(A',), Cov(A'1) A:! ).
  2. Let AT be a random variable with density function

z <0.

Calculate P(X > a). Using Markov's inequality, find an upper bound for P(X > a). Compare these two quantities for large a.

  1. Let A" be a random variable whose density function is given by 0, x<-a,

^(i-fy). -a<x<a,

(0, a<x.

Find E[X} and Var(A'). Find the distribution function F(x). Sketch a graph of f(x) and discuss how the graph, and the variance, depend on a.

  1. A door to door salesman makes on the average 1 sale every 20 house calls. In a day he mak<:s 50 house calls. What is the probability of his making at least 2 sales during the day?
  2. A casino offers a ^Hue-game consisting of throwing a pair of dice. It costs So.00 to play the game, and if the pair of dice show z. seven, the player collects $25. Is it wise for the casino to offer this payoff? If the game is played 1000 times per day, what is the expected daily profit or loss?

& 30 T