MDM4U
–
Module
2:
Probability
–
Unit
4:
Probability
Distributions
–
Lesson
4
Date:___________
Hypergeometric
Distributions
A.
What
is
a
Hypergeometric
Distribution?!
Unlike
the
other
distributions
we
have
encountered,
hypergeometric
distributions
have
trials
whose
probabilities
do
change
from
one
trial
to
the
next
–
making
them
dependent
on
one
another!!
Each
dependent
trial
continues
to
have
success
or
failure
as
the
only
options,
but
the
probability
of
success
changes
as
each
trial
is
made.
In
a
hypergeometric
distribution,each
trial
reduces
the
number
of
items
available
for
the
next
selection
(i.e.
items
are
not
replaced/repeated).
The
random
variable
for
a
hypergeometric
distribution
is
number
of
successful
trials
in
an
experiment.
Examples:
a)
When
choosing
a
starting
lineup
for
a
game,the
coach
must
obviously
choose
a
different
player
for
each
position.
b)
When
you
deal
cards
from
a
standard
deck,
there
can
be
no
repetitions.
c)
When
choosing
members
to
form
a
committee,
there
can
also
be
no
repetition.
Probability
in
a
Hypergeometric
D𝒏(𝑬) istribution
The
theoretical
p robability
o f
a n
e vent,
E ,
i s
g iven
b y:
P (E)
=
𝒏(𝑺)
The
probability
of
x
successes
in
r
dependent
trials
is
given
by
the
formula:
where
0
≤
P(E)
≤
1
C × C
P(x)
=
a x n −a r −x
C
n r
Where
a
is
the
number
of
successful
outcomes
among
a
total
of
n
possible
outcomes
The
hypergeometric
probability
distribution
can
be
created
by
finding
the
probabilities
for
all
possible
values
of
x
.
Ex.
1:
A
committee
of
5
is
to
be
chosen
from
6
men
and
8
women.
(a)
Determine
the
probability
distribution
for
the
number
of
women
on
this
committee.
(b)
What
is
the
expected
number
of
women
on
the
committee?
Number
of
Probability,
P(x)
Product
of
Women,
x
xi
*
P(xi)
E(X):
B.
Expected
Values
The
expected
value,
E(X),
for
a
hypergeometric
distribution
can
be
calculated
“traditionally”
by
taking
the
sum
of
all
xi*P(xi),
but
it
can
also
be
simplified
as
a
ratio
of
successes
in
the
overall
population
as
follows:
The
expected
value
for
a
hypergeometric
distribution
for
r
dependent
𝒏(𝑬) trials
is
given
by
the
formula:
The
theoretical
probability
of
an
event,
E,
is
given
by:
P(E)
=
𝒏(𝑺)
=
r a
where
0
≤
P(E)
≤
1E(x)
n
Where
a
is
the
number
of
successful
outcomes
among
a
total
of
n
possible
outcomes
Ex.
2:
A
box
contains
seven
yellow,
three
green,
five
purple,
and
six
red
candies
jumbled
together.
What
is
the
expected
number
of
red
candies
among
five
candies
poured
from
the
box?
Ex.
3:
In
the
spring,
500
dinosaurs
were
caught
in
a
wilderness
area.
The
dinosaurs
were
released
after
being
outfitted
with
laser
vision.
To
estimate
the
dinosaur
population
in
the
area,
rangers
caught
40
dinosaurs
in
the
summer.
Of
these,
15
had
laser
vision.
Estimate
the
dinosaur
population
in
the
wilderness
area.
Watch
the
Video
for
Example
#1
on
p.
398-‐400
using
Excel;
CW:
p.
404-‐405
#
1-‐4,
7,
8,
10-‐12