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Summary Notes 3.pdf
Summary Notes 3
.pdf
School
Irvine Valley College
*
*We aren't endorsed by this school
Course
CS 120
Subject
Mathematics
Date
Dec 16, 2024
Pages
19
Uploaded by AgentNeutron14927
Summary
Notes
3-Calculus
+
Probability
DS
120
Spen
Janima
Chatterje
PROBABILITY
1
.
when
order
matters
:
i
.
e
.
when
EA
,
B
,
C
is
&
different
from
EB
,
A
,
c}
eg
.
HAT
is
a
different
word
while
AH
is
a
different
word
with
the
same
letters
.
-
Use
Permutation
:
up
M
:
r)
!
⊥
-
Total
options
available
=
r
-
Total
empty
places
to
full
many
6
letter
words
(without
letter
Eg
.
How
make
with
repeated)
can
you
being
letters
of
the
alphabet
?
all
26
-
n
=
26
:
r
=
6
(26-
)
!
order
doesn't
matter
,
we
use
Combination
2
.
when
when
EA
,
B
,
CY
is
the
same
as
EB
,
A
,
C
.
i
.
2
..
-
-
-
Combination
:
r
=
T
Eg
.
A
group
has
s
people
.
In
how
many
different
ways
can
you
make
a
committee
of
3
people
out
of
this
group
.
-
>
n
=
5
M
=
3
Order
doesn't
matter
:
Combination
.
3Cz
·
Probability
of
an
event
happening
:
#
of
ways
the
event
can
happen
#
of
outcomes
·
Independent
events
:
Occurance
of
I
event
doesn't
effect
the
ocurance
of
the
other
event
.
·
Probability
of
2
independent
events
P(A
and
B)
=
P(A)
.
P(B)
·
Disjoint
events
:
Events
that
cannot
happen
together
·
P(A
or
B)
=
P(A)
+
P(B)
·
Binomial
distribution
:
events
with
2
outcomes
-
Works
for
p
:
probability
of
one
outcome
7
&
a
:
probability
of
other
outcome
:
C-p)
N
:
Total
number
of
trials
r
:
Total
number
of
successes
(happening
of
the
are
interested
in)
event
we
-
Probability
of
oberving
r
successes
in
N
independent
trials
:
N-M
p(X
=
r
,
N
,
p)
=
NC
q(-p)
CONDITIONAL
PROBABILITY
-
·
probability
of
event
A
,
guier
event
B
:
P(ArB)
P(AIB)-
P(B)
-
A
and
B
are
independent
:
I
P(A(B)
=
P
=
P(A)
PB)
Occurance
of
B
doesn't
effect
occurance
of
A
·
Bay's
Rule
:
P(B(A)
=
p(A1B)
·
P(B)
-
p(A)
#ECTATION
P(X
x)
X
=
x
_
probability
we
will
multiply
the
individual
i
.
2
.
of
each
outcome
to
the
outcome
and
seem
it
for
all
outcomes
·
E [X
+
Y]
=
E(X]
+
E[y]
·
ETaX]
=
a
E[X]
VARIANCE
-
·
van
(x)
=
E((X
-
E(xi)]
i
.
e
..
you
calculate
expected
value
.
-F(X)
expected
value
from
each
outcome
2
·
subtract
square
them
-
>
(n-E(X])
=
and
-
each
term
to
their
individual
*
multiply
T
p(X
=
u)
(x
-
E[x]]
probability
terms
together
·
Add
all
the
&
(a
-
E[X])
?
.
P(X
=
x)
X
=
x
·
Var
(X
+
Y)
=
Var(X)
+
Var
(Y)
·
Var
(aX)
=
Var (X)
GAUSSIAN
AND
CENTRAL
LIMIT
THEOREM
#
-
-
Mean
of
sample
--
/
population
M-
Mean
of
original
distribution
I
I
My
-
Mean
of
sampling
distribution
of
sample
mean
-I
standard
deviation
of
sample
⊥
I
standard
deviation
of
sampling
distribution
of
sample
means
MX
=
U
is
sample
size
where
t
U
=
On
z
:
M
=
X-
M
-
Ex
/
95
%
of
the
data
lis
1
.
91
standard
deviations
away
mean
from
the
z
-
Tells
us
now
many
standard
deviations
away
from
the
actual
mean
,
our
observed
mean
is
⊥
-
Standard
Error
&
"-
variance
of
sample
u
=
w
<
variance
of
sampling
distribution
of
sample
means
&
Confidence
Interval
:
Range
in
which
our
true
mean
is
likely
to
lie
with
a
certain
probability
:
&
M
=
Ex
-
z
.
8
,
X
+
28x)
*
-
Observed
mean
corresponding
to
confidence/probability
z-
Value
from
Confidence
Table
.
(If
nothing
is
given
,
assume
95
%
Confidence
U
-
standard
error
#
In
order
to
calculate
Confidence
Interval
,
_
a
*
(observed
sample
Mean)
1
.
Identify
Identify
or
Q
(variance
or
standard
deviation
2
.
-o
estimated
by
the
of
original
distribution
8
sample
variance
or
sample
standard
deviation)
3
.
Identify
n
,
(sample
size)
1
.
Calculate
standard
error-
by
=
nX
D
-
-
Confidence
percentage
5
.
Tentify
&
assume
95
%
]
(If
nothing
is
given
,
z-value
of
the
6
.
Look
up
E-table
for
given
confidence
percentage
F
.
Calculate
Confidence
Internal
:
m
:
[5-
b
·
Y
+
z
.
=]
z
-
BESSEL'S
CORRECTION
If
sample
data
is
given
and
you
have
to
calculate
the
variance
from
the
data
,
use
Bessel's
Correction
to
calculate
Make
sure
you
Ex
2
g
[
-
*
(xi
-
x)
n
-
1
i
=
1
⑤
degrees
of
freedom
If
sample
size
30
:
No
z-table
If
sample
size
30
:
Use
t-table
when
sample
size
30
-
>
use
t
distribution
when
sample
size
>30
-
use
z
distribution
when
Variance/S
.
d
.
Not
given
to
us
,
-
to
estimate
Bessel's
correction
.
use
deiration
from
the
population
standard
when
n30
(preferable
sample
-
Especially
bessels
if
sample
is
the
to
always
apply
-
used
to
*
interval
:
estimate
.
-a
calculating
confidence
population
For
sid
.
S
Is
Y
given
?
I
I
Yes
-No
*
P
-
actual
population
Je
S
.
&
.
Calculate
X
-
I
I
S-
estimated
population
-
s
.
d
.
Is
us
quien
?
I
T
No
I
Yes
I
↓
svessel's
correction
-
↑
Calculate
using
S
or
Ux
=
&
-
v
⊥
standard
error
.
I
.
2
.
Op
=
M
n
Calculate
#
Is
n 30
-No
I
Yes
*
use
M
=Y
+
z
.
Ex
Use
M
=
Y
+
t
.
U
MULTIVARIABLE
CALCULUS
·
f(x)
=
an
-
f'(x)
=
nx"
-
·
h(x)
=
fa
+
g(x)
+
h'(x)
=
y'(x)
+
g(x)
·
h(x)
=
f(x).
g(u)
-
>
h'(x)
=
y'(x)
.
g(x)
+
g(x)
.
f(x)
·
hx
=
f (g(x)
-
>
hea)
=
y (g()
.
g'()
-
Partial
derivatives
,
Multivariable
funcions
:
for
Symbol/Notation
-
O
instead
of
d
·
I
-
Partial
derivative
with
respect
to
x
.
Treat
other
variables
like
any
other
number/constant
·
Tny
-
Order
of
variables
in
the
subscript
tell
you
the
order
in
which
the
partial
derivative
was
calculated
How
to
find
saddle
points
,
relative
Maximum
or
Minimum
?
-
Calculate
gradient
of
f
(x
,
y
,
z
...
)
·
+8 ]
-
>
Equate
If
to
0
:
If
=
0
-
Calculate
the
value
of
(R
,
Y
,
z
...
)
for
which
If
critical
points
is
O
.
These
are
your
2
-
>
Calculate
D
=
You
Dyy
-
buy
each
critical
point
-
Evaluate
D
for
J
Saddle
point
·
130
-
·
If
Do
and
Jun
Lo
-
Relative
Max
·
If
Do
and
fun
>
0-
Relative
Min
DIRECTIONAL
DERIVATIVES
·
Directional
Derivative
of
f(K
,
Y
,
2)
at
a
point
(No
,
Yo
,
zo)
along
a
unit
vector
:
**
f
=
If
(4
,
%2)
·
is
f
*
unit
vector
i
in
the
direction
of
-
·
Direction
of
stepest
descent
:
-
f
·
Direction
of
stepest
ascent
:
Of
·
one
step
of
gradient
descent
:
xj
=
no
-
&Tf(x)
d
+
step
size
In
general
,
en
=
an
-
def(um)
y
=
%
.
-
d
-f
(yo)
In
general
Yn
+
1
=
Yn
-
d
+
f(yn)
I
Fred
is
living
up
his
four
gol
trophies
on
a
N
shelf
.
How
many
different
possible
arrangements
can
he
make
?
password
consists
of
3
digits
,
o
to
9)
,
followed
&
A
from
the
alphabet
(25
letters)
.
If
by
letters
but
repetition
10
-
a
reperton
of
digits
is
allowed
,
different
is
not
allowed
,
how
many
of
alphabets
passwords
can
be
made
?
&
A
student
calculates
a
90
%
confidence
interval
I
--
for
M
when
o
is
known
.
The
confidence
interval
cents
to
64
.
3
cents
.
What
is
is
-
24
.
3
the
sample
mean
X
?
In
the
Ohio
Lottery
,
there
is
a
game
called
-
Q
.
"Lucky
4"
.
The
player
pays
$
10
to
pick
a
I
digit
number
(repetitions
allowed)
.
If
in
the
Lottery
,
4
numbers
come
up
in
the
&
expected
,
You
win
$
1000
.
order
as
you
jacked
same
value
?
What
is
your
O
Find
all
the
first
order
partial
derivatives
-
y
of
and
valculate
the
gradient
at
(1
,
1)
f
(x
,
y)
-
3x3y
+
4y
SAT
scores
are
normally
distributed
with
mean
&.
ists
and
standard
deviation
325
.
a
If
one
sat
score
is
chosen
at
random
,
find
the
probability
that
it
is
between
and
1480
1440
b
.
If
16
SAT
scores
are
chosen
at
random
,
find
the
probability
that
they
have
a
mean
between
1440
and
1480
.
a
Calculate
the
directional
derivative
of
-
f(x
,
y)
=
3x2
+
47
in
the
direction
of
vector
T
:
(i]
at
point
(2
,
)
or
Knee
Q.
200
patients
who
had
either
chip
surgery
satisfied
-
were
surgery
were
asked
whether
they
or
dissatisfied
regarding
their
results
.
surgery
satisfied
Dissatisfied
Total
Knee
70
25
95
Hip
90
15
105
Total
160
40
200
these
200
is
selected
at
-3
a)
If
one
person
from
probability
the
patient
random
,
determine
the
is
satisfied
,
given
they
had
unle
surgery
b)
was
dissatisfied
given
they
had
hip
surgery