Rules for computing derivatives of functions
This is a summary of differentiation rules , that is, rules for computing the
derivative of a
function in
calculus .
Elementary rules of differentiation
Unless otherwise stated, all functions are functions of
real numbers (R ) that return real values; although more generally, the formulae below apply wherever they are
well defined
[ 1]
[ 2] — including the case of
complex numbers (C ) .
[ 3]
For any value of
c
{\displaystyle c}
, where
c
∈
R
{\displaystyle c\in \mathbb {R} }
, if
f
(
x
)
{\displaystyle f(x)}
is the constant function given by
f
(
x
)
=
c
{\displaystyle f(x)=c}
, then
d
f
d
x
=
0
{\displaystyle {\frac {df}{dx}}=0}
.
[ 4]
Let
c
∈
R
{\displaystyle c\in \mathbb {R} }
and
f
(
x
)
=
c
{\displaystyle f(x)=c}
. By the definition of the derivative,
f
′
(
x
)
=
lim
h
→
0
f
(
x
+
h
)
−
f
(
x
)
h
=
lim
h
→
0
(
c
)
−
(
c
)
h
=
lim
h
→
0
0
h
=
lim
h
→
0
0
=
0
{\displaystyle {\begin{aligned}f'(x)&=\lim _{h\to 0}{\frac {f(x+h)-f(x)}{h}}\\&=\lim _{h\to 0}{\frac {(c)-(c)}{h}}\\&=\lim _{h\to 0}{\frac {0}{h}}\\&=\lim _{h\to 0}0\\&=0\end{aligned}}}
This shows that the derivative of any constant function is 0.
Intuitive (geometric) explanation
The
derivative of the function at a point is the slope of the line
tangent to the curve at the point.
Slope of the constant function is zero, because the
tangent line to the constant function is horizontal and its angle is zero.
In other words, the value of the constant function, y, will not change as the value of x increases or decreases.
At each point, the
derivative is the slope of a
line that is
tangent to the
curve at that point. Note: the derivative at point A is
positive where green and dash–dot,
negative where red and dashed, and
zero where black and solid.
Differentiation is linear
For any functions
f
{\displaystyle f}
and
g
{\displaystyle g}
and any real numbers
a
{\displaystyle a}
and
b
{\displaystyle b}
, the derivative of the function
h
(
x
)
=
a
f
(
x
)
+
b
g
(
x
)
{\displaystyle h(x)=af(x)+bg(x)}
with respect to
x
{\displaystyle x}
is:
h
′
(
x
)
=
a
f
′
(
x
)
+
b
g
′
(
x
)
.
{\displaystyle h'(x)=af'(x)+bg'(x).}
In
Leibniz's notation this is written as:
d
(
a
f
+
b
g
)
d
x
=
a
d
f
d
x
+
b
d
g
d
x
.
{\displaystyle {\frac {d(af+bg)}{dx}}=a{\frac {df}{dx}}+b{\frac {dg}{dx}}.}
Special cases include:
The constant factor rule
(
a
f
)
′
=
a
f
′
{\displaystyle (af)'=af'}
The sum rule
(
f
+
g
)
′
=
f
′
+
g
′
{\displaystyle (f+g)'=f'+g'}
The difference rule
(
f
−
g
)
′
=
f
′
−
g
′
.
{\displaystyle (f-g)'=f'-g'.}
For the functions
f
{\displaystyle f}
and
g
{\displaystyle g}
, the derivative of the function
h
(
x
)
=
f
(
x
)
g
(
x
)
{\displaystyle h(x)=f(x)g(x)}
with respect to
x
{\displaystyle x}
is
h
′
(
x
)
=
(
f
g
)
′
(
x
)
=
f
′
(
x
)
g
(
x
)
+
f
(
x
)
g
′
(
x
)
.
{\displaystyle h'(x)=(fg)'(x)=f'(x)g(x)+f(x)g'(x).}
In Leibniz's notation this is written
d
(
f
g
)
d
x
=
g
d
f
d
x
+
f
d
g
d
x
.
{\displaystyle {\frac {d(fg)}{dx}}=g{\frac {df}{dx}}+f{\frac {dg}{dx}}.}
The derivative of the function
h
(
x
)
=
f
(
g
(
x
)
)
{\displaystyle h(x)=f(g(x))}
is
h
′
(
x
)
=
f
′
(
g
(
x
)
)
⋅
g
′
(
x
)
.
{\displaystyle h'(x)=f'(g(x))\cdot g'(x).}
In Leibniz's notation, this is written as:
d
d
x
h
(
x
)
=
d
d
z
f
(
z
)
|
z
=
g
(
x
)
⋅
d
d
x
g
(
x
)
,
{\displaystyle {\frac {d}{dx}}h(x)=\left.{\frac {d}{dz}}f(z)\right|_{z=g(x)}\cdot {\frac {d}{dx}}g(x),}
often abridged to
d
h
(
x
)
d
x
=
d
f
(
g
(
x
)
)
d
g
(
x
)
⋅
d
g
(
x
)
d
x
.
{\displaystyle {\frac {dh(x)}{dx}}={\frac {df(g(x))}{dg(x)}}\cdot {\frac {dg(x)}{dx}}.}
Focusing on the notion of maps, and the differential being a map
D
{\displaystyle {\text{D}}}
, this is written in a more concise way as:
D
(
f
∘
g
)
x
=
D
f
g
(
x
)
⋅
D
g
x
.
{\displaystyle [{\text{D}}(f\circ g)]_{x}=[{\text{D}}f]_{g(x)}\cdot [{\text{D}}g]_{x}\,.}
The inverse function rule
If the function f has an
inverse function g , meaning that
g
(
f
(
x
)
)
=
x
{\displaystyle g(f(x))=x}
and
f
(
g
(
y
)
)
=
y
,
{\displaystyle f(g(y))=y,}
then
g
′
=
1
f
′
∘
g
.
{\displaystyle g'={\frac {1}{f'\circ g}}.}
In Leibniz notation, this is written as
d
x
d
y
=
1
d
y
d
x
.
{\displaystyle {\frac {dx}{dy}}={\frac {1}{\frac {dy}{dx}}}.}
Power laws, polynomials, quotients, and reciprocals
The polynomial or elementary power rule
If
f
(
x
)
=
x
r
{\displaystyle f(x)=x^{r}}
, for any real number
r
≠
0
,
{\displaystyle r\neq 0,}
then
f
′
(
x
)
=
r
x
r
−
1
.
{\displaystyle f'(x)=rx^{r-1}.}
When
r
=
1
,
{\displaystyle r=1,}
this becomes the special case that if
f
(
x
)
=
x
,
{\displaystyle f(x)=x,}
then
f
′
(
x
)
=
1.
{\displaystyle f'(x)=1.}
Combining the power rule with the sum and constant multiple rules permits the computation of the derivative of any polynomial.
The derivative of
h
(
x
)
=
1
f
(
x
)
{\displaystyle h(x)={\frac {1}{f(x)}}}
for any (nonvanishing) function f is:
h
′
(
x
)
=
−
f
′
(
x
)
(
f
(
x
)
)
2
{\displaystyle h'(x)=-{\frac {f'(x)}{(f(x))^{2}}}}
wherever f is non-zero.
In Leibniz's notation, this is written
d
(
1
/
f
)
d
x
=
−
1
f
2
d
f
d
x
.
{\displaystyle {\frac {d(1/f)}{dx}}=-{\frac {1}{f^{2}}}{\frac {df}{dx}}.}
The reciprocal rule can be derived either from the quotient rule, or from the combination of power rule and chain rule.
If f and g are functions, then:
(
f
g
)
′
=
f
′
g
−
g
′
f
g
2
{\displaystyle \left({\frac {f}{g}}\right)'={\frac {f'g-g'f}{g^{2}}}\quad }
wherever g is nonzero.
This can be derived from the product rule and the reciprocal rule.
The elementary power rule generalizes considerably. The most general power rule is the functional power rule : for any functions f and g ,
(
f
g
)
′
=
(
e
g
ln
f
)
′
=
f
g
(
f
′
g
f
+
g
′
ln
f
)
,
{\displaystyle (f^{g})'=\left(e^{g\ln f}\right)'=f^{g}\left(f'{g \over f}+g'\ln f\right),\quad }
wherever both sides are well defined.
Special cases
If
f
(
x
)
=
x
a
{\textstyle f(x)=x^{a}\!}
, then
f
′
(
x
)
=
a
x
a
−
1
{\textstyle f'(x)=ax^{a-1}}
when a is any non-zero real number and x is positive.
The reciprocal rule may be derived as the special case where
g
(
x
)
=
−
1
{\textstyle g(x)=-1\!}
.
Derivatives of exponential and logarithmic functions
d
d
x
(
c
a
x
)
=
a
c
a
x
ln
c
,
c
>
0
{\displaystyle {\frac {d}{dx}}\left(c^{ax}\right)={ac^{ax}\ln c},\qquad c>0}
the equation above is true for all c , but the derivative for
c
<
0
{\textstyle c<0}
yields a complex number.
d
d
x
(
e
a
x
)
=
a
e
a
x
{\displaystyle {\frac {d}{dx}}\left(e^{ax}\right)=ae^{ax}}
d
d
x
(
log
c
x
)
=
1
x
ln
c
,
c
>
1
{\displaystyle {\frac {d}{dx}}\left(\log _{c}x\right)={1 \over x\ln c},\qquad c>1}
the equation above is also true for all c , but yields a complex number if
c
<
0
{\textstyle c<0\!}
.
d
d
x
(
ln
x
)
=
1
x
,
x
>
0.
{\displaystyle {\frac {d}{dx}}\left(\ln x\right)={1 \over x},\qquad x>0.}
d
d
x
(
ln
|
x
|
)
=
1
x
,
x
≠
0.
{\displaystyle {\frac {d}{dx}}\left(\ln |x|\right)={1 \over x},\qquad x\neq 0.}
d
d
x
(
W
(
x
)
)
=
1
x
+
e
W
(
x
)
,
x
>
−
1
e
.
{\displaystyle {\frac {d}{dx}}\left(W(x)\right)={1 \over {x+e^{W(x)}}},\qquad x>-{1 \over e}.\qquad }
where
W
(
x
)
{\displaystyle W(x)}
is the
Lambert W function
d
d
x
(
x
x
)
=
x
x
(
1
+
ln
x
)
.
{\displaystyle {\frac {d}{dx}}\left(x^{x}\right)=x^{x}(1+\ln x).}
d
d
x
(
f
(
x
)
g
(
x
)
)
=
g
(
x
)
f
(
x
)
g
(
x
)
−
1
d
f
d
x
+
f
(
x
)
g
(
x
)
ln
(
f
(
x
)
)
d
g
d
x
,
if
f
(
x
)
>
0
,
and if
d
f
d
x
and
d
g
d
x
exist.
{\displaystyle {\frac {d}{dx}}\left(f(x)^{g(x)}\right)=g(x)f(x)^{g(x)-1}{\frac {df}{dx}}+f(x)^{g(x)}\ln {(f(x))}{\frac {dg}{dx}},\qquad {\text{if }}f(x)>0,{\text{ and if }}{\frac {df}{dx}}{\text{ and }}{\frac {dg}{dx}}{\text{ exist.}}}
d
d
x
(
f
1
(
x
)
f
2
(
x
)
(
.
.
.
)
f
n
(
x
)
)
=
∑
k
=
1
n
∂
∂
x
k
(
f
1
(
x
1
)
f
2
(
x
2
)
(
.
.
.
)
f
n
(
x
n
)
)
|
x
1
=
x
2
=
.
.
.
=
x
n
=
x
,
if
f
i
<
n
(
x
)
>
0
and
{\displaystyle {\frac {d}{dx}}\left(f_{1}(x)^{f_{2}(x)^{\left(...\right)^{f_{n}(x)}}}\right)=\left[\sum \limits _{k=1}^{n}{\frac {\partial }{\partial x_{k}}}\left(f_{1}(x_{1})^{f_{2}(x_{2})^{\left(...\right)^{f_{n}(x_{n})}}}\right)\right]{\biggr \vert }_{x_{1}=x_{2}=...=x_{n}=x},{\text{ if }}f_{i<n}(x)>0{\text{ and }}}
d
f
i
d
x
exists.
{\displaystyle {\frac {df_{i}}{dx}}{\text{ exists. }}}
The
logarithmic derivative is another way of stating the rule for differentiating the
logarithm of a function (using the chain rule):
(
ln
f
)
′
=
f
′
f
{\displaystyle (\ln f)'={\frac {f'}{f}}\quad }
wherever f is positive.
Logarithmic differentiation is a technique which uses logarithms and its differentiation rules to simplify certain expressions before actually applying the derivative.[
citation needed ]
Logarithms can be used to remove exponents, convert products into sums, and convert division into subtraction — each of which may lead to a simplified expression for taking derivatives.
Derivatives of trigonometric functions
d
d
x
sin
x
=
cos
x
{\displaystyle {\frac {d}{dx}}\sin x=\cos x}
d
d
x
arcsin
x
=
1
1
−
x
2
{\displaystyle {\frac {d}{dx}}\arcsin x={\frac {1}{\sqrt {1-x^{2}}}}}
d
d
x
cos
x
=
−
sin
x
{\displaystyle {\frac {d}{dx}}\cos x=-\sin x}
d
d
x
arccos
x
=
−
1
1
−
x
2
{\displaystyle {\frac {d}{dx}}\arccos x=-{\frac {1}{\sqrt {1-x^{2}}}}}
d
d
x
tan
x
=
sec
2
x
=
1
cos
2
x
=
1
+
tan
2
x
{\displaystyle {\frac {d}{dx}}\tan x=\sec ^{2}x={\frac {1}{\cos ^{2}x}}=1+\tan ^{2}x}
d
d
x
arctan
x
=
1
1
+
x
2
{\displaystyle {\frac {d}{dx}}\arctan x={\frac {1}{1+x^{2}}}}
d
d
x
csc
x
=
−
csc
x
cot
x
{\displaystyle {\frac {d}{dx}}\csc x=-\csc {x}\cot {x}}
d
d
x
arccsc
x
=
−
1
|
x
|
x
2
−
1
{\displaystyle {\frac {d}{dx}}\operatorname {arccsc} x=-{\frac {1}{|x|{\sqrt {x^{2}-1}}}}}
d
d
x
sec
x
=
sec
x
tan
x
{\displaystyle {\frac {d}{dx}}\sec x=\sec {x}\tan {x}}
d
d
x
arcsec
x
=
1
|
x
|
x
2
−
1
{\displaystyle {\frac {d}{dx}}\operatorname {arcsec} x={\frac {1}{|x|{\sqrt {x^{2}-1}}}}}
d
d
x
cot
x
=
−
csc
2
x
=
−
1
sin
2
x
=
−
1
−
cot
2
x
{\displaystyle {\frac {d}{dx}}\cot x=-\csc ^{2}x=-{\frac {1}{\sin ^{2}x}}=-1-\cot ^{2}x}
d
d
x
arccot
x
=
−
1
1
+
x
2
{\displaystyle {\frac {d}{dx}}\operatorname {arccot} x=-{1 \over 1+x^{2}}}
The derivatives in the table above are for when the range of the inverse secant is
0
,
π
{\displaystyle [0,\pi ]\!}
and when the range of the inverse cosecant is
−
π
2
,
π
2
.
{\displaystyle \left[-{\frac {\pi }{2}},{\frac {\pi }{2}}\right].}
It is common to additionally define an
inverse tangent function with two arguments ,
arctan
(
y
,
x
)
.
{\displaystyle \arctan(y,x).}
Its value lies in the range
−
π
,
π
{\displaystyle [-\pi ,\pi ]}
and reflects the quadrant of the point
(
x
,
y
)
.
{\displaystyle (x,y).}
For the first and fourth quadrant (i.e.
x
>
0
{\displaystyle x>0}
) one has
arctan
(
y
,
x
>
0
)
=
arctan
(
y
/
x
)
.
{\displaystyle \arctan(y,x>0)=\arctan(y/x).}
Its partial derivatives are
∂
arctan
(
y
,
x
)
∂
y
=
x
x
2
+
y
2
and
∂
arctan
(
y
,
x
)
∂
x
=
−
y
x
2
+
y
2
.
{\displaystyle {\frac {\partial \arctan(y,x)}{\partial y}}={\frac {x}{x^{2}+y^{2}}}\qquad {\text{and}}\qquad {\frac {\partial \arctan(y,x)}{\partial x}}={\frac {-y}{x^{2}+y^{2}}}.}
Derivatives of hyperbolic functions
d
d
x
sinh
x
=
cosh
x
{\displaystyle {\frac {d}{dx}}\sinh x=\cosh x}
d
d
x
arsinh
x
=
1
1
+
x
2
{\displaystyle {\frac {d}{dx}}\operatorname {arsinh} x={\frac {1}{\sqrt {1+x^{2}}}}}
d
d
x
cosh
x
=
sinh
x
{\displaystyle {\frac {d}{dx}}\cosh x=\sinh x}
d
d
x
arcosh
x
=
1
x
2
−
1
{\displaystyle {\frac {d}{dx}}\operatorname {arcosh} x={\frac {1}{\sqrt {x^{2}-1}}}}
d
d
x
tanh
x
=
sech
2
x
=
1
−
tanh
2
x
{\displaystyle {\frac {d}{dx}}\tanh x={\operatorname {sech} ^{2}x}=1-\tanh ^{2}x}
d
d
x
artanh
x
=
1
1
−
x
2
{\displaystyle {\frac {d}{dx}}\operatorname {artanh} x={\frac {1}{1-x^{2}}}}
d
d
x
csch
x
=
−
csch
x
coth
x
{\displaystyle {\frac {d}{dx}}\operatorname {csch} x=-\operatorname {csch} {x}\coth {x}}
d
d
x
arcsch
x
=
−
1
|
x
|
1
+
x
2
{\displaystyle {\frac {d}{dx}}\operatorname {arcsch} x=-{\frac {1}{|x|{\sqrt {1+x^{2}}}}}}
d
d
x
sech
x
=
−
sech
x
tanh
x
{\displaystyle {\frac {d}{dx}}\operatorname {sech} x=-\operatorname {sech} {x}\tanh {x}}
d
d
x
arsech
x
=
−
1
x
1
−
x
2
{\displaystyle {\frac {d}{dx}}\operatorname {arsech} x=-{\frac {1}{x{\sqrt {1-x^{2}}}}}}
d
d
x
coth
x
=
−
csch
2
x
=
1
−
coth
2
x
{\displaystyle {\frac {d}{dx}}\coth x=-\operatorname {csch} ^{2}x=1-\coth ^{2}x}
d
d
x
arcoth
x
=
1
1
−
x
2
{\displaystyle {\frac {d}{dx}}\operatorname {arcoth} x={\frac {1}{1-x^{2}}}}
See
Hyperbolic functions for restrictions on these derivatives.
Derivatives of special functions
Gamma function
Γ
(
x
)
=
∫
0
∞
t
x
−
1
e
−
t
d
t
{\displaystyle \Gamma (x)=\int _{0}^{\infty }t^{x-1}e^{-t}\,dt}
Γ
′
(
x
)
=
∫
0
∞
t
x
−
1
e
−
t
ln
t
d
t
=
Γ
(
x
)
(
∑
n
=
1
∞
(
ln
(
1
+
1
n
)
−
1
x
+
n
)
−
1
x
)
=
Γ
(
x
)
ψ
(
x
)
{\displaystyle {\begin{aligned}\Gamma '(x)&=\int _{0}^{\infty }t^{x-1}e^{-t}\ln t\,dt\\&=\Gamma (x)\left(\sum _{n=1}^{\infty }\left(\ln \left(1+{\dfrac {1}{n}}\right)-{\dfrac {1}{x+n}}\right)-{\dfrac {1}{x}}\right)\\&=\Gamma (x)\psi (x)\end{aligned}}}
with
ψ
(
x
)
{\displaystyle \psi (x)}
being the
digamma function , expressed by the parenthesized expression to the right of
Γ
(
x
)
{\displaystyle \Gamma (x)}
in the line above.
Riemann zeta function
ζ
(
x
)
=
∑
n
=
1
∞
1
n
x
{\displaystyle \zeta (x)=\sum _{n=1}^{\infty }{\frac {1}{n^{x}}}}
ζ
′
(
x
)
=
−
∑
n
=
1
∞
ln
n
n
x
=
−
ln
2
2
x
−
ln
3
3
x
−
ln
4
4
x
−
⋯
=
−
∑
p
prime
p
−
x
ln
p
(
1
−
p
−
x
)
2
∏
q
prime
,
q
≠
p
1
1
−
q
−
x
{\displaystyle {\begin{aligned}\zeta '(x)&=-\sum _{n=1}^{\infty }{\frac {\ln n}{n^{x}}}=-{\frac {\ln 2}{2^{x}}}-{\frac {\ln 3}{3^{x}}}-{\frac {\ln 4}{4^{x}}}-\cdots \\&=-\sum _{p{\text{ prime}}}{\frac {p^{-x}\ln p}{(1-p^{-x})^{2}}}\prod _{q{\text{ prime}},q\neq p}{\frac {1}{1-q^{-x}}}\end{aligned}}}
Suppose that it is required to differentiate with respect to x the function
F
(
x
)
=
∫
a
(
x
)
b
(
x
)
f
(
x
,
t
)
d
t
,
{\displaystyle F(x)=\int _{a(x)}^{b(x)}f(x,t)\,dt,}
where the functions
f
(
x
,
t
)
{\displaystyle f(x,t)}
and
∂
∂
x
f
(
x
,
t
)
{\displaystyle {\frac {\partial }{\partial x}}\,f(x,t)}
are both continuous in both
t
{\displaystyle t}
and
x
{\displaystyle x}
in some region of the
(
t
,
x
)
{\displaystyle (t,x)}
plane, including
a
(
x
)
≤
t
≤
b
(
x
)
,
{\displaystyle a(x)\leq t\leq b(x),}
x
0
≤
x
≤
x
1
{\displaystyle x_{0}\leq x\leq x_{1}}
, and the functions
a
(
x
)
{\displaystyle a(x)}
and
b
(
x
)
{\displaystyle b(x)}
are both continuous and both have continuous derivatives for
x
0
≤
x
≤
x
1
{\displaystyle x_{0}\leq x\leq x_{1}}
. Then for
x
0
≤
x
≤
x
1
{\displaystyle \,x_{0}\leq x\leq x_{1}}
:
F
′
(
x
)
=
f
(
x
,
b
(
x
)
)
b
′
(
x
)
−
f
(
x
,
a
(
x
)
)
a
′
(
x
)
+
∫
a
(
x
)
b
(
x
)
∂
∂
x
f
(
x
,
t
)
d
t
.
{\displaystyle F'(x)=f(x,b(x))\,b'(x)-f(x,a(x))\,a'(x)+\int _{a(x)}^{b(x)}{\frac {\partial }{\partial x}}\,f(x,t)\;dt\,.}
This formula is the general form of the
Leibniz integral rule and can be derived using the
fundamental theorem of calculus .
Some rules exist for computing the n -th derivative of functions, where n is a positive integer. These include:
If f and g are n -times differentiable, then
d
n
d
x
n
f
(
g
(
x
)
)
=
n
!
∑
{
k
m
}
f
(
r
)
(
g
(
x
)
)
∏
m
=
1
n
1
k
m
!
(
g
(
m
)
(
x
)
)
k
m
{\displaystyle {\frac {d^{n}}{dx^{n}}}[f(g(x))]=n!\sum _{\{k_{m}\}}f^{(r)}(g(x))\prod _{m=1}^{n}{\frac {1}{k_{m}!}}\left(g^{(m)}(x)\right)^{k_{m}}}
where
r
=
∑
m
=
1
n
−
1
k
m
{\textstyle r=\sum _{m=1}^{n-1}k_{m}}
and the set
{
k
m
}
{\displaystyle \{k_{m}\}}
consists of all non-negative integer solutions of the Diophantine equation
∑
m
=
1
n
m
k
m
=
n
{\textstyle \sum _{m=1}^{n}mk_{m}=n}
.
If f and g are n -times differentiable, then
d
n
d
x
n
f
(
x
)
g
(
x
)
=
∑
k
=
0
n
(
n
k
)
d
n
−
k
d
x
n
−
k
f
(
x
)
d
k
d
x
k
g
(
x
)
{\displaystyle {\frac {d^{n}}{dx^{n}}}[f(x)g(x)]=\sum _{k=0}^{n}{\binom {n}{k}}{\frac {d^{n-k}}{dx^{n-k}}}f(x){\frac {d^{k}}{dx^{k}}}g(x)}
^ Calculus (5th edition) , F. Ayres, E. Mendelson, Schaum's Outline Series, 2009,
ISBN
978-0-07-150861-2 .
^ Advanced Calculus (3rd edition) , R. Wrede, M.R. Spiegel, Schaum's Outline Series, 2010,
ISBN
978-0-07-162366-7 .
^ Complex Variables , M.R. Spiegel, S. Lipschutz, J.J. Schiller, D. Spellman, Schaum's Outlines Series, McGraw Hill (USA), 2009,
ISBN
978-0-07-161569-3
^
"Differentiation Rules" . University of Waterloo – CEMC Open Courseware . Retrieved 3 May 2022 .
Sources and further reading
These rules are given in many books, both on elementary and advanced calculus, in pure and applied mathematics. Those in this article (in addition to the above references) can be found in:
Mathematical Handbook of Formulas and Tables (3rd edition) , S. Lipschutz, M.R. Spiegel, J. Liu, Schaum's Outline Series, 2009,
ISBN
978-0-07-154855-7 .
The Cambridge Handbook of Physics Formulas , G. Woan, Cambridge University Press, 2010,
ISBN
978-0-521-57507-2 .
Mathematical methods for physics and engineering , K.F. Riley, M.P. Hobson, S.J. Bence, Cambridge University Press, 2010,
ISBN
978-0-521-86153-3
NIST Handbook of Mathematical Functions , F. W. J. Olver, D. W. Lozier, R. F. Boisvert, C. W. Clark, Cambridge University Press, 2010,
ISBN
978-0-521-19225-5 .