Differentiation: Applications of derivatives
The second derivative
The derivative #f'# of a function #f# can be differentiated again. We call this the second derivative of #f#.
For a function #\blue{f(x)}# , we denote the second derivative as:
\[\purple{f''(x)}=\frac{\dd}{\dd x}\green{f'(x)}=\frac{\dd}{\dd x}\left(\frac{\dd}{\dd x}\blue{f(x)}\right)=\frac{\dd^2}{\dd x^2} \,\blue{f(x)}\]
Example
\[\begin{array}{rcl}\blue{f(x)}&\blue{=}&\blue{3x^2}\\ \green{f'(x)}&\green{=}&\green{6x}\\\purple{f''(x)}&\purple{=}&\purple{6}\end{array}\]
The second derivative is useful when one wants to find the extreme values of a function #f(x)#. We saw earlier that the condition #f'(c)=0# does not immediately imply that #c# corresponds to an extreme value. The following theorem will help us determine whether stationary points, which are points with #f'(c)=0#, correspond to an extreme value or not without sketching the graph or making a sign analysis chart.
Identifying stationary points
Let #\blue{f(x)}# be a function and #\orange{c}# a stationary point in the domain of #\blue{f(x)}#.
If #\purple{f''(}\orange{c}\purple{)}\neq 0#, then #\blue{f(x)}# has an extreme value in #\orange{c}#.
More specifically,
- If #\purple{f''(}\orange{c}\purple{)}>0#, then #\orange{c}# corresponds to a local minimum,
- If #\purple{f''(}\orange{c}\purple{)}<0#, then #\orange{c}# corresponds to a local maximum.
Example
\[\begin{array}{rcl}\blue{f(x)}&=&\blue{2x^2+x}\\
\green{f'(x)}&=&\green{4x+1}\\
\purple{f''(x)}&=&\purple{4}\\
\green{f'(}\orange{-\frac{1}{4}}\green{)}&=&0\\
\purple{f''(}\orange{-\frac{1}{4}}\purple{)}&=&4\neq 0\end{array}\] #\textstyle\purple{f''(}\orange{-\frac{1}{4}}\purple{)}> 0#, so #\textstyle\blue{f(}\orange{-\frac{1}{4}}\blue{)}=\frac{3}{8}#
is a local minimum of #\blue{f(x)}#.
We first calculate the first derivative using the power rule.
\[f'(x)=28\cdot x^3-10\cdot x\]
Then we calculate the second derivative in the same way.
\[f''(x)=84\cdot x^2-10\]
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