Derivative of a function f at a number a edit

Notation edit

We denote the derivative of a function   at a number   as  .

Definition edit

The derivative of a function   at a number   a is given by the following limit (if it exists):

 


An analogous equation can be defined by letting  . Then  , which shows that when   approaches  ,   approaches  :

 

Interpretations edit

As the slope of a tangent line edit

Given a function  , the derivative   can be understood as the slope of the tangent line to   at  :

As a rate of change edit

The derivative of a function   at a number   can be understood as the instantaneous rate of change of   when  .

At a tangent to one point of a curve edit

Vocabulary edit

The point A(a; f(a)) is the point in contact of the tangent and Cf.

Definition edit

If f is differentiable in a, then the curve C admits at a point A which has for coordinates (a ; f(a)), a tangent : it is the straight line passing by A and of direction coefficient f'(a). An equation of that tangent is written: y = f'(a)*(x-a)+f(a)

Degrees edit

First Degree Derivative [First Order Derivative; f'(x)] edit

The first degree derivative of a function, commonly showing the slope of the tangent line at one point of the function, shows its instantaneous rate of change. Intuitively, the first degree derivative reveals the direction of the function; a positive first degree derivative shows the increasing of a function, and it shows decreasing when negative.

Minimum/Maximum edit

Local edit

Local minimums/maximums are found from solving for f'(x)=0, for f(x) is differentiable for all x on desired interval. When the first order derivative is zero, it suggests the stop in increasing or decreasing. Whether the point x at f'(x)=0 is a maximum or minimum requires the derivative to the left and right of x. If the derivative is positive on the left and negative on the right; if the graph shifts from increasing to decreasing at point x, f(x) at x would be a local maximum. Conversely, If the derivative is negative on the left and positive on the right; if the graph shifts from decreasing to increasing at point x, f(x) at x would be a local maximum.

Global edit

Global minimums/maximums are found at the smallest/largest y-values of each graph.

A saddle point refers to the point where f'(x)=0 but the graph maintains its movement direction.

Application edit

In a function that measures an object's disposition, the first order derivative shows its instantaneous change in position, i.e. velocity.

Second Degree Derivative [Second Order Derivative; f''(x)] edit

The second order derivative takes

Inflection Point edit

An inflection point refers to the point where the function changes its concavity (from sloping up to down, vice versa). The inflection point is found from solving for f''(x)=0, for f(x) is differentiable for all x on desired interval.

Application edit

In a function that measures an object's velocity, the first order derivative shows its instantaneous change in velocity, i.e. acceleration.

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Differentiation Rules edit

Power Rule edit

One of the most commonly used derivative rules for functions in the form of  (  raised to the  th power),  .

 

Polynomial Differentiations edit

Taking the derivative of a polynomial requires the differentiation procedure to be applied to each term including the variable  .

Example:

 

 

Negative Power Differentiations edit

Taking the derivative of a function in the form   can be achieved through rewriting the function with a negative power,  .

Example:

 

 

Fractional Exponents and Radicals edit

Differentiating a function with a radical such as a square root, , can be done through rewriting the function in the form with a fraction as the exponent,  .

Example:

 

 

Quotient Rule edit

This rule is used to differentiate functions written in the form of  .

 

Example:

 

 

Trigonometric Functions edit

Rules for differentiating trigonometric functions:

 

 

 

 

 

 

Logarithmic Functions edit

Rules for differentiating logarithmic functions:

 

 

Sample Problems edit

Differentiate the following:

  1.  
  2.  
  3.  
  4.  
  5.  
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  8.