Outcome 3. Higher. Using differentiation (Application). Higher Unit 1. Finding the gradient for a polynomial. Increasing / Decreasing functions. Max / Min and inflexion Points. Differentiating Brackets ( Type 1 ) . Curve Sketching. Differentiating Harder Terms (Type 2).
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Outcome 3
Higher
Using differentiation (Application)
Higher Unit 1
Finding the gradient for a polynomial
Increasing / Decreasing functions
Max / Min and inflexion Points
Differentiating Brackets ( Type 1 )
Curve Sketching
Differentiating Harder Terms (Type 2)
Max & Min Values on closed Intervals
Differentiating with Leibniz Notation
Optimization
Equation of a Tangent Line ( Type 3 )
Mind Map of Chapter
www.mathsrevision.com
Gradients & Curves
Outcome 3
Higher
On a straight line the gradient remains constant, however with curves the gradient changes continually, and the gradient at any point is in fact the same as the gradient of the tangent at that point.
The sides of the halfpipe are very steep(S) but it is not very steep near the base(B).
S
Demo
B
Gradients & Curves
Outcome 3
Higher
Gradient of tangent = gradient of curve at A
A
Demo
B
Gradient of tangent = gradient of curve at B
To find the gradient at any point on a curve we need to modify the gradient formula
Gradients & Curves
Outcome 3
Higher
For the function y = f(x) we do this by taking the point (x, f(x))
and another “very close point” ((x+h), f(x+h)).
Then we find the gradient between the two.
((x+h), f(x+h))
Approx gradient
(x, f(x))
True gradient
Gradients & Curves
Outcome 3
Higher
The gradient is not exactly the same but is
quite close to the actual value
We can improve the approximation by making the value of h smaller
This means the two points are closer together.
((x+h), f(x+h))
Approx gradient
(x, f(x))
True gradient
Gradients & Curves
Outcome 3
Higher
We can improve upon this approximation by making the value of h even smaller.
So the points are even closer together.
((x+h), f(x+h))
Approx gradient
True gradient
(x, f(x))
Outcome 3
Higher
We have seen that on curves the gradient changes continually and is dependant on the position on the curve. ie the xvalue of the given point.
Derivative
Finding the GRADIENT
Differentiating
The process of finding the gradient is called
Finding the rate of change
DIFFERENTIATING
or
FINDING THE DERIVATIVE (Gradient)
Derivative
Outcome 3
Higher
If the formula/equation of the curve is given by f(x)
Then the derivative is called f '(x)  “f dash x”
There is a simple way
of finding f '(x) from f(x).
f(x) f '(x)
2x24x
4x28x
Have guessed the rule yet !
5x1050x9
6x7 42x6
x3 3x2
x5 5x4
x99 99x98
Derivative
Rule for Differentiating
Outcome 3
Higher
It can be given by this simple flow diagram ...
multiply by the power
reduce the power by 1
If f(x) = axn
n
n
1
ax
then f '(x) =
NB: the following terms & expressions mean the same
GRADIENT,
DERIVATIVE,
RATE OF CHANGE,
f '(x)
Derivative
Rule for Differentiating
Outcome 3
Higher
To be able to differentiate
it is VERY IMPORTANT that you are
comfortable using indices rules
Outcome 3
Higher
(I) f(x) = ax (Straight line function)
Special Points
Index Laws
x0 = 1
If f(x) = ax
= ax1
then f '(x) = 1 X ax0
= a X 1 = a
So if g(x) = 12x then g '(x) = 12
Also using y = mx + c
The line y = 12x has gradient 12,
and derivative = gradient !!
Outcome 3
Higher
Special Points
(II) f(x) = a, (Horizontal Line)
Index Laws
x0 = 1
If f(x) = a
= a X 1 = ax0
then f '(x) = 0 X ax1
= 0
So if g(x) = 2 then g '(x) = 0
Also using formula y = c , (see outcome 1 !)
The line y = 2 is horizontal so has gradient 0 !
Differentiation techniques
Differentiation
=
Gradient
Differentiation
=
Rate of change
Name :
Calculus Revision
Differentiate
Calculus Revision
Differentiate
Calculus Revision
Differentiate
Derivative
Outcome 3
Higher
Example 1
A curve has equation f(x) = 3x4
Find the formula for its gradient and find the gradient when x = 2
Its gradient is f '(x) = 12x3
f '(2) = 12 X 23 =
12 X 8 =
96
Example 2
A curve has equation f(x) = 3x2
Find the formula for its gradient and find the gradient when x = 4
Its gradient is f '(x) = 6x
At the point where x = 4 the gradient is
f '(4) = 6 X 4 =
24
Derivative
Outcome 3
Higher
Example 3
If g(x) = 5x4  4x5 then find g '(2) .
g '(x) = 20x3  20x4
g '(2) = 20 X 23  20 X 24
= 160  320
= 160
Derivative
Outcome 3
Higher
Example 4
h(x) = 5x2  3x + 19
so h '(x) = 10x  3
and h '(4) = 10 X (4)  3
= 40  3 = 43
Example 5
k(x) = 5x4  2x3 + 19x  8, find k '(10) .
k '(x) = 20x3  6x2 + 19
So k '(10) = 20 X 1000  6 X 100 + 19
= 19419
Derivative
Outcome 3
Higher
Example 6 : Find the points on the curve
f(x) = x3  3x2 + 2x + 7 where the gradient is 2.
NB: gradient = derivative = f '(x)
Now using original formula
We need f '(x) = 2
ie 3x2  6x + 2 = 2
f(0) = 7
or 3x2  6x = 0
ie 3x(x  2) = 0
f(2) = 8 12 + 4 + 7
ie 3x = 0 or x  2 = 0
= 7
Points are (0,7) & (2,7)
so x = 0 or x = 2
Calculus Revision
Differentiate
Calculus Revision
Differentiate
Straight line form
Differentiate
Calculus Revision
Differentiate
Straight line form
Differentiate
Calculus Revision
Differentiate
Straight line form
Chain Rule
Simplify
Calculus Revision
Differentiate
Straight line form
Differentiate
Calculus Revision
Differentiate
Straight line form
Differentiate
Calculus Revision
Differentiate
Straight line form
Differentiate
Outcome 3
Higher
Brackets
Basic Rule: Break brackets before you differentiate !
Example
h(x) = 2x(x + 3)(x 3)
= 2x(x2  9)
= 2x3  18x
So h'(x) = 6x2 18
Calculus Revision
Differentiate
Multiply out
Differentiate
Calculus Revision
Differentiate
multiply out
differentiate
Calculus Revision
Differentiate
Straight line form
multiply out
Differentiate
Calculus Revision
Differentiate
multiply out
Differentiate
Calculus Revision
Differentiate
multiply out
Simplify
Straight line form
Differentiate
Calculus Revision
Differentiate
Multiply out
Straight line form
Differentiate
Outcome 3
Higher
Fractions
Reversing the above we get the following “rule” !
This can be used as follows …..
Fractions
Outcome 3
Higher
Example
f(x) = 3x3  x + 2 x2
= 3x3  x + 2 x2 x2x2
= 3x  x1 + 2x2
f '(x) = 3 + x2  4x3
= 3 + 1  4 x2 x3
Calculus Revision
Differentiate
Split up
Straight line form
Differentiate
Outcome 3
Higher
Leibniz Notation is an alternative way of expressing derivatives to f'(x) , g'(x) , etc.
Leibniz Notation
If y is expressed in terms of x then the derivative is written as dy/dx .
eg y = 3x2  7x
so dy/dx = 6x  7 .
Example 19
Q = 9R2  15 R3
Find dQ/dR
= 18R + 45 R4
NB: Q = 9R2  15R3
So dQ/dR = 18R + 45R4
Leibniz Notation
Outcome 3
Higher
Example 20
A curve has equation y = 5x3  4x2 + 7 .
Find the gradient where x = 2 ( differentiate ! )
gradient = dy/dx = 15x2  8x
if x = 2 then
gradient = 15 X (2)2  8 X (2)
= 60  (16) = 76
Real Life Example
Physics
Outcome 3
Higher
Newton’s 2ndLaw of Motion
s = ut + 1/2at2 where s = distance & t = time.
Finding ds/dt means “diff in dist” “diff in time”
ie speed or velocity
so ds/dt = u + at
but ds/dt = v so we get
v = u + at
and this is Newton’s 1st Law of Motion
Equation of Tangents
y = mx +c
Outcome 3
Higher
y = f(x)
A(a,b)
tangent
NB: at A(a, b) gradient of line = gradient of curve
gradient of line = m (from y = mx + c )
gradient of curve at (a, b) = f (a)
it follows that m = f (a)
Straight line so we need a point plus the gradient then we can use the formula y  b = m(x  a) .
Equation of Tangents
Outcome 3
Higher
Example 21
Find the equation of the tangent line to the curve
y = x3  2x + 1 at the point where x = 1.
Point: if x = 1 then y = (1)3  (2 X 1) + 1
= 1  (2) + 1
= 2point is (1,2)
Gradient:dy/dx = 3x2  2
when x = 1 dy/dx = 3 X (1)2  2
m = 1
= 3  2 = 1
Equation of Tangents
Outcome 3
Higher
Now using y  b = m(x  a)
point is (1,2)
m = 1
we get y  2 = 1( x + 1)
or y  2 = x + 1
or y = x + 3
Equation of Tangents
Outcome 3
Higher
Example 22
Find the equation of the tangent to the curve y = 4 x2 at the point where x = 2. (x 0)
Also find where the tangent cuts the Xaxis and Yaxis.
Point:when x = 2 then y = 4 (2)2
= 4/4 = 1
point is (2, 1)
Gradient:y = 4x2 so dy/dx = 8x3
= 8 x3
when x = 2 then dy/dx = 8 (2)3
= 8/8 = 1
m = 1
Equation of Tangents
Outcome 3
Higher
Now using y  b = m(x  a)
we get y  1 = 1( x + 2)
or y  1 = x + 2
or y = x + 3
Axes
Tangent cuts Yaxis when x = 0
so y = 0 + 3 = 3
at point (0, 3)
Tangent cuts Xaxis when y = 0
so 0 = x + 3 or x = 3
at point (3, 0)
Equation of Tangents
Outcome 3
Higher
Example 23  (other way round)
Find the point on the curve y = x2  6x + 5 where the gradient of the tangent is 14.
gradient of tangent = gradient of curve
dy/dx =
2x  6
so2x  6 = 14
2x = 20
x = 10
Put x = 10 into y = x2  6x + 5
Point is (10,45)
Giving y = 100  60 + 5
= 45
Outcome 3
Higher
Increasing & Decreasing Functions and Stationary Points
Consider the following graph of y = f(x) …..
y = f(x)
+
0
0
+

+
+
a
b
c
d
e
f

X
+
0
Increasing & Decreasing Functions and Stationary Points
Outcome 3
Higher
In the graph of y = f(x)
The function is increasing if the gradient is positive
i.e. f (x) > 0 when x < b or d < x < f or x > f .
The function is decreasing if the gradient is negative
and f (x) < 0 when b < x < d .
The function is stationary if the gradient is zero
and f (x) = 0 when x = b or x = d or x = f .
These are called STATIONARY POINTS.
At x = a, x = c and x = e
the curve is simply crossing the Xaxis.
Increasing & Decreasing Functions and Stationary Points
Outcome 3
Higher
Example 24
For the function f(x) = 4x2  24x + 19 determine the intervals when the function is decreasing and increasing.
f (x) = 8x  24
so 8x  24 < 0
f(x) decreasing when f (x) < 0
8x < 24
Check: f (2) = 8 X 2 – 24 = 8
x < 3
f(x) increasing when f (x) > 0
so 8x  24 > 0
8x > 24
Check: f (4) = 8 X 4 – 24 = 8
x > 3
Increasing & Decreasing Functions and Stationary Points
Outcome 3
Higher
Example 25
For the curve y = 6x – 5/x2
Determine if it is increasing or decreasing when x = 10.
y = 6x  5 x2
= 6x  5x2
so dy/dx = 6 + 10x3
= 6 + 10 x3
when x = 10 dy/dx = 6 + 10/1000
= 6.01
Since dy/dx > 0 then the function is increasing.
Increasing & Decreasing Functions and Stationary Points
Outcome 3
Higher
Example 26
Show that the function g(x) = 1/3x3 3x2 + 9x 10
is never decreasing.
g (x) = x2  6x + 9
= (x  3)(x  3)
= (x  3)2
Squaring a negative or a positive value produces a positive value, while 02 = 0. So you will never obtain a negative by squaring any real number.
Since (x  3)2 0 for all values of x
then g (x) can never be negative
so the function is never decreasing.
Increasing & Decreasing Functions and Stationary Points
Outcome 3
Higher
Example 27
Determine the intervals when the function
f(x) = 2x3 + 3x2  36x + 41
is (a) Stationary (b) Increasing (c) Decreasing.
f (x) = 6x2 + 6x  36
Function is stationary when f (x) = 0
= 6(x2 + x  6)
ie 6(x + 3)(x  2) = 0
= 6(x + 3)(x  2)
ie x = 3 or x = 2
Increasing & Decreasing Functions and Stationary Points
Outcome 3
Higher
We now use a special table of factors to determine when f (x) is positive & negative.
x
3
2

+
+
0
0
f’(x)
Function increasing when f (x) > 0
ie x < 3 or x > 2
Function decreasing when f (x) < 0
ie 3 < x < 2
Outcome 3
Higher
y = f(x)
Stationary Points and Their Nature
Consider this graph of y = f(x) again
0
+
0

+
+

c
+
a
b
X
+
0
Stationary Points and Their Nature
Outcome 3
Higher
This curve y = f(x) has three types of stationary point.
When x = a we have a maximum turning point (max TP)
When x = b we have a minimum turning point (min TP)
When x = c we have a point of inflexion (PI)
Each type of stationary point is determined by the gradient ( f(x) ) at either side of the stationary value.
Stationary Points and Their Nature
Outcome 3
Higher
Maximum Turning point
Minimum Turning Point
x
a
x
b
 0 +
f(x)
f(x)
+ 0 
Stationary Points and Their Nature
Outcome 3
Higher
Rising Point of inflexion
Other possible type of inflexion
x
c
x
d
f(x)
+ 0 +
f(x)
 0 
Stationary Points and Their Nature
Outcome 3
Higher
Example 28
Find the coordinates of the stationary point on the curve y = 4x3 + 1 and determine its nature.
SP occurs when dy/dx = 0
Using y = 4x3 + 1
so 12x2 = 0
if x = 0 then y = 1
x2 = 0
SP is at (0,1)
x = 0
Stationary Points and Their Nature
Outcome 3
Higher
Nature Table
x
0
+
+
dy/dx
0
dy/dx = 12x2
So (0,1) is a rising point of inflexion.
Stationary Points and Their Nature
Outcome 3
Higher
Example 29
Find the coordinates of the stationary points on the curve y = 3x4  16x3 + 24 and determine their nature.
Using y = 3x4  16x3 + 24
SP occurs when dy/dx = 0
So 12x3  48x2 = 0
if x = 0 then y = 24
12x2(x  4) = 0
if x = 4 then y = 232
12x2 = 0 or (x  4) = 0
x = 0 or x = 4
SPs at (0,24) & (4,232)
Stationary Points and Their Nature
Outcome 3
Higher
Nature Table
4
x
0
dy/dx
 0  0 +
dy/dx=12x3  48x2
So (0,24) is a Point of inflexion
and (4,232) is a minimum Turning Point
Stationary Points and Their Nature
Outcome 3
Higher
Example 30
Find the coordinates of the stationary points on the curve y = 1/2x4  4x2 + 2 and determine their nature.
Using y = 1/2x4  4x2 + 2
SP occurs when dy/dx = 0
if x = 0 then y = 2
So 2x3  8x= 0
if x = 2 then y = 6
2x(x2  4) = 0
if x = 2 then y = 6
2x(x + 2)(x  2) = 0
x = 0 or x = 2 or x = 2
SP’s at(2,6), (0,2) & (2,6)
Stationary Points and Their Nature
Outcome 3
Higher
Nature Table
x
2
0
2
dy/dx
 0 + 0  0 +
So (2,6) and (2,6) are Minimum Turning Points
and (0,2) is a Maximum Turning Points
Outcome 3
Higher
Note: A sketch is a rough drawing which includes important details. It is not an accurate scale drawing.
Curve Sketching
Process
(a) Find where the curve cuts the coordinate axes.
for Yaxis put x = 0
for Xaxis put y = 0 then solve.
(b) Find the stationary points & determine their nature as done in previous section.
(c)Check what happens as x +/ .
This comes automatically if (a) & (b) are correct.
Curve Sketching
Outcome 3
Higher
Dominant Terms
Suppose that f(x) = 2x3 + 6x2 + 56x  99
As x +/ (ie for large positive/negative values)
The formula is approximately the same as f(x) = 2x3
Graph roughly
As x + then y 
As x  then y +
Curve Sketching
Outcome 3
Higher
Example 31
Sketch the graph of y = 3x2 + 12x + 15
(a) Axes
If x = 0 then y = 15
If y = 0 then 3x2 + 12x + 15 = 0
( 3)
x2  4x  5 = 0
(x + 1)(x  5) = 0
x = 1 or x = 5
Graph cuts axes at (0,15) , (1,0) and (5,0)
Curve Sketching
Outcome 3
Higher
(b) Stationary Points
occur where dy/dx = 0
so 6x + 12 = 0
If x = 2
then y = 12 + 24 + 15 = 27
6x = 12
x = 2
Stationary Point is (2,27)
Nature Table
x
2
dy/dx
+ 0 
So (2,27)
is a Maximum Turning Point
Curve Sketching
Outcome 3
Higher
Summarising
as x + then y 
(c) Large values
as x  then y 
using y = 3x2
Y
Sketching
5
Cuts xaxis at 1 and 5
1
15
Cuts yaxis at 15
Max TP (2,27)
(2,27)
X
y = 3x2 + 12x + 15
Curve Sketching
Outcome 3
Higher
Example 32
Sketch the graph of y = 2x2 (x  4)
(a) Axes
If x = 0 then y = 0 X (4) = 0
If y = 0 then 2x2 (x  4) = 0
2x2 = 0 or (x  4) = 0
x = 0 or x = 4
(b) SPs
Graph cuts axes at (0,0) and (4,0) .
y = 2x2 (x  4)
= 2x3 + 8x2
SPs occur where dy/dx = 0
so 6x2 + 16x = 0
Curve Sketching
Outcome 3
Higher
2x(3x  8) = 0
2x = 0 or (3x  8) = 0
x = 0 or x = 8/3
If x = 0 then y = 0 (see part (a) )
If x = 8/3 then y = 2 X (8/3)2X (8/3 4) =512/27
nature
x
0
8/3

+

0
0
dy/dx
Curve Sketching
Outcome 3
Higher
Summarising
(c) Large values
as x + then y 
using y = 2x3
as x  then y +
Y
Sketch
Cuts x – axis at 0 and 4
4
0
Max TP’s at (8/3, 512/27)
(8/3, 512/27)
X
y = 2x2 (x – 4)
Curve Sketching
Outcome 3
Higher
Example 33
Sketch the graph of y = 8 + 2x2  x4
(a) Axes
If x = 0 then y = 8 (0,8)
If y = 0 then 8 + 2x2  x4 = 0
Let u = x2 so u2 = x4
Equation is now 8 + 2u  u2 = 0
(4  u)(2 + u) = 0
(4  x2)(2 + x2) = 0
or (2 + x) (2  x)(2 + x2) = 0
So x = 2 or x = 2 but x2 2
Graph cuts axes at (0,8) , (2,0) and (2,0)
Curve Sketching
Outcome 3
Higher
SPs occur where dy/dx = 0
(b) SPs
So 4x  4x3 = 0
4x(1  x2) = 0
4x(1  x)(1 + x) = 0
x = 0 or x =1 or x = 1
Using y = 8 + 2x2  x4
when x = 0 then y = 8
when x = 1 then y = 8 + 2  1 = 9 (1,9)
when x = 1 then y = 8 + 2  1 = 9 (1,9)
Curve Sketching
Outcome 3
Higher
nature
x
1
0
1
+

+

0
0
0
dy/dx
So (0,8) is a min TP while (1,9) & (1,9) are max TPs .
Curve Sketching
Outcome 3
Higher
Summarising
(c) Large values
Using y =  x4
Sketch is
as x + then y 
Y
as x  then y 
Cuts x – axis at 2 and 2
2
2
Cuts y – axis at 8
8
(1,9)
Max TP’s at
(1,9)
(1,9)
(1,9)
X
y = 8 + 2x2  x4
Outcome 3
Higher
Max & Min on Closed Intervals
In the previous section on curve sketching we dealt with the entire graph.
In this section we shall concentrate on the important details to be found in a small section of graph.
Suppose we consider any graph between the points where x = a and x = b (i.e. a x b)
then the following graphs illustrate where we would expect to find the maximum & minimum values.
Max & Min on Closed Intervals
Outcome 3
Higher
y =f(x)
(b, f(b))
max = f(b) end point
(a, f(a))
min = f(a) end point
X
a b
Max & Min on Closed Intervals
Outcome 3
Higher
(c, f(c))
max = f(c ) max TP
y =f(x)
(b, f(b))
min = f(a) end point
(a, f(a))
x
a b
c
NB: a < c < b
Max & Min on Closed Intervals
Outcome 3
Higher
y =f(x)
max = f(b) end point
(b, f(b))
(a, f(a))
(c, f(c))
min = f(c) min TP
x
NB: a < c < b
c
a b
Max & Min on Closed Intervals
Outcome 3
Higher
From the previous three diagrams we should be able to see that the maximum and minimum values of f(x) on the closed interval a x b can be found either at the end points or at a stationary point between the two end points
Example 34
Find the max & min values of y = 2x3  9x2 in the interval where 1 x 2.
End points
If x = 1 then y = 2  9 = 11
If x = 2 then y = 16  36 = 20
Max & Min on Closed Intervals
Outcome 3
Higher
Stationary points
dy/dx = 6x2  18x
= 6x(x  3)
SPs occur where dy/dx = 0
6x(x  3) = 0
6x = 0 or x  3 = 0
x = 0 or x = 3
not in interval
in interval
If x = 0 then y = 0  0 = 0
Hence for 1 x 2 , max = 0 & min = 20
Max & Min on Closed Intervals
Outcome 3
Higher
Extra bit
Using function notation we can say that
Domain = {xR: 1 x 2 }
Range = {yR: 20 y 0 }
Outcome 3
Higher
Optimization
Note: Optimum basically means the best possible.
In commerce or industry production costs and profits can often be given by a mathematical formula.
Optimum profit is as high as possible so we would look for a max value or max TP.
Optimum production cost is as low as possible so we would look for a min value or min TP.
Outcome 3
Higher
Optimization
Practical exercise on optimizing volume.
Graph
Problem
Q. What is the maximum volume
We can have for the given dimensions
Optimization
Outcome 3
Higher
Example 35
A rectangular sheet of foil measuring 16cm X 10 cm has four small squares each x cm cut from each corner.
16cm
x cm
10cm
x cm
NB: x > 0 but 2x < 10 or x < 5
ie 0 < x < 5
This gives us a particular interval to consider !
Optimization
Outcome 3
Higher
By folding up the four flaps we get a small cuboid
x cm
(10  2x) cm
(16  2x) cm
The volume is now determined by the value of x so we can write
V(x) = x(16  2x)(10  2x)
= x(160  52x + 4x2)
= 4x3  52x2 +160x
We now try to maximize V(x) between 0 and 5
Optimization
Outcome 3
Higher
End Points
Considering the interval 0 < x < 5
V(0) = 0 X 16 X 10 = 0
V(5) = 5 X 6 X 0 = 0
SPs
V '(x) = 12x2  104x + 160
= 4(3x2  26x + 40)
= 4(3x  20)(x  2)
Optimization
Outcome 3
Higher
SPs occur when V '(x) = 0
ie 4(3x  20)(x  2) = 0
3x  20 = 0 or x  2 = 0
ie x = 20/3or x = 2
not in interval
in interval
When x = 2 then
V(2) = 2 X 12 X 6 = 144
We now check gradient near x = 2
Optimization
Outcome 3
Higher
Nature
x
2

+
V '(x)
0
Hence max TP when x = 2
So max possible volume = 144cm3
Optimization
Outcome 3
Higher
Example 36
When a company launches a new product its share of the market after x months is calculated by the formula
(x 2)
So after 5 months the share is
S(5) = 2/5 – 4/25
= 6/25
Find the maximum share of the market
that the company can achieve.
Optimization
Outcome 3
Higher
End points
S(2) = 1 – 1 = 0
There is no upper limit but as x S(x) 0.
SPs occur where S (x) = 0
Optimization
Outcome 3
Higher
rearrange
8x2 = 2x3
8x2  2x3 = 0
2x2(4 – x) = 0
x = 0 or x = 4
In interval
Out with interval
We now check the gradients either side of 4
Optimization
Outcome 3
Higher
Nature
S (3.9 ) = 0.00337…
x 4
S (4.1) = 0.0029…

+
0
S (x)
Hence max TP at x = 4
And max share of market = S(4)
= 2/4 – 4/16
= 1/2 – 1/4
= 1/4
Nature Table
Equation of tangent line
Leibniz Notation
x
1
2
5

+
f’(x)
0
Straight Line
Theory
Max
Gradient at a point
f’(x)=0
Stationary Pts
Max. / Mini Pts
Inflection Pt
Graphs
f’(x)=0
Derivative
= gradient
= rate of change
Differentiation
of Polynomials
f(x) = axn
then f’x) = anxn1
Outcome 3
Are you on Target !