1. Second Derivatives, Inflection Points and Concavity

2. Important Terms
turning point: points where the direction of the function changes
maximum: the highest point on a function
minimum: the lowest point on a function
local vs absolute: a max can be a highest point in the entire domain (absolute) or only over a specified region within the domain (local). Likewise for a minimum.
increase: the part of the domain (the interval) where the function values are getting larger as the independent variable gets higher; if f(x1) < f(x2) when x1 < x2; the graph of the function is going up to the right (or down to the left)
decrease: the part of the domain (the interval) where the function values are getting smaller as the independent variable gets higher; if f(x1) > f(x2) when x1 < x2; the graph of the function is going up to the left (or down to the right)
"end behaviour": describing the function values (or appearance of the graph) as x values getting infinitely large positively or infinitely large negatively or approaching an asymptote

3. New Term – Graphs Showing Concavity

4. New Term – Concave Up Concavity is best “defined” with graphs
(i) “concave up” means in simple terms that the “direction of opening” is upward or the curve is “cupped upward”
An alternative way to describe it is to visualize where you would draw the tangent lines  you would have to draw the tangent lines “underneath” the curve

5. New Term – Concave down Concavity is best “defined” with graphs
(ii) “concave down” means in simple terms that the “direction of opening” is downward or the curve is “cupped downward”
An alternative way to describe it is to visualize where you would draw the tangent lines  you would have to draw the tangent lines “above” the curve

6. New Term – Concavity
In keeping with the idea of concavity and the drawn tangent lines, if a curve is concave up and we were to draw a number of tangent lines and determine their slopes, we would see that the values of the tangent slopes increases (become more positive) as our x-value at which we drew the tangent slopes increase
This idea of the “increase of the tangent slope is illustrated on the next slides:

7. New Term – Concave Up

8. New Term – Concave Down

9. Functions and Their Derivatives
In order to “see” the connection between a graph of a function and the graph of its derivative, we will use graphing technology to generate graphs of functions and simultaneously generate a graph of its derivative
Then we will connect concepts like max/min, increase/decrease, concavities on the original function to what we see on the graph of its derivative

10. Example 1

11. Example 1 Points to note:
(1) the fn has a minimum at x=2 and the derivative has an x-intercept at x=2
(2) the fn decreases on (-∞,2) and the derivative has negative values on (-∞,2)
(3) the fn increases on (2,+∞) and the derivative has positive values on (2,+∞)
(4) the fn changes from decrease to increase at the min while the derivative values change from negative to positive
(5) the function is concave up and the derivative fn is an increasing fn
(6) the second derivative graph is positive on the entire domain

12. Example 2

13. Example 2
f(x) has a max. at x = -3.1 and f `(x) has an x-intercept at x = -3.1
f(x) has a min. at x = -0.2 and f `(x) has a root at –0.2
f(x) increases on (-, -3.1) & (-0.2, ) and on the same intervals, f `(x) has positive values
f(x) decreases on (-3.1, -0.2) and on the same interval, f `(x) has negative values
At the max (x = -3.1), the fcn changes from being an increasing fcn to a decreasing fcn  the derivative changes from positive values to negative values
At a the min (x = -0.2), the fcn changes from decreasing to increasing  the derivative changes from negative to positive
f(x) is concave down on (-, -1.67) while f `(x) decreases on (-, -1.67) and the 2nd derivative is negative on (-, -1.67)
f(x) is concave up on (-1.67,  ) while f `(x) increases on (-1.67, ) and the 2nd derivative is positive on (-1.67, )
The concavity of f(x) changes from CD to CU at x = -1.67, while the derivative has a min. at x = -1.67

14. Second Derivative – A Summary
If f ‘’(x) >0, then f(x) is concave up
If f ‘(x) < 0, then f(x) is concave down
If f ‘’(x) = 0, then f(x) is neither concave nor concave down, but has an inflection points where the concavity is then changing directions
The second derivative also gives information about the “extreme points” or “critical points” or max/mins on the original function:
If f ‘(x) = 0 and f ‘’(x) > 0, then the critical point is a minimum point (picture y = x2 at x = 0)
If f ‘(x) = 0 and f ‘’(x) < 0, then the critical point is a maximum point (picture y = -x2 at x = 0)
These last two points form the basis of the “Second Derivative Test” which allows us to test for maximum and minimum values

15. Examples - Algebraically
Find where the curve y = x3 - 3x2 - 9x - 5 is concave up and concave down. Find and classify all extreme points. Then use this info to sketch the curve.
f(x) = x3 – 3x2 - 9x – 5
f `(x) = 3x2 – 6x - 9 = 3(x2 – 2x – 3) = 3(x – 3)(x + 1)
So f(x) has critical points (or local/global extrema) at x = -1 and x = 3
f ``(x) = 6x – 6 = 6(x – 1)
So at x = 1, f ``(x) = 0 and we have a change of concavity
Then f ``(-1) = -12  the curve is concave down, so x = -1 must represent a maximum point
Also f `(3) = +12  the curve is concave up, so x = 3 must represent a minimum point
Then f(3) = -33, f(-1) = 0 as the ordered pairs for the function whose graph is shown on the next slide: