I understand these concepts (increasing, decreasing, maximum, minimum, etc.) at a very high level, but it is useful to define them precisely.
High level of f′(x) and f′′(x)
Intuitively, f′(x) represents the rate of change of the values of f(x) (or think of it as the slope of the tangent lines to f(x). We use f′(x) to understand when a function is increasing and decreasing, as well as find extrema values.
f′′(x) is a bit harder to grasp. It describes the rate of change of the tangent line to f(x).
Think of it related to Newton’s law,
s′′(t)=v′(t)=a(t)
The second derivative provides information about the curve behavior, which we call concavity.
Increasing and Decreasing, Monotonic
A function f is increasing if f(x2​)>f(x1​) whenever x2​>x1​.
A function f is decreasing if f(x2​)<f(x1​) whenever x2​>x1​.
We can define these in terms of the derivative,
Note: The converse is NOT true. If f is increasing we may still find that f′(x)=0 at some isolated points.#idontunderstand
Maxima and Minima (Extrema), Critical Point
A function f has an absolute maximum at c if f(c)≥f(x) for all x in the domain of f.
A function f has an absolute minimum at c if f(c)≤f(x) for all x in the domain of f.
Algorithm for identifying Global Extrema: Closed Interval Method
We use the idea that if c is a global maximum or minimum of f, one of three things must be true:
f′(c)=0 (a critical point)
f′(c) is undefined (a critical point)
c is an endpoint of the interval.
Thus, we develop an algorithm for this.
Algorithm for identifying Local Extrema: First Derivative Test
The second derivative test also works.
Concavity, Inflection Point
If the concavity of f(x) changes at a point (x0​,f(x0​)), then we call this point an inflection point.