- •Lecture 1.
- •§1. Determinants and their properties
- •Is the minor of .
- •§2. Matrices and operations on them. Inverse matrix
- •Definition 4. (Definition of a matrix)
- •§3. Systems of linear equations
- •Vector Addition and Multiplication of a vector by a scalar
- •2 The inner, vector and mixed product of vectors
- •Inner Product and its Properties
- •Lecture 2.
- •Vectors. The elementary operations over vectors. The scalar, vector and mixed product of vectors.
- •§1. The elementary operations over vectors
- •Vector Product and its Properties
- •The vector product in coordinates. Consider vectors
- •Triple Product in Coordinates. Given three vectors , , and , let us express the triple product of these vectors in terms of their coordinates. Consider the triple product
- •The simplest problem of analytic geometry
- •Division of an interval in a given ratio. Suppose given an interval м1м2. Let us find the coordinates a of point м on the interval for which .
- •3. Second-Order Curves in the Plane Ellipse
- •Parabola
- •Lecture 4 Function. The function limit. Fundamental theorems on limits. Infinitely small and infinitely large quantities
- •1. Functions
- •2. The Theory of Limits
- •Infinitesimals and bounded functions.
- •3. Fundamental Theorems on Limits
- •4. Continuity of Functions
- •Lecture 5 The derivative of the function. Geometric and mechanical meaning of derivative. Table of derivatives. The differential of a function
- •1. The derivative of a function
- •Implicit Function Derivative
- •2. Differential of a function
- •3. Higher Derivatives
- •1. Properties of differentiable functions
- •L’Hospital’s Rule for Form
- •L’Hospital’s Rule for Form
- •Taylor’s formula
- •2. Monotonic conditions. Extremum of function
- •3. Convexity and concavity. Point of inflection
- •4. Asymptotes
- •5. General Scheme for the Investigation of the Graph of a Function
- •1. Concept of functions of several variables
- •2. Partial derivatives. Total differential
- •3. Differentiation of composite and implicit functions. Tangent and surface normal
- •Implicit function of two variables
- •4. Partial derivatives and higher order differentials
- •5. Extrema of functions of two variables
- •Lecture 8 Antiderivative. Indefinite integral and its properties. Table of integrals. Main methods of integration
- •1. Antiderivative and indefinite integral
- •2. Main methods of integration
- •Integration by substitution ( or change of variable )
- •Integration by parts
- •3. Integration of fractional rational functions
- •I. Integrating Proper Rational Functions
- •II. Integrating Improper Rational Functions
- •4. Integration of irrational functions
- •5. Integration of trigonometric functions
- •1. Concept of definite integral
- •2. Main properties of definite integrals
- •Integration by substitution
- •Integration by Parts
- •3. Applications of definite integrals
- •The areas of plane figures
- •Lecture 11 Differential equations of the first and second order. Homogeneous and non-homogeneous linear differential equations. Linear differential equations with constant coefficients
- •1. Problems that lead to differential equations
- •2. Equations with separable variables
- •3. Bernoulli’s equation
- •4. The equations that allow lower-order
- •5. Homogeneous equation
- •1. Numerical series
- •6. Types of series:
- •2. The convergence of the sum of the series
- •Integral
- •3. Alternating series
- •4. Power series
- •Main concept. Definition of probability
- •2. Properties of probability
- •Lecture 15. Elements of Mathematical Statistics. Random variables, their types. Distribution laws of random variables
- •1. Random variables, their types
- •2. Distribution laws of random variables
2. Monotonic conditions. Extremum of function
Theorem 1. Let
be continuous on [a, b] and differentiable on (a, b).
is a constant
function if and only if
for all
.
Definition 1. A function is said to be monotonic increasing (resp. monotonic decreasing )
or simply increasing ( resp. decreasing ) on an
interval
if and only if
,
if
then
(resp.
,
if
,
then
).
Definition 2. A function is said to be strictly increasing ( resp. strictly decreasing ) on an
interval
if and only if
,
if
then
(resp.
,
if
,
then
).
Theorem 2. Let be continuous on [a, b] and differentiable on (a, b). Then
(a) if
is strictly
increasing
on [a, b]; and
(b)if
is strictly decreasing
on [a, b].
Definition 3. A
neighborhood of a point
is an open interval containing
,
i.e.
is
a neighborhood of
for some
.
Definition 4. A
function
is said to attain a relative maximum (minimum ) at a point
if
(
)
in a certain neighborhood of
,
i.e.
such that
(
)
for
.
Theorem (Fermat Theorem).
Given
is a point defined on
and differentiable at a point
if
has an extreme value ( max. or min )
,
then
.
N
ote
has maximum or minimum at
.
Definition 5. (a) A turning point is a maximum or minimum point.
If
,
then
is called a critical or
stationary value and its corresponding point on
the graph
is called stationary point.
Notes
1. turning point stationary point
2. turning point + differentiable stationary point
3. stationary point turning point
3. Convexity and concavity. Point of inflection
Let
be a function differentiable on an interval J. The function f
is called convex
(concave)
on J, if all points of its graph on J lie above (below) any tangent
line to
on this interval (excepting point of tangency). Let f
be continuous at a point
.
If there exists
such that f is concave (convex) in
and convex (concave) in
,
the point
is called the point of inflection
of
.
The second Derivative Test for Concavity and Convexity:
If
,
for each
,
then
is convex on J,
if
,
for each
,
then
is concave on J.
It follows:
If is continuous at and ( ) in and ( ) in , then is a point of inflection.
Moreover: If
is a point of inflection of f,
then either
or
doesn’t exist.
If f
is three times differentiable at a point
,
and
,
then
is a point of inflection.
Definition 6. Given
that
is continuous on
,
if any
such that
(i)
(ii)
Concave Downward
Concave Upward
Theorem 3. If is a function on such that is second differentiable on then
(i)
if
is concave upward on
(ii)
if
is concave downward on
.
Definition 7. Let
be a continuous function. A point
on the graph of
is a point of inflexion (point of inflection) if the graph on one
side of this point is concave downward and concave upward on the
other side. That is, the graph changes concavity at
.
Note A point of inflexion of a curve must be a continuous point but need not be differentiable there. In Figure (c), R is a point of inflexion of the curve but the function is not differentiable at .
Theorem 4. If is second differentiable function and attains a point of inflexion at , then
.
Note:
(i) max. or min. point but not derivative.
(ii) point of inflexion may not be obtained by
solving
where
and
such that
.
(iii) Let
be a function which is second differentiable in a neighborhood of a
point of inflexion iff
does not change sign as
increases through (sign gradient test)
– if
and
,
then
attains a relative max. or relative min.
– if
and
,
then
attains an inflexion point at
.
