Topics
Relations and Functions
Relations and Functions
Algebra
Inverse Trigonometric Functions
Matrices
- Concept of Matrices
- Types of Matrices
- Equality of Matrices
- Operations on Matrices> Addition and Subtraction of Matrices
- Operations on Matrices>Scalar Multiplication
- Operations on Matrices> Matrix Multiplication
- Transpose of a Matrix
- Symmetric and Skew Symmetric Matrices
- Invertible Matrices
- Overview of Matrices
Calculus
Determinants
Vectors and Three-dimensional Geometry
Continuity and Differentiability
- Continuous and Discontinuous Functions
- Algebra of Continuous Functions
- Concept of Differentiability
- Derivatives of Composite Functions
- Derivative of Implicit Functions
- Derivative of Inverse Function
- Exponential and Logarithmic Functions
- Logarithmic Differentiation
- Derivatives of Functions in Parametric Forms
- Second Order Derivative
- Overview of Continuity and Differentiability
Linear Programming
Probability
Applications of Derivatives
Integrals
- Introduction of Integrals
- Integration as an Inverse Process of Differentiation
- Properties of Indefinite Integral
- Methods of Integration> Integration by Substitution
- Methods of Integration>Integration Using Trigonometric Identities
- Methods of Integration> Integration Using Partial Fraction
- Methods of Integration> Integration by Parts
- Integrals of Some Particular Functions
- Definite Integrals
- Fundamental Theorem of Integral Calculus
- Evaluation of Definite Integrals by Substitution
- Properties of Definite Integrals
- Overview of Integrals
Sets
Applications of the Integrals
Differential Equations
- Basic Concepts of Differential Equations
- Order and Degree of a Differential Equation
- General and Particular Solutions of a Differential Equation
- Methods of Solving Differential Equations> Variable Separable Differential Equations
- Methods of Solving Differential Equations> Homogeneous Differential Equations
- Methods of Solving Differential Equations>Linear Differential Equations
- Overview of Differential Equations
Vectors
- Basic Concepts of Vector Algebra
- Direction Ratios, Direction Cosine & Direction Angles
- Types of Vectors in Algebra
- Algebra of Vector Addition
- Multiplication in Vector Algebra
- Components of Vector in Algebra
- Vector Joining Two Points in Algebra
- Section Formula in Vector Algebra
- Product of Two Vectors
- Overview of Vectors
Three - Dimensional Geometry
Linear Programming
Probability
Definition: Continuity at a Point
Let f(x) be a real function and a be a point in its domain.
A function f is continuous at x = a iff all three conditions hold:
- f(a) is defined
- \[\lim_{x\to a}f(x)\] exists
- \[\lim_{x\to a}f(x)\] = f(a)
\[\lim_{x\to a^-}f(x)=\lim_{x\to a^+}f(x)=f(a)\]
Key Points: When Function is Not Continuous
A function fails to be continuous at x = a if any one of the following occurs:
-
f(a) is not defined
-
\[\lim_{x\to a}f(x)\] does not exist
-
Either LHL or RHL does not exist
-
Or LHL ≠ RHL
-
-
\[\lim_{x\to a}f(x)\] exists but \[\lim_{x\to a}f(x)\] ≠ f(a)
Key Points: Types of Discontinuity
| Basis of Comparison | Removable Discontinuity | Non-Removable Discontinuity |
|---|---|---|
| Existence of \[\lim_{x\to a}f(x)\] | Exists | Does not exist |
| Left Hand Limit (LHL) | Exists | May not exist |
| Right Hand Limit (RHL) | Exists | May not exist |
| Relation between LHL & RHL | LHL = RHL | LHL ≠ RHL (or one/both do not exist) |
| Value of f(a) | Not defined OR f(a) ≠ \[\lim_{x\to a}f(x)\] | May or may not be defined |
| Continuity at ( x = a ) | Discontinuous | Discontinuous |
| Graphical interpretation | Hole/gap in the graph | Jump, break or vertical asymptote |
| Nature of discontinuity | Temporary | Permanent |
Definition: Continuity in an Interval
For the open interval:
A function f is said to be continuous on an open interval (a, b) if it is continuous at every point in the interval.
For a closed interval:
A function f is said to be continuous on the closed interval [a,b] iff:
-
f is continuous at every point of (a,b)
-
f is right continuous at a
\[\lim_{x\to a^+}f(x)=f(a)\] -
f is left continuous at b
\[\lim_{x\to b^-}f(x)=f(b)\]
Definition: Domain of Continuity
The set of all points where a function is continuous is called its domain of continuity.
Formula: Derivative at any Point
A function f is said to have a derivative at any point x if
\[f^{\prime}(x)=\lim_{h\to0}\frac{f(x+h)-f(x)}{h}\]
Formula: Implicit Differentiation
\[\frac{d}{dx}(y^n)=ny^{n-1}\frac{dy}{dx}\]
\[\frac{d}{dx}(xy)=x\frac{dy}{dx}+y\]
Formula: Exponential Function
-
-
-
\[(a^x)^y=a^{xy}\]
- \[a^{-x}=\frac{1}{a^x}\]
\[\frac{d}{dx}(e^x)=e^x\]
\[\frac{d}{dx}(a^x)=a^x\log a,\quad a>0,a\neq1\]
\[\frac{d}{dx}(e^{f(x)})=e^{f(x)}\cdot f^{\prime}(x)\]
\[\frac{d}{dx}(a^{f(x)})=a^{f(x)}\log a\cdot f^{\prime}(x)\]
Formula: Derivative of Product of Function
(i) Product of two functions
If y = uv then, \[\frac{dy}{dx}=u\frac{dv}{dx}+v\frac{du}{dx}\]
(i) Product of three functions
If y = uvw then \[\frac{dy}{dx}=uv\frac{dw}{dx}+uw\frac{dv}{dx}+vw\frac{du}{dx}\]
Formula: Derivative of Quotient Function
Quotient Rule:
If \[y=\frac{u}{v}\] then \[\frac{dy}{dx}=\frac{v\frac{du}{dx}-u\frac{dv}{dx}}{v^2}\]
Reciprocal Rule:
\[\frac{d}{dx}{\left(\frac{1}{f(x)}\right)}=-\frac{f^{\prime}(x)}{[f(x)]^2}\]
Formula: Logarithmic Function
| Function / Rule | Derivative |
|---|---|
| log x | \[\frac{1}{x}\] |
| \[\log_{a}x\] | \[\frac{1}{x\log a}\] |
| \[\log_ax^n\] | \[n\log_ax\] |
| log u | \[\frac{1}{u}\cdot\frac{du}{dx}\] |
| \[log_a1\] | 0 |
| \[\log_aa\] | 1 |
| \[log_au\] | \[\frac{1}{u\log a}\cdot\frac{du}{dx}\] |
| \[\log_a(xy)\] | \[\log_ax+\log_ay\] |
| \[\log_a\left(\frac{x}{y}\right)\] | \[\log_ax-\log_ay\] |
| \[\log_ax\] | \[\frac{\log x}{\log a}\] |
| \[y=u^{v}\] | \[u^v\frac{d}{dx}(v\log u)\] |
Formula: Parametric Functions
First derivative:
If x = f(t), y = ϕ(t) then \[\frac{dy}{dx}=\frac{\frac{dy}{dt}}{\frac{dx}{dt}}\]
Second derivative:
\[\frac{d^2y}{dx^2}=\frac{\frac{d}{dt}\left(\frac{dy}{dx}\right)}{\frac{dx}{dt}}\]
Formula: Differentiation of a Determinant
For a 2×2 determinant:
\[F^{\prime}(x)=
\begin{vmatrix}
f_1^{\prime}(x) & f_2(x) \\
g_1^{\prime}(x) & g_2(x)
\end{vmatrix}+
\begin{vmatrix}
f_1(x) & f_2^{\prime}(x) \\
g_1(x) & g_2^{\prime}(x)
\end{vmatrix}\]
For a 3×3 determinant:
\[\mathrm{F^{\prime}}(x)=
\begin{vmatrix}
f_1^{\prime}(x) & f_2^{\prime}(x) & f_3^{\prime}(x) \\
g_1(x) & g_2(x) & g_3^{\prime}(x) \\
h_1(x) & h_2(x) & h_3(x)
\end{vmatrix}+
\begin{vmatrix}
f_1(x) & f_2(x) & f_3(x) \\
g_1^{\prime}(x) & g_2^{\prime}(x) & g_3^{\prime}(x) \\
h_1(x) & h_2(x) & h_3(x)
\end{vmatrix}+
\begin{vmatrix}
f_1(x) & f_2(x) & f_3(x) \\
g_1(x) & g_2(x) & g_3(x) \\
h_1^{\prime}(x) & h_2^{\prime}(x) & h_3^{\prime}(x)
\end{vmatrix}\]
Theorem: Rolle’s Theorem
If a function f(x) is
-
Continuous on [a,b]
-
Differentiable on (a,b)
-
f(a) = f(b)
Then there exists at least one c ∈ (a,b) such that f′(c) = 0
Theorem: Lagrange's Mean Value Theorem
f a function f(x) is
-
Continuous on [a,b]
-
Differentiable on (a,b)
Then there exists at least one c ∈ (a,b) such that
\[f^{\prime}(c)=\frac{f(b)-f(a)}{b-a}\]
