Topics
Mathematical Logic
- Concept of Statements
- Truth Value of Statement
- Logical Connective, Simple and Compound Statements
- Statement Patterns and Logical Equivalence
- Tautology, Contradiction, and Contingency
- Duality
- Quantifier and Quantified Statements in Logic
- Negations of Compound Statements
- Converse, Inverse, and Contrapositive
- Algebra of Statements
- Application of Logic to Switching Circuits
- Overview of Mathematical Logic
Matrices
- Elementry Transformations
- Properties of Matrix Multiplication
- Application of Matrices
- Applications of Determinants and Matrices
- Overview of Matrices
Trigonometric Functions
- Trigonometric Equations and Their Solutions
- Solutions of Triangle
- Inverse Trigonometric Functions
- Overview of Trigonometric Functions
Pair of Straight Lines
- Combined Equation of a Pair Lines
- Homogeneous Equation of Degree Two
- Angle between lines represented by ax2 + 2hxy + by2 = 0
- General Second Degree Equation in x and y
- Equation of a Line in Space
- Overview of Pair of Straight Lines
Vectors
Line and Plane
- Vector and Cartesian Equations of a Line
- Distance of a Point from a Line
- Distance Between Skew Lines and Parallel Lines
- Equation of a Plane
- Angle Between Planes
- Coplanarity of Two Lines
- Distance of a Point from a Plane
- Overview of Line and Plane
Linear Programming
Differentiation
- Differentiation
- Derivatives of Composite Functions - Chain Rule
- Geometrical Meaning of Derivative
- Derivatives of Inverse Functions
- Logarithmic Differentiation
- Derivatives of Implicit Functions
- Derivatives of Parametric Functions
- Higher Order Derivatives
- Overview of Differentiation
Applications of Derivatives
- Applications of Derivatives in Geometry
- Derivatives as a Rate Measure
- Approximations
- Rolle's Theorem
- Lagrange's Mean Value Theorem (LMVT)
- Increasing and Decreasing Functions
- Maxima and Minima
- Overview of Applications of Derivatives
Indefinite Integration
Definite Integration
- Definite Integral as Limit of Sum
- Integral Calculus
- Methods of Evaluation and Properties of Definite Integral
- Overview of Definite Integration
Application of Definite Integration
- Application of Definite Integration
- Area Bounded by the Curve, Axis and Line
- Area Between Two Curves
- Overview of Application of Definite Integration
Differential Equations
- Differential Equations
- Order and Degree of a Differential Equation
- Formation of Differential Equations
- Homogeneous Differential Equations
- Linear Differential Equations
- Application of Differential Equations
- Solution of a Differential Equation
- Overview of Differential Equations
Probability Distributions
- Random Variables and Its Probability Distributions
- Types of Random Variables
- Probability Distribution of Discrete Random Variables
- Probability Distribution of a Continuous Random Variable
- Variance of a Random Variable
- Expected Value and Variance of a Random Variable
- Overview of Probability Distributions
Binomial Distribution
- Bernoulli Trial
- Binomial Distribution
- Mean of Binomial Distribution (P.M.F.)
- Variance of Binomial Distribution (P.M.F.)
- Bernoulli Trials and Binomial Distribution
- Overview of Binomial Distribution
Formula: Standard Functions
| y = f(x) | \[\frac{dy}{dx}=f^{\prime}(x)\] |
|---|---|
| c (Constant) | 0 |
| \[X^{n}\] | \[nx^{n-1}\] |
| \[\frac{1}{x}\] | \[-\frac{1}{x^2}\] |
| \[\frac{1}{x^n}\] | \[-\frac{n}{x^{n+1}}\] |
| \[\sqrt{x}\] | \[\frac{1}{2\sqrt{x}}\] |
| sin x | cos x |
| cos x | -sin x |
| tan x | sec2 x |
| cot x | -cosec2 x |
| sec x | sec x.tan x |
| cosec x | -cosec x cot x |
| \[e^{X}\] | \[e^{X}\] |
| \[a^{X}\] | \[a^xloga\] |
| log x | \[\frac{1}{x}\] |
| \[\log_{a}x\] | \[\frac{1}{x\log a}\] |
Formula: Rules of Differentiation
1. Sum Rule:
\[y=u\pm v\] then \[\frac{dy}{dx}=\frac{du}{dx}\pm\frac{dv}{dx}\]
2. Product Rule:
\[y=uv\] then \[\frac{dy}{dx}=u\frac{d\nu}{dx}+\nu\frac{du}{dx}\]
3. Quotient Rule:
\[y=\frac{u}{v}\] where v ≠ 0 then \[\frac{dy}{dx}=\frac{\nu\frac{du}{dx}-u\frac{d\nu}{dx}}{\nu^{2}}\]
4. Difference Rule:
y = u − v then \[\frac{dy}{dx}=\frac{du}{dx}-\frac{dv}{dx}\]
5. Constant Multiple:
y = k. u then \[\frac{dy}{dx}=k.\frac{du}{dx}\], k constant.
Formula: Composite Functions
| y | dy/dx |
|---|---|
| \[[f(x)]^{n}\] | \[n\left[f(x)\right]^{n-1}\cdot f^{\prime}(x)\] |
| \[\sqrt{f(x)}\] | \[\frac{f^{\prime}(x)}{2\sqrt{f(x)}}\] |
| \[\frac{1}{[f(x)]^{n}}\] | \[-\frac{n\cdot f^{\prime}(x)}{[f(x)]^{n+1}}\] |
| sin [f(x)] | \[\cos[f(x)]\cdot f^{\prime}(x)\] |
| cos [f(x)] | \[-\sin\left[f(x)\right]\cdot f^{\prime}(x)\] |
| tan [f(x)] | \[\sec^2[f(x)]\cdot f^{\prime}(x)\] |
| sec [f(x)] | \[\sec\left[f(x)\right]\cdot\tan\left[f(x)\right]\cdot f^{\prime}(x)\] |
| cot [f(x)] | \[-\operatorname{cosec}^2[f(x)]\cdot f^{\prime}(x)\] |
| cosec [f(x)] | \[-\operatorname{cosec}\left[f(x)\right]\cdot\cot\left[f(x)\right]\cdot f^{\prime}(x)\] |
| \[a^{f(x)}\] | \[a^{f(x)}\log a\cdot f^{\prime}(x)\] |
| \[e^{f(x)}\] | \[e^{f(x)}\cdot f^{\prime}(x)\] |
| log [f(x)] | \[\frac{f^\prime(x)}{f(x)}\] |
| \[\log_{a}[f(x)]\] | \[\frac{f^{\prime}(x)}{f(x)\log a}\] |
Formula: Inverse Trigonometric Functions
| y | dy/dx | Conditions |
|---|---|---|
| \[\sin^{-1}x\] | \[\frac{1}{\sqrt{1-x^2}},|x|<1\] | −1 ≤ x ≤ 1 \[-\frac{\pi}{2}\leq y\leq\frac{\pi}{2}\] |
| \[\cos^{-1}x\] | \[-\frac{1}{\sqrt{1-x^{2}}},|x|<1\] | −1 ≤ x ≤ 1 0 ≤ y ≤ π |
| \[\tan^{-1}x\] | \[\frac{1}{1+x^2}\] | x ∈ R \[-\frac{\pi}{2}<y<\frac{\pi}{2}\] |
| \[\cot^{-1}x\] | \[-\frac{1}{1+x^2}\] | x ∈ R 0 < y < π |
| \[\sec^{-1}x\] | \[\frac{1}{x\sqrt{x^{2}-1}}\quad\mathrm{for}x>1\] | 0 ≤ y ≤ π |
| \[-\frac{1}{x\sqrt{x^2-1}}\mathrm{~for~}x<-1\] | \[y\neq\frac{\pi}{2}\] | |
| \[cosec^{-1}x\] | \[-\frac{1}{x\sqrt{x^{2}-1}}\mathrm{for}x>1\] | \[-\frac{\pi}{2}\leq y\leq\frac{\pi}{2}\] |
| \[{\frac{1}{x{\sqrt{x^{2}-1}}}}\quad{\mathrm{for}}x<-1\] | \[y\neq0\] |
Formula: Logarithmic Differentiation
| Type of Function | Derivative |
|---|---|
| \[a^{x}\] | \[a^x\log a\] |
| \[e^{x}\] | \[e^{x}\] |
| \[x^{x}\] | \[x^x(1+\log x)\] |
| \[x^{a}\](a constant) | \[ax^{a-1}\] |
| \[a^{f(x)}\] | \[a^{f(x)}\log a\cdot f^{\prime}(x)\] |
Formula: Implicit Functions
General implicit form: F(x,y) = 0
\[x^my^n=(x+y)^{m+n}\]
\[\frac{dy}{dx}=\frac{y}{x}\]
| Expression | Derivative |
|---|---|
| \[y^{n}\] | \[ny^{n-1}\frac{dy}{dx}\] |
| f (y) | \[f^{\prime}(y)\frac{dy}{dx}\] |
| sin y | \[\cos y\frac{dy}{dx}\] |
| cos y | \[-\sin y\frac{dy}{dx}\] |
| \[e^{y}\] | \[e^y\frac{dy}{dx}\] |
| log y | \[\frac{1}{y}\frac{dy}{dx}\] |
Formula: Parametric Differentiation
| Given | Formula / Result |
|---|---|
| x = f(t), ; y = g(t) | Parametric form |
| First derivative | \[\frac{dy}{dx}=\frac{\frac{dy}{dt}}{\frac{dx}{dt}}\] |
| Condition | \[\frac{dx}{dt}\neq0\] |
| Second derivative | \[\frac{d^2y}{dx^2}=\frac{d}{dt}\left(\frac{dy}{dx}\right)/\frac{dx}{dt}\] |
Formula: Differentiation of One Function with Respect to Another
If: u = f(x),v = g(x)
Then: \[\frac{du}{dv}=\frac{du/dx}{dv/dx}\]
Definition: Higher Order Derivatives
If y = f(x) is a differentiable function of x, then its derivative f′(x) is also a function of x.
If this derivative f′(x) is again differentiable, its derivative is called the second derivative of f(x).
\[f^{\prime\prime}(x)\quad\mathrm{or}\quad\frac{d^2y}{dx^2}\]
If the second derivative is differentiable, its derivative is called the third derivative, denoted by:
\[f^{\prime\prime\prime}(x)\quad\mathrm{or}\quad\frac{d^3y}{dx^3}\]
Continuing this process, the derivative obtained after differentiating f(x) n times is called the nth derivative of f(x), and is denoted by:
\[f^{(n)}(x)\quad\mathrm{or}\quad\frac{d^ny}{dx^n}\]
These derivatives beyond the first derivative are called higher-order derivatives.
Definition: Derivative of a Composite Function
If y = f(u) is a differentiable function of u and u = g(x) is a differentiable function of x, then
\[\frac{dy}{dx}=\frac{dy}{du}\times\frac{du}{dx}\]
Definition: Derivative of an Inverse Function
If y = f(x) is a differentiable function of x such that the inverse function x = f − 1(y) exists, then x is a differentiable function of
y and
\[\frac{dx}{dy}=\frac{1}{\frac{dy}{dx}},\frac{dy}{dx}\neq0\]
Definition: Derivative of a Parametric Function
If x = f(t) and y = g(t) are differential functions of parameter ‘t’, then y is a differential function of x and
\[\begin{aligned}
\frac{dy}{dx} & =\frac{\frac{dy}{dt}}{\frac{dx}{dt}}, \\
\\
\frac{dx}{dt} & \neq0
\end{aligned}\]
Key Points: Applications of Derivative in Economics
1. Elasticity of Demand
\[\eta=-\frac{P}{D}\cdot\frac{dD}{dP}\]
2. Marginal Revenue & Elasticity Relation
\[R_m=R_A\left(1-\frac{1}{\eta}\right)\]
3. Propensity to Consume & Save
MPC + MPS = 1
APC + APS = 1
