Topics
Mathematical Logic
- Statements and Truth Values in Mathematical Logic
- Logical Connectives
- Tautology, Contradiction, and Contingency
- Quantifier, Quantified and Duality 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
Trigonometric Functions
Pair of Straight Lines
Vectors
Line and Plane
Linear Programming
Differentiation
- Introduction & Derivatives of Some Standard Functions
- Derivatives of Composite Functions
- Geometrical Meaning of Derivative
- Derivative of Inverse Function
- Logarithmic Differentiation
- Derivative of Implicit Functions
- Derivatives of Functions in Parametric Forms
- 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 Two Curves
- Overview of Application of Definite Integration
Differential Equations
- Basic Concepts of Differential Equations
- Order and Degree of a Differential Equation
- Formation of Differential Equations
- Methods of Solving Differential Equations> Homogeneous Differential Equations
- Methods of Solving Differential Equations>Linear Differential Equations
- Applications of Differential Equation
- Solution of a Differential Equation
- Overview of Differential Equations
Probability Distributions
- 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
Definition: Parametric Form
When x = f(t) and y = g(t), the relation between x and y is said to be in parametric form.
Stepwise Method
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Write the given equations in parametric form: x = f(t), y = g(t).
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Find \[\frac{dx}{dt}\] and \[\frac{dy}{dt}\] separately.
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Use the formula \[\frac{dy}{dx} = \frac{dy/dt}{dx/dt}\].
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Simplify the answer carefully.
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If required, express the final answer in terms of x and y instead of the parameter.
Example 1
Find \[\frac{dy}{dx}\], if \[x^{\frac{2}{3}} + y^{\frac{2}{3}} = a^{\frac{2}{3}}\].
Solution: Let \[x = a \cos^3 \theta, y = a \sin^3 \theta\]. Then
Hence, \[x = a \cos^3 \theta, y = a \sin^3 \theta\] is parametric equation of \[x^{\frac{2}{3}} + y^{\frac{2}{3}} = a^{\frac{2}{3}}\]
Now \[\frac{dx}{d\theta} = - 3a \cos^2 \theta \sin \theta \text{ and } \frac{dy}{d\theta} = 3a \sin^2 \theta \cos \theta\]
Therefore \[\frac{dy}{dx} = \frac{\frac{dy}{d\theta}}{\frac{dx}{d\theta}} = \frac{3a \sin^2 \theta \cos \theta}{-3a \cos^2 \theta \sin \theta} = -\tan \theta = -\sqrt[3]{\frac{y}{x}}\]
Maharashtra State Board: Class 12
Key Points: Derivative of Parametric Functions
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Parametric form means both x and y are written in terms of a third variable.
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The third variable is called the parameter.
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The main formula is:
\[\frac{dy}{dx} = \frac{\frac{dy}{dt}}{\frac{dx}{dt}}\] -
This formula is based on the chain rule.
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Always check that \[\frac{dx}{dt} \neq 0\].
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The final answer may remain in terms of the parameter unless the question asks for conversion.
