Derivative First Principles Simplified Revision Notes for SSCE HSC Mathematics Advanced
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Learn about Finding the derivative from first principles for your SSCE Mathematics Advanced Exam. This Revision Note includes a summary of Finding the derivative from first principles for easy recall in your Mathematics Advanced exam
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Derivative First Principles
Introduction
Limit: A limit in calculus signifies the value a function approaches as the input draws near a specific point. Limits are vital for deriving derivatives, which measure instantaneous rates of change. For example, imagine a car slowing gradually to a stop at traffic lights—its speed reducing to zero akin to a function approaching a limit.
Derivative: The gradient of the tangent line to the curve of a function at a specific point, serving as a bridge between algebra and geometry.
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Real-world Applications:
Derivatives are used to determine rates of change and to optimise systems in fields such as engineering and economics.
The Derivative Quotient
Formal Definition:
limh→0hf(x+h)−f(x)
Significance: Used to predict trends in graphs, model biological processes, and measure athletic acceleration.
Misconceptions about Limits:
Limits are dynamic entities, not static.
Example: Evaluate limx→2x−2x2−4, even though it is undefined at x=2.
chatImportant
Key Connection: A solid understanding of limits is essential for comprehending broader calculus topics such as continuity and integrals.
Finding Derivatives from First Principles
Utilise the limit definition of a derivative: limh→0hf(x+h)−f(x) to find the derivative of function: f(x)=x2.
Step-by-Step Derivation Example
Initial Setup:
Expression: f(x+h)=(x+h)2.
Expand & Simplify:
Expand: (x+h)2=x2+2xh+h2.
Simplify: h(x2+2xh+h2)−x2=h2xh+h2=2x+h.
Apply the Limit:
Result: f′(x)=limh→0(2x+h)=2x.
chatImportant
Pitfalls to Avoid:
Missteps in expansion or limit application.
Verify each step of your calculation thoroughly.
Numerical and Graphical Illustrations
Numerical
Approach: Numerical calculations of hf(x+h)−f(x) become more accurate as h decreases, providing improved approximations.
Graphical
Visualise: Secant lines gradually converge to tangent lines as h→0.
Numerical Estimation
Numerical Methods: Provide approximations for derivatives when analytical solutions are not feasible.
Finite Difference Methods:
Forward: f′(x)≈hf(x+h)−f(x).
Backward: f′(x)≈hf(x)−f(x−h).
Central: f′(x)≈2hf(x+h)−f(x−h).
Error Analysis
Types:
Truncation errors arise from approximations.
Round-off errors result from the finite precision of computing.
Mitigation: Careful selection of interval sizes and strategic error reduction methods.
Practice Problems with Solutions
Problem 1: Derive f(x)=x3 from first principles. Solution:
Begin with the definition: f′(x)=limh→0hf(x+h)−f(x)
Problem 2: Use the limit definition to derive f(x)=x1.
Solution:
Begin with the definition: f′(x)=limh→0hf(x+h)−f(x)
Substitute f(x)=x1: f′(x)=limh→0hx+h1−x1
Find a common denominator: f′(x)=limh→0hx(x+h)x−(x+h)=limh→0hx(x+h)−h
Simplify: f′(x)=limh→0x(x+h)−1=x2−1
Therefore, f′(x)=−x21
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