Derivative Calculator
Calculate the derivative of any function at a point using numerical methods. Supports polynomials, trig, exp, log. Includes power rule shortcut and common functions table.
Derivative f'(x) at x (numerical approx.)
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f(x) at point —
Second Derivative f''(x) at x (numerical approx.) —
Extended More scenarios, charts & detailed breakdown ▾
f'(x) central difference (numerical approx.)
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f'(x) forward difference —
Professional Full parameters & maximum detail ▾
Numerical Differentiation Methods
Forward difference f'(x) —
Backward difference f'(x) —
Central difference f'(x) (best) —
5-point stencil f'(x) —
Accuracy & Higher Order
Error estimate |central − 5pt| —
n-th derivative (numerical approx.) —
How to Use This Calculator
- Enter your function f(x) using standard notation (e.g.
x^2 + 3*x). - Enter the point x where you want the derivative.
- The central difference approximation f'(x) ≈ (f(x+h)−f(x−h))/(2h) is computed instantly.
- Use the Power Rule tab for exact polynomial derivatives.
- Use the Professional tab for 4-method comparison and higher-order derivatives.
Formula
Central difference: f'(x) ≈ (f(x+h) − f(x−h)) / (2h), h = 0.0001
Power rule (exact): d/dx[axⁿ] = a·n·xⁿ⁻¹
Example
f(x) = x², x = 3: f'(3) ≈ (9.0001² − 2.9999²)/(0.0002) = 6.0000 (exact: 2x = 6).
Frequently Asked Questions
- The derivative f'(x) of a function at a point x measures the instantaneous rate of change — how fast the function value is changing at exactly that point. Geometrically, it is the slope of the tangent line to the curve y = f(x) at x. For example, if f(x) = x², then f'(x) = 2x, and at x = 3 the slope of the tangent is 6. Derivatives are used to find velocity (derivative of position), marginal cost (derivative of total cost), and optimization (maximum/minimum occur where f'(x) = 0).
- This calculator uses the central difference formula: f'(x) ≈ (f(x+h) − f(x−h)) / (2h), where h is a small step size (default h = 0.0001). By evaluating the function at two points slightly to the left and right of x, it approximates the tangent slope. This method is accurate to about 8 significant figures for smooth functions — much better than the one-sided forward difference f(x+h)−f(x))/h, which has error proportional to h rather than h². Large h gives lower precision; too small h introduces floating-point cancellation errors.
- The power rule is the most fundamental differentiation rule: for f(x) = a·xⁿ, the derivative is f'(x) = a·n·xⁿ⁻¹. Examples: d/dx[3x²] = 6x, d/dx[5x³] = 15x², d/dx[x] = 1, d/dx[7] = 0 (constant). The Power Rule tab lets you enter a polynomial term and get the exact symbolic derivative. Combined with the sum rule (derivative of a sum equals sum of derivatives), you can differentiate any polynomial term by term.
- No — symbolic differentiation (producing formulas like 'd/dx[sin(x)] = cos(x)') requires a computer algebra system (CAS). This tool computes highly accurate numerical values of the derivative at a specific point. For exact symbolic results, use Wolfram Alpha (free, web-based), SymPy (Python library), or a CAS like Mathematica. However, the numerical approach is often all that is needed in practice — engineering and physics simulations routinely use numerical derivatives with excellent results.
- The second derivative f''(x) is the derivative of the derivative — it measures the rate of change of the slope, which describes concavity. If f''(x) > 0 at a point, the function is concave up (shaped like a U). If f''(x) < 0, it is concave down (shaped like an inverted U). The second derivative test: if f'(c) = 0 and f''(c) > 0, then c is a local minimum; if f''(c) < 0, it is a local maximum. The calculator computes f''(x) using a second application of the central difference formula.
Related Calculators
Sources & References (5) ▾
- Derivatives — Paul's Online Math Notes — Lamar University
- Differential Calculus — Khan Academy
- MIT OpenCourseWare 18.01 Single Variable Calculus — MIT
- Derivative — MathWorld — Wolfram MathWorld
- Numerical Differentiation — Wikipedia / Stewart's Calculus reference