In particular, the time derivatives of an object's position are significant in Newtonian physics:. A differential equation is a relation between a collection of functions and their derivatives. An ordinary differential equation is a differential equation that relates functions of one variable to their derivatives with respect to that variable.

A partial differential equation is a differential equation that relates functions of more than one variable to their partial derivatives. Differential equations arise naturally in the physical sciences, in mathematical modelling, and within mathematics itself.

For example, Newton's second law , which describes the relationship between acceleration and force, can be stated as the ordinary differential equation. The heat equation in one space variable, which describes how heat diffuses through a straight rod, is the partial differential equation. The mean value theorem gives a relationship between values of the derivative and values of the original function. In practice, what the mean value theorem does is control a function in terms of its derivative.

For instance, suppose that f has derivative equal to zero at each point. This means that its tangent line is horizontal at every point, so the function should also be horizontal. The mean value theorem proves that this must be true: The slope between any two points on the graph of f must equal the slope of one of the tangent lines of f. All of those slopes are zero, so any line from one point on the graph to another point will also have slope zero.

But that says that the function does not move up or down, so it must be a horizontal line. More complicated conditions on the derivative lead to less precise but still highly useful information about the original function. The derivative gives the best possible linear approximation of a function at a given point, but this can be very different from the original function.

One way of improving the approximation is to take a quadratic approximation. For each one of these polynomials, there should be a best possible choice of coefficients a , b , c , and d that makes the approximation as good as possible.


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In the neighbourhood of x 0 , for a the best possible choice is always f x 0 , and for b the best possible choice is always f' x 0. For c , d , and higher-degree coefficients, these coefficients are determined by higher derivatives of f. Using these coefficients gives the Taylor polynomial of f. The Taylor polynomial of degree d is the polynomial of degree d which best approximates f , and its coefficients can be found by a generalization of the above formulas. Taylor's theorem gives a precise bound on how good the approximation is. If f is a polynomial of degree less than or equal to d , then the Taylor polynomial of degree d equals f.

The limit of the Taylor polynomials is an infinite series called the Taylor series. The Taylor series is frequently a very good approximation to the original function. Functions which are equal to their Taylor series are called analytic functions. It is impossible for functions with discontinuities or sharp corners to be analytic, but there are smooth functions which are not analytic.

Some natural geometric shapes, such as circles , cannot be drawn as the graph of a function.


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This set is called the zero set of f. It is not the same as the graph of f , which is a paraboloid. It states that if f is continuously differentiable , then around most points, the zero set of f looks like graphs of functions pasted together. The points where this is not true are determined by a condition on the derivative of f. The implicit function theorem is closely related to the inverse function theorem , which states when a function looks like graphs of invertible functions pasted together.

A Gentle Introduction To Learning Calculus – BetterExplained

From Wikipedia, the free encyclopedia. Limits of functions Continuity. Mean value theorem Rolle's theorem. Differentiation notation Second derivative Third derivative Change of variables Implicit differentiation Related rates Taylor's theorem.

Differential Calculus

Fractional Malliavin Stochastic Variations. Taylor polynomial and Taylor series. Differential calculus at Wikipedia's sister projects. However, Leibniz published his first paper in , predating Newton's publication in It is possible that Leibniz saw drafts of Newton's work in or , or that Newton made use of Leibniz's work to refine his own. Both Newton and Leibniz claimed that the other plagiarized their respective works. This resulted in a bitter Newton Leibniz calculus controversy between the two men over who first invented calculus which shook the mathematical community in the early 18th century.

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In other projects Wikimedia Commons Wikiquote. This page was last edited on 21 November , at By using this site, you agree to the Terms of Use and Privacy Policy. Fundamental theorem Limits of functions Continuity Mean value theorem Rolle's theorem. Integral Lists of integrals.

Specialized Fractional Malliavin Stochastic Variations. Differentiating polynomials Opens a modal. Tangents of polynomials Opens a modal. Differentiating polynomials review Opens a modal. Rational functions differentiation intro. Differentiating integer powers mixed positive and negative Opens a modal. Radical functions differentiation intro. Fractional powers differentiation Opens a modal. Radical functions differentiation intro Opens a modal.

Partial derivatives, introduction

Power rule review Opens a modal. Power rule with rewriting the expression. Differentiate integer powers mixed positive and negative. Derivatives of sin x and cos x Opens a modal. Derivatives of sin x and cos x.