Lecture

Implications of the Mean Value Theorem

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Description

This lecture discusses the implications of the mean value theorem, starting with remarks and a reformulation of the theorem, followed by immediate implications. The reformulation focuses on analyzing small intervals to compare values at different points within a given interval using the mean value theorem and derivative information. The lecture also explores how to restrict functions to sub-intervals while maintaining the properties of the original function. By introducing a new perspective on the theorem, the instructor demonstrates how to use derivative information to predict function values at specific points. The reformulation sets the stage for analyzing small intervals and introduces the concept of a 'small' increment in function values.

In MOOCs (2)

Analysis I (part 5): Continuous and derivable functions, the derivative function

This brings us to the heart of our discussion of functions: the concept of the derivability of a function. We are particularly interested in the question of the continuity of derived functions. We begin the chapter by completing the study of continuous functions by studying their properties on closed intervals. This enables us to define the maximum and minimum of continuous functions. We go on to define the bisection method, and demonstrate it. Introducing the concepts of maximum and minimum allows us to

Analysis I

This course covers : Part 1: Prelude, basic concepts, real numbers. Part 2: Introduction to complex numbers. Part 3: Real number sequences I and II. Part 4: Limit of a function, continuous functions. Part 5: Continuous functions and derivable functions, the derivative function. Part 6: Studies of functions, limited developments. Part 7: Indefinite and definite integrals, integration (selected chapters).

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Related concepts (11)

Derivative

In mathematics, the derivative shows the sensitivity of change of a function's output with respect to the input. Derivatives are a fundamental tool of calculus. For example, the derivative of the position of a moving object with respect to time is the object's velocity: this measures how quickly the position of the object changes when time advances. The derivative of a function of a single variable at a chosen input value, when it exists, is the slope of the tangent line to the graph of the function at that point.

Partial derivative

In mathematics, a partial derivative of a function of several variables is its derivative with respect to one of those variables, with the others held constant (as opposed to the total derivative, in which all variables are allowed to vary). Partial derivatives are used in vector calculus and differential geometry. The partial derivative of a function with respect to the variable is variously denoted by It can be thought of as the rate of change of the function in the -direction.

Total derivative

In mathematics, the total derivative of a function f at a point is the best linear approximation near this point of the function with respect to its arguments. Unlike partial derivatives, the total derivative approximates the function with respect to all of its arguments, not just a single one. In many situations, this is the same as considering all partial derivatives simultaneously. The term "total derivative" is primarily used when f is a function of several variables, because when f is a function of a single variable, the total derivative is the same as the ordinary derivative of the function.

Mean value theorem

In mathematics, the mean value theorem (or Lagrange theorem) states, roughly, that for a given planar arc between two endpoints, there is at least one point at which the tangent to the arc is parallel to the secant through its endpoints. It is one of the most important results in real analysis. This theorem is used to prove statements about a function on an interval starting from local hypotheses about derivatives at points of the interval.

Generalizations of the derivative

In mathematics, the derivative is a fundamental construction of differential calculus and admits many possible generalizations within the fields of mathematical analysis, combinatorics, algebra, geometry, etc. The Fréchet derivative defines the derivative for general normed vector spaces . Briefly, a function , an open subset of , is called Fréchet differentiable at if there exists a bounded linear operator such that Functions are defined as being differentiable in some open neighbourhood of , rather than at individual points, as not doing so tends to lead to many pathological counterexamples.

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