Calculus through Data & Modelling: Techniques of Integration

Calculus through Data & Modelling: Techniques of Integration course by Johns Hopkins University

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Created by Johns Hopkins University Staff Last updated Wed, 16-Mar-2022 English


Calculus through Data & Modelling: Techniques of Integration free videos and free material uploaded by Johns Hopkins University Staff .

Syllabus / What will i learn?

Module 1: Iterated Integrals

In this module, we extend the idea of a definite integral to double and even triple integrals of functions of two or three variables These ideas are then used to compute areas, volumes, and masses of more general regions Double integrals are also used to calculate probabilities when two random variables are involved This extension of single variable calculus is the first step towards major tools that arise later in this specialization involving theorems of vector calculus

Module 2: Double Integrals Over Plane Regions

For integrals of a function f(x), the region over which we integrate is always an interval of the real line But for double integrals, we want to expand our abilities to integrate a multivariable function f(x,y) not only over rectangles, but also over more general regions in the plane In this module, we develop the tools and techniques to do that

Vector Functions

A vector-valued function, also referred to as a vector function, is a mathematical function of one or more variables whose range is a set of multidimensional vectors or infinite-dimensional vectors The input of a vector-valued function could be a scalar or a vector, but the output of this function is a vector In this way, points are assigned to vectors In this module, we will study these new types of functions and develop examples and applications of these new mathematical objects They will play a key part in the development of vector calculus in future modules

Integration with Data

Despite the broad algebraic tools we have learned to find antiderivatives and evaluate definite integrals using the Fundamental Theorem of Calculus, there are times when using antiderivatives is not possible This could be because the function is too complicated in a way where no nice antiderivative exists, or that we are working with discrete data instead of a continuous function In this module we introduce the notions and algorithms of numerical integration, which allow us to estimate the values of definite integrals This is the basic problem we seek to solve: compute an approximate solution to a definite integral to a given degree of accuracy There are many methods for approximating the integral to the desired precision, and we introduce a few here



Curriculum for this course
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Description

In this course, we build on previously defined notions of the integral of a single-variable function over an interval Now, we will extend our understanding of integrals to work with functions of more than one variable First, we will learn how to integrate a real-valued multivariable function over different regions in the plane Then, we will introduce vector functions, which assigns a point to a vector This will prepare us for our final course in the specialization on vector calculus Finally, we will introduce techniques to approximate definite integrals when working with discrete data and through a peer reviewed project on, apply these techniques real world problems

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