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It is the study of how to apply calculus to functions of more then 1 variable. It allows us to do the same things we could in two dementions in n dementions. It is closely related to linear algebra.

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Q: What is multivariable calculus?
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How is multivariable calculus useful?

I am assuming you understand the distinction between single-variable calculus (calculus of one variable) and multivariable calculus (calculus of several variables). Well, if you know the former, that is highly beneficial because the same techniques are used in the latter -- they are generalized to apply to calculus of n-variables. This is ultimately the goal of single-variable calculus. Why? Well, if you think about it, single-variable is not really applicable. Not many real world phenomena involve one variable. For example, in macroeconomics, GDP = Y is a function of many variables: Consumption (a function of net taxes and income), Investment (a function of real interest rates), Government Spending, and Net Exports. That is, Y=f(C(Y,T), I(r), G, NX). To perform many of the tools of calculus (e.g. finding how Y changes as G increases) to this function, one must know and apply multivariable calculus.


What is the formula for functions?

Assume you want to know what is the formula of the gradient of the function in multivariable calculus. Let F be a scalar field function in n-dimension. Then, the gradient of a function is: ∇F = <fx1 , fx2, ... , fxn> In the 3-dimensional Cartesian space: ∇F = <fx, fy, fz>


What is a gradient function?

Assume you want to know what is the formula of the gradient of the function in multivariable calculus. Let F be a scalar field function in n-dimension. Then, the gradient of a function is: ∇F = <fx1 , fx2, ... , fxn> In the 3-dimensional Cartesian space: ∇F = <fx, fy, fz>


What is the formula of gradient?

Assume you want to know what is the formula of the gradient of the function in multivariable calculus. Let F be a scalar field function in n-dimension. Then, the gradient of a function is: ∇F = <fx1 , fx2, ... , fxn> In the 3-dimensional Cartesian space: ∇F = <fx, fy, fz>


How do you solve multivariable equations?

You need as many equations as you have variables.

Related questions

What has the author Lawrence J Corwin written?

Lawrence J. Corwin has written: 'Multivariable calculus' -- subject(s): Calculus


When do you normally take multivariable calculus?

It is usually the third class in the calculus series ,so it is often taken in the second or third semester.


How is multivariable calculus useful?

I am assuming you understand the distinction between single-variable calculus (calculus of one variable) and multivariable calculus (calculus of several variables). Well, if you know the former, that is highly beneficial because the same techniques are used in the latter -- they are generalized to apply to calculus of n-variables. This is ultimately the goal of single-variable calculus. Why? Well, if you think about it, single-variable is not really applicable. Not many real world phenomena involve one variable. For example, in macroeconomics, GDP = Y is a function of many variables: Consumption (a function of net taxes and income), Investment (a function of real interest rates), Government Spending, and Net Exports. That is, Y=f(C(Y,T), I(r), G, NX). To perform many of the tools of calculus (e.g. finding how Y changes as G increases) to this function, one must know and apply multivariable calculus.


What has the author Thomas H Barr written?

Thomas H. Barr has written: 'Vector calculus' -- subject(s): Vector analysis 'Naval Warfare Analysis Experiment' -- subject(s): Management 'Multivariable calculus'


Is multivariable calculus hard?

That is not an easy question to answer. Many people find math hard in general and certainly some people find calculus hard to understand.Multivariable calculus is not really harder than single variable calculus. It is lots of fun since you learn about double and triple integrals, partial derivatives and lots more.I strongly suggest it for anyone who is thinking about taking it.


What has the author Donald W Trim written?

Donald W. Trim has written: 'Multivariable Calculus' 'Introduction to complex analysis and its applications' -- subject(s): Mathematical analysis, Functions of complex variables


What math level is after calculus?

Once you've completed differential and integral calculus, multivariable calculus is often next step, and beyond that there is advanced calculus which generalizes calc to multidimensional spaces and uses vector-valued functions. Often concurrent with high level calculus in college courses is linear algebra and differential equations. There's nothing really 'after' calculus, because any topic in mathematics has a myriad of problems, theories, and potential applications to be explored. Calculus is, however, normally the highest level of math taught in US high schools and is a basic required course for any science/engineering major in college.


What is the formula for gradient?

Assume you want to know what is the formula of the gradient of the function in multivariable calculus. Let F be a scalar field function in n-dimension. Then, the gradient of a function is: ∇F = <fx1 , fx2, ... , fxn> In the 3-dimensional Cartesian space: ∇F = <fx, fy, fz>


What is gradient formula?

Assume you want to know what is the formula of the gradient of the function in multivariable calculus. Let F be a scalar field function in n-dimension. Then, the gradient of a function is: ∇F = <fx1 , fx2, ... , fxn> In the 3-dimensional Cartesian space: ∇F = <fx, fy, fz>


What is the formula for functions?

Assume you want to know what is the formula of the gradient of the function in multivariable calculus. Let F be a scalar field function in n-dimension. Then, the gradient of a function is: ∇F = <fx1 , fx2, ... , fxn> In the 3-dimensional Cartesian space: ∇F = <fx, fy, fz>


What is a gradient function?

Assume you want to know what is the formula of the gradient of the function in multivariable calculus. Let F be a scalar field function in n-dimension. Then, the gradient of a function is: ∇F = <fx1 , fx2, ... , fxn> In the 3-dimensional Cartesian space: ∇F = <fx, fy, fz>


What is the formula of gradient?

Assume you want to know what is the formula of the gradient of the function in multivariable calculus. Let F be a scalar field function in n-dimension. Then, the gradient of a function is: ∇F = <fx1 , fx2, ... , fxn> In the 3-dimensional Cartesian space: ∇F = <fx, fy, fz>