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What is the difference between total differentiation and partial differentiation?
Wiki User
∙ 2009-12-16 11:33:52
Suppose, Z is a function of X and Y. In case of Partial Differentiation of Z with respect to X, all other variables, except X are treated as constants. But, total derivative pf z is given by,
dz=(partial derivative of z w.r.t x)dx + (partial derivative of z w.r.t y)dy
Wiki User
∙ 2009-12-16 11:33:52
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What is difference between partial differentiation and total differentiation of the function of two or more variables with example?
total differentiation is closer to implicit differentiation although you are not solving for dy/dx. in other words: the total derivative of f(x1,x2,...,xk) with respect to xn= [df(x1,x2,...,xk)/dx1][dx1/dxn] + df(x1,x2,...,xk)/dx2[dx2/dxn]+...+df(x1,x2,...,xk)/dxn +[df(x1,x2,...,xk)/dxn+1][dxn+1/dxn]+...+[df(x1,x2,...,xk)/dxk][dxk/dxn] however, the partial derivative is not this way. the partial derivative of f(x1,x2,...,xk) with respect to xn is just that, can't be expanded. The chain rule is not the same as total differentiation either. The chain rule is for partially differentiating f(x1,x2,...,xk) with respect to a variable not included in the explicit form. In other words, xn has to be considered a function of this variable for all integers n. so the total derivative is similar to the chain rule, but not the same.
What is difference between partial differentiation and total differentiation?
We use differentiation to find the rate at which a function changes as its input changes. This can give us information about the rate at which a physical process is occurring, or about how a physical quantity changes with position, for example. Partial differentiation gives us an extra facility: it is a way for us to find out about the change in a function that depends on more than one input. In real problems, physical quantities very commonly depend on more than one physical variable and we need to know how the quantity changes as we change any of these variables. For example, the sediment build-up on a river bed may be described by a function representing the thickness of the sediment. This function will depend on one or more spatial coordinates (i.e. whereabouts on the bed we look) and will also depend on time. That means we can ask two quite different questions about the sediment thickness: how rapidly does the sediment thickness change as we move over the bed, at any particular time, or how rapidly does the thickness change in time, at any particular point on the bed. Notice that these questions are about two totally different physical characteristics of the sediment build-up. The main point to remember about those two questions is the following. When we are concerned about how the thickness changes as we change one of the variables, we want to keep the other variable fixed. So if we look at different positions we do it at a particular time and if we're looking at different times we do it at a fixedposition. That idea is at the heart of the process of partial differentiation.
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What is difference between partial differentiation and total differentiation of the function of two or more variables with example?
total differentiation is closer to implicit differentiation although you are not solving for dy/dx. in other words: the total derivative of f(x1,x2,...,xk) with respect to xn= [df(x1,x2,...,xk)/dx1][dx1/dxn] + df(x1,x2,...,xk)/dx2[dx2/dxn]+...+df(x1,x2,...,xk)/dxn +[df(x1,x2,...,xk)/dxn+1][dxn+1/dxn]+...+[df(x1,x2,...,xk)/dxk][dxk/dxn] however, the partial derivative is not this way. the partial derivative of f(x1,x2,...,xk) with respect to xn is just that, can't be expanded. The chain rule is not the same as total differentiation either. The chain rule is for partially differentiating f(x1,x2,...,xk) with respect to a variable not included in the explicit form. In other words, xn has to be considered a function of this variable for all integers n. so the total derivative is similar to the chain rule, but not the same.
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