∂z/∂x

Definition

∂z/∂x, read as 'partial derivative of z with respect to x,' represents the rate of change of the function z with respect to the variable x, while holding all other variables constant. It is a fundamental concept in the study of functions of several variables.

5 Must Know Facts For Your Next Test

1. The partial derivative ∂z/∂x measures the instantaneous rate of change of the function z with respect to x, while holding all other variables constant.
2. Partial derivatives are essential in optimization problems involving functions of several variables, as they help identify critical points and determine the direction of maximum increase or decrease.
3. The partial derivative ∂z/∂x can be interpreted geometrically as the slope of the tangent plane to the surface z = f(x, y) at a given point (x, y, z).
4. Partial derivatives are used to construct the gradient vector, which points in the direction of the greatest rate of increase of the function.
5. The concept of partial derivatives is foundational in the study of multivariable calculus and is applied in various fields, such as physics, engineering, and economics.

Review Questions

• Explain the meaning and significance of the partial derivative ∂z/∂x in the context of functions of several variables.
  • The partial derivative ∂z/∂x represents the rate of change of the function z with respect to the variable x, while holding all other variables constant. This is a crucial concept in the study of functions of several variables, as it allows us to analyze the behavior of a function along a specific direction, independent of the other variables. The partial derivative ∂z/∂x is essential for optimization problems, as it helps identify critical points and determine the direction of maximum increase or decrease of the function. Geometrically, ∂z/∂x can be interpreted as the slope of the tangent plane to the surface z = f(x, y) at a given point (x, y, z).
• Describe how the partial derivative ∂z/∂x is used to construct the gradient vector of a function of several variables.
  • The gradient of a function of several variables is the vector of all its partial derivatives. In the case of a function z = f(x, y), the gradient is given by the vector $\nabla f = \left(\frac{\partial f}{\partial x}, \frac{\partial f}{\partial y}\right)$. The partial derivative ∂z/∂x is one component of this gradient vector, representing the rate of change of the function z with respect to the variable x. The gradient vector points in the direction of the greatest rate of increase of the function, and its magnitude is the maximum rate of change. Understanding the properties of the gradient vector, which incorporates the partial derivative ∂z/∂x, is crucial for optimization and analysis of functions of several variables.
• Explain how the concept of the partial derivative ∂z/∂x is applied in various fields, such as physics, engineering, and economics.
  • The concept of the partial derivative ∂z/∂x is widely applied across different disciplines. In physics, partial derivatives are used to describe the behavior of physical quantities, such as the rate of change of temperature with respect to position in heat transfer problems, or the rate of change of pressure with respect to volume in thermodynamics. In engineering, partial derivatives are employed in the analysis of multivariable systems, such as the optimization of design parameters or the study of the sensitivity of a system's output to changes in its inputs. In economics, partial derivatives are used to analyze the behavior of economic variables, such as the rate of change of a firm's profit with respect to the price of a good or the rate of change of a consumer's utility with respect to the quantity of a commodity. The versatility of the partial derivative ∂z/∂x makes it a fundamental tool in the study and analysis of complex systems across various fields.

Related terms

Partial Derivative: A partial derivative is the derivative of a function of several variables with respect to one of its variables, treating the other variables as constants.

Gradient: The gradient of a function of several variables is the vector of all its partial derivatives, and it represents the direction and rate of change of the function at a given point.

Total Derivative: The total derivative of a function of several variables is the sum of the products of each partial derivative and the corresponding differential of the respective variable.