
FunctionsReview81_84
... 13) For each equation pick five values of the domain, and solve for the range. Then graph the four points.(for and b pick 0, 2 positives, and 2 negatives) a) y = 2x – 5 ...
... 13) For each equation pick five values of the domain, and solve for the range. Then graph the four points.(for and b pick 0, 2 positives, and 2 negatives) a) y = 2x – 5 ...
3x y = 6
... We are going to solve one of the equations for either x or y – we must decide which will be easier: •The easiest thing to solve for is a variable without a coefficient (such as x in the 2nd equation ...
... We are going to solve one of the equations for either x or y – we must decide which will be easier: •The easiest thing to solve for is a variable without a coefficient (such as x in the 2nd equation ...
Section 4.1 Solving Systems of Linear Equations in 2 Variables
... 3. If the lines are parallel, there is no solution. (Inconsistent system) 4. If the lines are identical, there are infinitely many solutions. (Consistent with dependent equations) ...
... 3. If the lines are parallel, there is no solution. (Inconsistent system) 4. If the lines are identical, there are infinitely many solutions. (Consistent with dependent equations) ...
Partial differential equation

In mathematics, a partial differential equation (PDE) is a differential equation that contains unknown multivariable functions and their partial derivatives. (A special case are ordinary differential equations (ODEs), which deal with functions of a single variable and their derivatives.) PDEs are used to formulate problems involving functions of several variables, and are either solved by hand, or used to create a relevant computer model.PDEs can be used to describe a wide variety of phenomena such as sound, heat, electrostatics, electrodynamics, fluid flow, elasticity, or quantum mechanics. These seemingly distinct physical phenomena can be formalised similarly in terms of PDEs. Just as ordinary differential equations often model one-dimensional dynamical systems, partial differential equations often model multidimensional systems. PDEs find their generalisation in stochastic partial differential equations.