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In Mathematics simultaneous equations are a set of equations containing multiple variables. This set is often referred to as a system of equations. To solve simultaneous equations, the solver needs to use the provided equations to find the exact value of each variable. Generally the solver uses either a graphical method (by plotting all the lines and/or curves on the same graph and finding the exact coordinates of their intersection), the matrix method, the substitution method, and/or the elimination method. Some textbooks refer to the elimination method as the addition method, since it involves adding equations (or constant multiples of the said equations) to one another, as detailed later in this article. For other meanings of mathematics or uses of math and maths, see Mathematics (disambiguation) and Math (disambiguation). ... An equation is a mathematical statement, in symbols, that two things are the same (or equivalent). ...

This is a set of linear equations, also known as a linear system of equations: A linear equation in algebra is an equation which is constructed by equating two linear functions. ... In mathematics and linear algebra, a system of linear equations is a set of linear equations such as A standard problem is to decide if any assignment of values for the unknowns can satisfy all three equations simultaneously, and to find such an assignment if it exists. ...

Solving this involves subtracting x + y = 6 from 2x + y = 8 (using the elimination method) to remove the y-variable, then simplifying the resulting equation to find the value of x, then substituting the x-value into either equation to find y.

The solution of this system is:

which can also be written as an ordered pair (2, 4), representing on a graph the coordinates of the point of intersection of the two lines represented by the equations. Coordinates are numbers which describe the location of points in a plane or in space. ...

Finding solutions

If there are fewer independent equations than variables, not all variables can be solved for, and so an answer for at least one variable must be expressed in terms of other variables. In general, to solve a system exactly, at least one equation is needed for each unknown variable that needs to be solved for. If the number of independent equations is the same as the number of variables, then potentially the system can be exactly solvable, but does not have to be. This frequently occurs in linear systems if one equation is a simple multiple of the other (representing the same line, e.g. 2x + y = 3 and 4x + 2y = 6) or if the ratio of like variables in two linear equations is the same (representing parallel lines, e.g. 2x + y = 3 and 6x + 3y = 7 where the ratio of comparable letters is 3). Because of the importance of this, a phrase in the form "E equations, U unknowns" (for example "2 equations, 3 unknowns" or "4 equations, 4 unknowns") is often used to describe systems of equations. If E = U or E < U, then usually the system has solutions - usually finite when E = U. If, however, E > U, the system usually has no solutions.

Systems of two equations in two real-value unknowns usually appear as one of five different types, having a relationship to the number of solutions:

1. Systems that represent intersecting sets of points such as lines and curves, and that are not of one of the types below. This can be considered the normal type, the others being exceptional in some respect. These systems usually have a finite number of solutions, each formed by the coordinates of one point of intersection.
2. Systems that simplify down to false (for example, equations such as 1 = 0). Such systems have no points of intersection and no solutions. This type is found, for example, when the equations represent parallel lines.
3. Systems in which both equations simplify down to an identity (for example, x = 2x − x and 0y = 0). Any assignment of values to the unknown variables satisfies the equations. Thus, there are an infinite number of solutions: all points of the plane.
4. Systems in which the two equations represent the same set of points: they are mathematically equivalent (one equation can typically be transformed into the other through algebraic manipulation). Such systems represent completely overlapping lines, or curves, etc. One of the two equations is redundant and can be discarded. Each point of the set of points corresponds to a solution. Usually, this means there are an infinite number of solutions.
5. Systems in which one (and only one) of the two equations simplifies down to an identity. It is therefore redundant, and can be discarded, as per the previous type. Each point of the set of points represented by the other equation is a solution of which there are then usually an infinite number.

The equation x² + y² = 0 can be thought of as the equation of a circle whose radius has shrunk to zero, and so it represents a single point: (x = 0, y = 0), unlike a normal circle containing an infinity of points. This and similar examples show the reason why the last two types described above need the qualification "usually". An example of a system of equations of the first type described above with an infinite number of solutions is given by x = |x|, y = |y| (where the notation |•| denotes the absolute value function), whose solutions form a quadrant of the x-y plane. Another example is x = |y|, y = |x|, whose solution represents a ray. In mathematics, the absolute value (or modulus[1]) of a real number is its numerical value without regard to its sign. ... Fig. ... Line redirects here. ...

Substitution method

The two example equations intersect twice. Therefore, there are two solutions.

Systems of simultaneous equations can be hard to solve unless a systematic approach is used. A common technique is the substitution method: Find an equation that can be rearranged for one variable, that is, it can be rewritten in the form 〈VARIABLE〉 = 〈EXPRESSION〉, in which the left-hand side variable does not occur in the right-hand side expression. Next, substitute that expression where that variable appears in the other equations, thereby obtaining a smaller system with fewer variables. After that smaller system has been solved (whether by further application of the substitution method or by other methods), substitute the solutions found for the variables in the above right-hand side expression. Image File history File links Simultaneous_equations_example_1. ... Image File history File links Simultaneous_equations_example_1. ... An equation is a mathematical statement, in symbols, that two things are the same (or equivalent). ... Look up substitution in Wiktionary, the free dictionary. ...

In this set of equations

we first make x the subject of the second equation:

and substitute this result into the first equation:

After simplification, this yields the solutions

and by substituting this in x = −2y we obtain the corresponding x values. We now have the two solutions of our system of equations:

Elimination method

Elimination by judicious multiplication is the other commonly used method to solve simultaneous linear equations. It uses the general principles that each side of an equation still equals the other when both sides are multiplied (or divided) by the same quantity, or when the same quantity is added (or subtracted) from both sides. In multiplication/division, a factor is chosen so that when both sides have equivalent quantities added from another equation in the system (that is, the equations are added), one or more of the variables disappear, the resulting equations are still valid representations in the system, and their smaller number of remaining unknowns thus makes the system of equations easier to solve. As the equations grow simpler through the elimination of some variables, a variable will eventually appear in fully solvable form, and this value can then be "back-substituted" into previously derived equations by plugging this value in for the variable. Typically, each "back-substitution" can then allow another variable in the system to be solved.

Matrices

Systems of equations may also be represented in terms of matrices, allowing various principles of matrix operations to be handily applied to the problem. Systems of simultaneous linear equations are studied in linear algebra and can always be solved; one uses Gaussian elimination or the Cholesky decomposition. To determine approximate solutions to general systems numerically on a computer, the n-dimensional Newton's method may be used. Algebraic geometry is essentially the theory of simultaneous polynomial equations. The question of effective computation with such equations belongs to elimination theory. See also Cramer's Rule, which computes the quotient of 2 determinants to calculate the solution. In mathematics and linear algebra, a system of linear equations is a set of linear equations such as A standard problem is to decide if any assignment of values for the unknowns can satisfy all three equations simultaneously, and to find such an assignment if it exists. ... Linear algebra is the branch of mathematics concerned with the study of vectors, vector spaces (also called linear spaces), linear maps (also called linear transformations), and systems of linear equations. ... In linear algebra, Gaussian elimination is an algorithm that can be used to determine the solutions of a system of linear equations, to find the rank of a matrix, and to calculate the inverse of an invertible square matrix. ... In mathematics, the Cholesky decomposition, named after André-Louis Cholesky, is a matrix decomposition of a symmetric positive-definite matrix into a lower triangular matrix and the transpose of the lower triangular matrix. ... Numerical analysis is the study of approximate methods for the problems of continuous mathematics (as distinguished from discrete mathematics). ... In numerical analysis, Newtons method (also known as the Newton–Raphson method or the Newton–Fourier method) is an efficient algorithm for finding approximations to the zeros (or roots) of a real-valued function. ... Algebraic geometry is a branch of mathematics which, as the name suggests, combines techniques of abstract algebra, especially commutative algebra, with the language and the problematics of geometry. ... In mathematics, a polynomial is an expression that is constructed from one variable or more variables and constants, using only the operations of addition, subtraction, multiplication, and constant positive whole number exponents. ... In algebraic geometry, elimination theory is the classical name for algorithmic approaches to eliminating between polynomials of several variables. ...

Simultaneous equation models are a form of statistical model in the form of a set of linear simultaneous equations. They are often used in econometrics. Simultaneous equation models are a form of statistical model in the form of a set of linear simultaneous equations. ... A statistical model is used in applied statistics. ... Econometrics is concerned with the tasks of developing and applying quantitative or statistical methods to the study and elucidation of economic principles. ...

In modular arithmetic, simple systems of simultaneous congruences can be solved by the method of successive substitution. Modular arithmetic (sometimes called modulo arithmetic, or clock arithmetic because of its use in the 24-hour clock system) is a system of arithmetic for integers, where numbers wrap around after they reach a certain value — the modulus. ... In modular arithmetic, the method of successive substitution is a method of solving problems of simultaneous congruences by using the definition of the congruence equation. ...