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The phrase "linear equation" takes its origin in this correspondence between lines and equations: a linear equation in two variables is an equation whose solutions form a line. If b ≠ 0 , the line is the graph of the function of x that has been defined in the preceding section.
A covering LP is a linear program of the form: Minimize: b T y, subject to: A T y ≥ c, y ≥ 0, such that the matrix A and the vectors b and c are non-negative. The dual of a covering LP is a packing LP, a linear program of the form: Maximize: c T x, subject to: Ax ≤ b, x ≥ 0, such that the matrix A and the vectors b and c are non-negative.
Simultaneous linear equation solver supports up to 4 variables; Polynomial equation solver supports up to 4th degree equations and inequalities; Engineering symbols display and entry previously found in MS / W / S / D-series calculators; Periodic table mode with atomic weight information (fx-JP900, fx-991CE X and fx-991RS X only) [7] Models:
The 42S, however, has a much smaller form factor than the 41, and features many more built-in functions, such as a matrix editor, complex number support, an equation solver, user-defined menus, and basic graphing capabilities (the 42S can draw graphs only by programs). Additionally, it features a two-line dot matrix display, which made stack ...
The transformation of a linear program to one in standard form may be accomplished as follows. [16] First, for each variable with a lower bound other than 0, a new variable is introduced representing the difference between the variable and bound. The original variable can then be eliminated by substitution. For example, given the constraint
Pearson's correlation coefficient is the covariance of the two variables divided by the product of their standard deviations. The form of the definition involves a "product moment", that is, the mean (the first moment about the origin) of the product of the mean-adjusted random variables; hence the modifier product-moment in the name.
Two linear systems using the same set of variables are equivalent if each of the equations in the second system can be derived algebraically from the equations in the first system, and vice versa. Two systems are equivalent if either both are inconsistent or each equation of each of them is a linear combination of the equations of the other one.
Matrices can be used to compactly write and work with multiple linear equations, that is, systems of linear equations. For example, if A is an m×n matrix, x designates a column vector (that is, n×1-matrix) of n variables x 1, x 2, ..., x n, and b is an m×1-column vector, then the matrix equation =