11.8 Solving Systems with Cramer's Rule

3 min readjune 24, 2024

Determinants and are powerful tools for solving systems of linear equations. They provide a systematic approach to finding solutions by calculating scalar values from elements and using them in specific formulas.

These methods are particularly useful for smaller systems, offering a straightforward way to solve equations without the need for complex row operations. Understanding determinants and Cramer's Rule builds a strong foundation for more advanced concepts.

Determinants and Cramer's Rule

Calculation of matrix determinants

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  • is a scalar value computed from the elements of a square matrix
  • 2x2 matrix formula: abcd=adbc\begin{vmatrix}a & b \\ c & d\end{vmatrix} = ad - bc
  • 3x3 matrix determinant can be calculated using the "" or ""
    • Sum the products of elements along the main diagonal and two parallel diagonals (top-left to bottom-right)
    • Subtract the products of elements along the other three diagonals (top-right to bottom-left)
    • Formula: abcdefghi=a(eifh)b(difg)+c(dheg)\begin{vmatrix}a & b & c \\ d & e & f \\ g & h & i\end{vmatrix} = a(ei - fh) - b(di - fg) + c(dh - eg)
  • Determinants play a crucial role in solving systems of linear equations using Cramer's Rule

Application of Cramer's Rule

  • Cramer's Rule is a method for solving systems of linear equations (also known as ) using determinants
  • For a system of two equations with two variables: a1x+b1y=c1a_1x + b_1y = c_1 and a2x+b2y=c2a_2x + b_2y = c_2
    • Solution: x=DxDx = \frac{D_x}{D} and y=DyDy = \frac{D_y}{D}
    • DD: determinant of the a1b1a2b2\begin{vmatrix}a_1 & b_1 \\ a_2 & b_2\end{vmatrix}
    • DxD_x: determinant of the matrix replacing the coefficients of xx with the constants c1b1c2b2\begin{vmatrix}c_1 & b_1 \\ c_2 & b_2\end{vmatrix}
    • DyD_y: determinant of the matrix replacing the coefficients of yy with the constants a1c1a2c2\begin{vmatrix}a_1 & c_1 \\ a_2 & c_2\end{vmatrix}
  • Cramer's Rule provides a straightforward approach to solve systems of linear equations
  • It can be used to find a when one exists

Extension to three-variable systems

  • Cramer's Rule can be extended to solve systems of three equations with three variables
  • For a system: a1x+b1y+c1z=d1a_1x + b_1y + c_1z = d_1, a2x+b2y+c2z=d2a_2x + b_2y + c_2z = d_2, and a3x+b3y+c3z=d3a_3x + b_3y + c_3z = d_3
    • Solution: x=DxDx = \frac{D_x}{D}, y=DyDy = \frac{D_y}{D}, and z=DzDz = \frac{D_z}{D}
    • DD: determinant of the a1b1c1a2b2c2a3b3c3\begin{vmatrix}a_1 & b_1 & c_1 \\ a_2 & b_2 & c_2 \\ a_3 & b_3 & c_3\end{vmatrix}
    • DxD_x, DyD_y, DzD_z: determinants of the matrices formed by replacing the coefficients of xx, yy, and zz with the constants, respectively
  • The process remains similar to the two-variable case, with the addition of a third variable and a larger determinant calculation

Properties of determinants

  • Interchanging any two rows or columns of a matrix changes the sign of the determinant
  • If any two rows or columns of a matrix are identical, the determinant is zero
  • Multiplying a row or column by a scalar multiplies the determinant by the same scalar
  • Adding a multiple of one row or column to another does not change the determinant
  • These properties can simplify determinant calculations and improve problem-solving efficiency (row reduction)

Cramer's Rule vs other methods

  • Cramer's Rule is straightforward but may be less efficient for large systems
  • transforms the into through row operations
    • More efficient for larger systems
  • solves multiple systems with the same matrix but different constant vectors
    • Efficient when solving many systems with the same coefficients
  • Method choice depends on system size, nature, and problem context (computational complexity, numerical stability)

System of Equations and Solutions

  • A consists of two or more equations with multiple variables
  • Solutions to systems of equations can be classified as:
    • Unique solution: The system has exactly one solution (determined by Cramer's Rule when the determinant is non-zero)
    • : The system has no solution (occurs when equations contradict each other)
    • : The system has infinitely many solutions (happens when equations are equivalent or redundant)
  • These concepts are fundamental in linear algebra and help determine the nature of solutions for various systems of equations

Key Terms to Review (39)

2x2 System: A 2x2 system refers to a system of two linear equations with two variables, typically represented in the form of a 2x2 matrix. These systems are commonly solved using various methods, including Cramer's Rule, which is the focus of the given topic.
3x3 System: A 3x3 system refers to a system of three linear equations with three unknowns, where the coefficients of the variables form a 3x3 matrix. These types of systems are commonly solved using techniques such as Cramer's Rule, which involves calculating determinants to find the unique solution.
Augmented matrix: An augmented matrix is a matrix that represents a system of linear equations, including both the coefficients and the constants from the equations. It combines the coefficient matrix and the constant vector into one larger matrix for easier manipulation and solution.
Augmented Matrix: An augmented matrix is a special type of matrix that is used to represent a system of linear equations. It is formed by combining the coefficient matrix of the system with the column of constants on the right-hand side of the equations.
Binomial coefficient: A binomial coefficient is a coefficient of any of the terms in the expansion of a binomial raised to a power, typically written as $\binom{n}{k}$ or $C(n,k)$. It represents the number of ways to choose $k$ elements from a set of $n$ elements without regard to order.
Coefficient: A coefficient is a numerical factor that multiplies a variable in an algebraic expression. It represents the magnitude or strength of the relationship between the variable and the overall expression. Coefficients are essential in various mathematical contexts, including polynomial factorization, linear equations, quadratic equations, and the graphing of polynomial functions.
Coefficient matrix: A coefficient matrix is a rectangular array that contains only the coefficients of the variables in a system of linear equations. It is used to facilitate methods such as Gaussian Elimination and finding matrix inverses.
Coefficient Matrix: A coefficient matrix, also known as the coefficient array, is a matrix that contains the coefficients of the variables in a system of linear equations. It is a crucial component in the analysis and solution of systems of linear equations, as it provides a compact and organized representation of the coefficients that define the relationships between the variables.
Cofactor: A cofactor is a non-protein chemical compound or metallic ion that is required for an enzyme to function properly. It is an essential component that assists the enzyme in catalyzing specific biochemical reactions within the body.
Constant Term: The constant term is a numerical value in a polynomial or equation that does not depend on any variable. It is the term that remains unchanged regardless of the values assigned to the variables in the expression.
Cramer's Rule: Cramer's rule is a method used to solve systems of linear equations by expressing the solution as a ratio of determinants. It provides a systematic way to find the unique solution to a system of linear equations, if it exists, by using the coefficients and constants of the equations.
Dependent system: A dependent system is a system of linear equations in which all equations represent the same line, resulting in infinitely many solutions. This occurs when the equations are scalar multiples of one another.
Dependent System: A dependent system, in the context of linear equations, refers to a system where the equations are linearly dependent, meaning that one equation can be expressed as a linear combination of the other equations. This implies that the system has an infinite number of solutions or no solution at all.
Determinant: A determinant is a scalar value that can be computed from the elements of a square matrix. It provides important properties about the matrix such as whether it is invertible.
Determinant: The determinant of a square matrix is a scalar value that is a function of the entries of the matrix. It is a fundamental concept in linear algebra that has important applications in the study of systems of linear equations, matrix inversions, and other areas of mathematics.
Diagonal Rule: The diagonal rule is a method used to solve systems of linear equations by applying Cramer's rule. It involves calculating the determinant of the coefficient matrix and the determinants of the matrices formed by replacing the columns of the coefficient matrix with the constant terms.
Elimination Method: The elimination method, also known as the method of elimination, is a technique used to solve systems of linear equations by systematically eliminating variables to find the unique solution. This method is applicable in the context of various topics, including parametric equations, systems of linear equations in two and three variables, and systems of nonlinear equations and inequalities.
Gabriel Cramer: Gabriel Cramer was an 18th century Swiss mathematician who is best known for developing Cramer's rule, a method for solving systems of linear equations. Cramer's rule provides a way to express the solution to a system of linear equations in terms of the coefficients and constants of the equations.
Gaussian elimination: Gaussian elimination is a method for solving systems of linear equations. It transforms the system's augmented matrix into row-echelon form using row operations.
Gaussian Elimination: Gaussian elimination is a method for solving systems of linear equations by transforming the system into an equivalent one that is easier to solve. It involves a series of row operations on the augmented matrix of the system to obtain an upper triangular matrix, which can then be used to find the solution to the system.
Inconsistent system: An inconsistent system is a set of equations that has no solution. This typically occurs when the equations represent parallel lines that never intersect.
Inconsistent System: An inconsistent system is a system of linear equations that has no solution, meaning there is no set of values for the variables that satisfies all the equations simultaneously. This term is particularly relevant in the context of solving systems of linear equations in two or more variables, as well as the techniques of Gaussian elimination and Cramer's rule.
Linear Algebra: Linear algebra is a branch of mathematics that deals with the study of linear equations, vectors, matrices, and the properties of linear transformations. It provides a framework for analyzing and solving systems of linear equations, which are fundamental in many areas of science, engineering, and mathematics.
Linear System: A linear system is a collection of linear equations that describe the relationship between multiple variables. These equations can be solved simultaneously to find the values of the variables that satisfy all the equations in the system.
Matrix: A matrix is a rectangular array of numbers, symbols, or expressions, arranged in rows and columns, that can be used to represent and manipulate mathematical relationships and data. Matrices are fundamental tools in various areas of mathematics, including linear algebra, applied mathematics, and computer science.
Matrix Inversion: Matrix inversion is the process of finding the inverse of a square matrix, which is a matrix that, when multiplied by the original matrix, results in the identity matrix. The inverse of a matrix allows for the solution of systems of linear equations using Cramer's rule.
Minor: In the context of solving systems with Cramer's Rule, a minor is the determinant of a submatrix formed by deleting a row and a column from the original matrix. Minors play a crucial role in the application of Cramer's Rule, which is a method for solving systems of linear equations.
Row Echelon Form: Row echelon form is a particular arrangement of the rows in a matrix or system of linear equations that simplifies the process of solving the system using techniques like Gaussian elimination. It is a crucial concept in the context of solving systems of linear equations.
Rule of Sarrus: The Rule of Sarrus is a method used to efficiently calculate the determinant of a 3x3 matrix. It provides a systematic approach to evaluating the determinant by arranging the matrix elements in a specific pattern and performing a series of multiplications and additions.
Simultaneous Equations: Simultaneous equations are a set of two or more equations that share common variables and must be solved together to find the values of those variables. They are a fundamental concept in algebra and are essential for understanding systems of linear and nonlinear equations.
Substitution method: The substitution method is a technique for solving systems of equations by substituting one equation into another. This transforms the system into a single-variable equation that can be solved more easily.
Substitution Method: The substitution method is a technique used to solve systems of linear equations, systems of nonlinear equations, and other types of equations by substituting one variable in terms of another. This method involves isolating a variable in one equation and then substituting that expression into the other equation(s) to solve for the remaining variable(s).
System of equations: A system of equations consists of two or more linear equations with the same set of variables. Solutions to the system are the variable values that satisfy all the equations simultaneously.
System of Equations: A system of equations is a set of two or more linear equations that share common variables and must be solved simultaneously to find the values of those variables. The solutions to a system of equations represent the point(s) where the equations intersect.
Unique solution: A unique solution refers to a single, distinct answer to a system of equations where all variables can be solved explicitly, resulting in one point of intersection in a graph. This concept is essential in understanding how various systems behave, especially when analyzing the relationships between multiple variables, whether linear or nonlinear. Identifying a unique solution ensures that the system is consistent and that there is a clear and definitive outcome for the values of the variables involved.
Δ: Δ, also known as the delta symbol, is a widely used mathematical symbol that typically represents the change or difference between two values or quantities. It is particularly significant in the context of solving systems of linear equations using Cramer's rule, as it plays a crucial role in the calculation and interpretation of determinants.
Δx: Δx, or delta x, is a small change or increment in the independent variable x. It is a fundamental concept in calculus and is often used in the context of analyzing rates of change and approximating derivatives.
Δy: Δy, or delta y, represents the change in the dependent variable y with respect to a change in the independent variable. It is a fundamental concept in calculus and is used to analyze the rate of change and behavior of functions.
Δz: Δz, or delta z, represents the change in the variable z within a system or function. It is a fundamental concept in mathematics and physics, particularly in the context of calculus and differential equations, where it is used to describe the infinitesimal change in a variable.
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