Class 12 Mathematics MATRIX-BASED SYSTEM OF LINEAR EQUATIONS Notes

Class 12 Mathematics Matrix-Based System of Linear Equations Notes | Nepal eNotes

Unit 7

Algebra

Class 12 Mathematics

Matrix-Based System of Linear Equations

Class 12 Mathematics – Matrix-Based System of Linear Equations Notes PDF

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NEB / CDC Focus

This chapter develops matrix-based techniques for solving simultaneous linear equations, especially Cramer’s rule, the row-equivalent matrix method, and the inverse-matrix method, for systems involving up to three variables.

1. System of Linear Equations

Linear Equation in Two Variables

An equation such as ax+by=c, where a and b are not both zero, is linear in x,y.

System of Linear Equations

Two or more linear equations considered simultaneously form a system of linear equations. A solution is a set of values satisfying every equation in the system.

For example,

2x+y=7,    x−y=2

is a system of two linear equations in two unknowns.

Geometric Meaning of a 2×2 System solution (x,y) equation 1 equation 2 A unique solution corresponds to a single intersection point.
Figure 1: A pair of linear equations in two variables represents two straight lines.

2. Matrix Form of a Linear System: AX=B

Consider

a₁x+b₁y=c₁,    a₂x+b₂y=c₂.

It can be written as

Matrix Form

a₁b₁a₂b₂ xy = c₁c₂

AX=B

where:

  • A = coefficient matrix,
  • X = column matrix of unknowns,
  • B = constant column matrix.
From Equations to AX=B Equations 2x+3y=7 x−y=1 organize Matrix Equation [ 2 3 ] [ x ] [ 7 ] [ 1 −1 ] [ y ] = [ 1 ] A · X = B
Figure 2: Matrix notation separates coefficients, unknowns and constants.

3. Determinants Needed for Cramer’s Rule

3.1 Determinant of a 2×2 Matrix

|a   b; c   d| = ad−bc.

For the coefficient matrix

a₁b₁a₂b₂,

its determinant is

D=a₁b₂−a₂b₁.

3.2 Determinant of a 3×3 Matrix

For D = |a₁ b₁ c₁; a₂ b₂ c₂; a₃ b₃ c₃| , expand along any row or column. Expanding along the first row:

D = a₁(b₂c₃−b₃c₂) −b₁(a₂c₃−a₃c₂) +c₁(a₂b₃−a₃b₂).
3×3 Determinant Expansion a₁b₁c₁ a₂b₂c₂ a₃b₃c₃ a₁(b₂c₃−b₃c₂) − b₁(a₂c₃−a₃c₂) + c₁(a₂b₃−a₃b₂) Sign pattern along the first row: +, −, +.
Figure 3: First-row expansion of a 3×3 determinant.
Remember

A sign error in a determinant affects every later step in Cramer’s rule. For first-row expansion, use + − +.

4. Cramer’s Rule for Two Variables

For

a₁x+b₁y=c₁,

a₂x+b₂y=c₂,

define

Cramer Determinants
D = a₁b₂−a₂b₁ Dx = c₁b₂−c₂b₁ Dy = a₁c₂−a₂c₁

If D≠0, then

Cramer’s Rule
x=Dx/D y=Dy/D
Cramer’s Rule: Replace One Column at a Time D | a₁ b₁ | | a₂ b₂ | original coefficient columns Dₓ | c₁ b₁ | | c₂ b₂ | replace x-column by constants Dᵧ | a₁ c₁ | | a₂ c₂ | replace y-column by constants x=Dₓ/D,   y=Dᵧ/D
Figure 4: Each numerator determinant replaces the column of the corresponding unknown.
Worked Example

Solve 2x+y=7, x−y=2.

D=2(−1)−1(1)=−3.

Dₓ=7(−1)−2(1)=−9.

Dᵧ=2(2)−1(7)=−3.

x=(−9)/(−3)=3,   y=(−3)/(−3)=1.

Answer: x=3, y=1.

5. Cramer’s Rule for Three Variables

For

a₁x+b₁y+c₁z=d₁,

a₂x+b₂y+c₂z=d₂,

a₃x+b₃y+c₃z=d₃,

let

D = |a₁ b₁ c₁; a₂ b₂ c₂; a₃ b₃ c₃|.

To form Dₓ, replace the x-column by the constants d₁,d₂,d₃. Similarly replace the y-column for Dᵧ and the z-column for Dz.

Solution when D≠0
x=Dₓ/D,   y=Dᵧ/D,   z=Dz/D.
Three-Variable Cramer Pattern D a₁ b₁ c₁a₂ b₂ c₂a₃ b₃ c₃ Dₓ d₁ b₁ c₁d₂ b₂ c₂d₃ b₃ c₃ Dᵧ a₁ d₁ c₁a₂ d₂ c₂a₃ d₃ c₃ D_z a₁ b₁ d₁a₂ b₂ d₂a₃ b₃ d₃ Replace exactly the column belonging to the unknown being solved.
Figure 5: Column replacement in Cramer’s rule for a 3×3 system.
Worked Example

Solve:

x+y+z=6,
2x−y+z=3,
x+2y−z=2.

Coefficient determinant:

D= |1 1 1; 2 −1 1; 1 2 −1| =7.

Dₓ=7,   Dᵧ=14,   Dz=21.

x=1,   y=2,   z=3.

6. Row-Equivalent Matrix Method

A system is written as an augmented matrix and transformed using elementary row operations until its solution is easy to read.

Elementary Row Operations
  • Rᵢ ↔ Rⱼ: interchange two rows.
  • Rᵢ → kRᵢ, k≠0: multiply a row by a non-zero constant.
  • Rᵢ → Rᵢ+kRⱼ: add a multiple of one row to another.

For

2x+y=7,   x−y=2,

the augmented matrix is

2171−12.

Use row operations:

R₁ → R₁−2R₂

to get

0331−12.

Thus 3y=3, so y=1, and x−1=2, so x=3.

Row-Reduction Strategy Augmented Matrix [ A | B ] write the full system row operations Row-Echelon / Reduced Form zeros below pivots simpler equivalent system Back-substitute / Read off obtain x, y, z
Figure 6: Row operations simplify the augmented matrix without changing its solution set.
Exam Important

Always write the row operation beside the step. Do not jump between matrices without showing how the new row was obtained.

7. Inverse Matrix Method

If

AX=B

and A is invertible, multiply by A⁻¹ from the left:

A⁻¹AX=A⁻¹B.

Since A⁻¹A=I,

Inverse-Matrix Solution
X=A⁻¹B.

7.1 Inverse of a 2×2 Matrix

If

A=abcd,

then, provided ad−bc≠0,

A⁻¹ = 1/(ad−bc) d−b−ca.
Inverse-Matrix Method AX = B left-multiply by A⁻¹ A⁻¹AX=A⁻¹B A⁻¹A=I X=A⁻¹B This method requires det(A)≠0 so that A⁻¹ exists.
Figure 7: Multiplying by the inverse isolates the unknown matrix X.
Worked Example

Solve 2x+y=7, x−y=2 using the inverse method.

A=211−1,   X=xy,   B=72.

det(A)=2(−1)−1(1)=−3.

A⁻¹=(-1/3) −1−1−12.

X=A⁻¹B= 31.

Answer: x=3, y=1.

8. Nature of Solutions and What the Determinant Tells Us

For a square system AX=B, the determinant of the coefficient matrix is especially important.

ConditionMeaningConsequence
det(A)≠0A is invertibleExactly one solution; Cramer and inverse methods both apply.
det(A)=0A is singularNo inverse exists; the system may have no solution or infinitely many solutions.

In row reduction, contradictory rows indicate no solution, while dependent rows may leave one or more free variables and hence infinitely many solutions.

Typical Row-Reduction Signals
[0   0   |   non-zero] ⇒ inconsistent ⇒ no solution [0   0   |   0] with a free variable ⇒ infinitely many solutions
Possible Solution Sets for Two Linear Equations One Solution lines intersect once No Solution distinct parallel lines Infinitely Many coincident lines
Figure 8: A two-equation system may have one, none, or infinitely many solutions.

9. Worked Examples

Example 1: Cramer’s Rule – 2×2

Solve 3x+2y=12, x−y=1.

D=3(−1)−2(1)=−5,

Dₓ=12(−1)−2(1)=−14,

Dᵧ=3(1)−12(1)=−9.

x=14/5,   y=9/5.

Example 2: Row Reduction – 2×2

Solve x+2y=5, 3x+4y=11.

1253411

R₂→R₂−3R₁

1250−2−4.

Hence y=2, then x=1.

Example 3: Inverse Method – 2×2

Solve x+y=5, 2x−y=1.

A=112−1,   B=51.

det(A)=−3.

A⁻¹=(-1/3) −1−1−21.

X=A⁻¹B=(2,3)T.

Answer: x=2, y=3.

Example 4: Three Variables by Elimination / Row Form

Solve:

x+y+z=6,
x−y+z=2,
2x+y−z=1.

Subtract row 1 from row 2:

−2y=−4 ⇒ y=2.

Using x+z=4 and the third equation 2x−z=−1:

3x=3 ⇒ x=1,   z=3.

Answer: x=1, y=2, z=3.

Example 5: Singular System with Infinitely Many Solutions

Consider x+y=2 and 2x+2y=4.

The second equation is exactly twice the first. Row reduction gives a zero row:

112000.

There is one free variable, so the system has infinitely many solutions.

Example 6: Inconsistent System

Consider x+y=2 and 2x+2y=5.

Eliminating gives 0=1, which is impossible.

Therefore the system has no solution.

Example 7: Check a Proposed Solution

Check whether (x,y)=(2,1) satisfies 3x−y=5 and x+2y=4.

3(2)−1=5,   2+2(1)=4.

Both are true, so (2,1) is the solution.

10. Application to Word Problems

Linear systems often arise when several unknown quantities satisfy several independent conditions. The main challenge is translating the wording into equations.

Worked Example: Ticket Problem

Adult tickets cost NPR 200 and student tickets cost NPR 100. A total of 30 tickets produces NPR 4,500. Find the number of each type.

Let x = adult tickets, y = student tickets.

x+y=30,
200x+100y=4500.

Divide the second equation by 100:

2x+y=45.

Subtract the first equation:

x=15.

Then y=15.

Answer: 15 adult tickets and 15 student tickets.

Word-Problem Checklist
  • Define each unknown clearly.
  • Translate each independent condition into one linear equation.
  • Write the coefficient matrix in the same variable order in every row.
  • Solve by the method requested in the question.
  • Interpret the numerical answer in the original context.

11. Choosing the Best Method

MethodBest useMain requirement / caution
Cramer’s ruleSmall square systems, especially 2×2 or 3×3; exam questions asking determinant methodFor the direct unique-solution formula, D≠0.
Row-equivalent methodGeneral systematic solving and identifying no/infinite solutionsKeep row operations accurate and preserve the augmented column.
Inverse matrix methodSquare system written as AX=BRequires A⁻¹, so det(A)≠0.

12. Common Mistakes and Warnings

Mistake 1: Wrong variable order

If columns are ordered x,y,z, every equation must follow that same order.

Mistake 2: Cramer column replacement

For Dₓ replace only the x-column; for Dᵧ only the y-column, etc.

Mistake 3: Dividing by D=0

Cramer’s direct formula cannot be used when the main determinant is zero.

Mistake 4: 3×3 sign error

When expanding across the first row, the cofactor signs are +, −, +.

Mistake 5: Row operation on A only

In an augmented matrix, apply the row operation to the entire row, including constants.

Mistake 6: Wrong side for A⁻¹

From AX=B, multiply on the left by A⁻¹: A⁻¹AX=A⁻¹B.

Mistake 7: Using an inverse when det(A)=0

A singular matrix has no ordinary inverse.

Mistake 8: Not checking the answer

Substitute the final x,y,z into the original equations to catch arithmetic errors.

13. Exam-Important Formula Sheet

Core Formulas
Matrix system: AX=B 2×2 determinant: |a b; c d|=ad−bc Cramer: x=Dₓ/D, y=Dᵧ/D Three variables: x=Dₓ/D, y=Dᵧ/D, z=D_z/D Inverse method: X=A⁻¹B A⁻¹=(1/det A) adj(A), when det(A)≠0 For A=[a b; c d], A⁻¹=(1/(ad−bc))[d −b; −c a] Elementary row operations: Rᵢ↔Rⱼ, Rᵢ→kRᵢ, Rᵢ→Rᵢ+kRⱼ

14. Important Exam Questions

Short-Answer Questions

  1. Write a given system of linear equations in matrix form AX=B.
  2. Define the coefficient matrix and augmented matrix.
  3. State Cramer’s rule for two variables.
  4. State Cramer’s rule for three variables.
  5. Write the three elementary row operations.
  6. State the inverse-matrix method for solving AX=B.
  7. What condition is required for A⁻¹ to exist?
  8. What does det(A)≠0 imply for a square linear system?

Derivation / Explanation Questions

  1. Derive the inverse-matrix solution X=A⁻¹B from AX=B.
  2. Explain how the determinants D,Dₓ,Dᵧ are formed in Cramer’s rule.
  3. Explain how row operations preserve an equivalent linear system.
  4. Describe how row reduction identifies a contradictory or dependent system.

Numerical Questions

  1. Solve a 2×2 system by Cramer’s rule.
  2. Solve a 3×3 system by Cramer’s rule.
  3. Solve a system using the row-equivalent matrix method.
  4. Solve a 2×2 or 3×3 system using the inverse-matrix method.
  5. Determine whether a system has a unique solution, no solution or infinitely many solutions.
  6. Translate a simple word problem into simultaneous linear equations and solve it by a matrix method.

Diagram / Matrix Practice

  1. Show the conversion of simultaneous equations into AX=B.
  2. Draw the column-replacement pattern used in Cramer’s rule.
  3. Write the row-reduction flow from an augmented matrix to echelon form.
  4. Illustrate geometrically the one-solution, no-solution and infinitely-many-solution cases for two variables.

15. One-Minute Revision

Quick Revision
  • A linear system can be represented compactly as AX=B.
  • A contains coefficients, X unknowns, and B constants.
  • For a 2×2 matrix, determinant = ad−bc.
  • Cramer’s rule replaces one coefficient column at a time by the constant column.
  • If D≠0, a square system has a unique solution.
  • For two variables, x=Dₓ/D, y=Dᵧ/D.
  • For three variables, also use z=D_z/D.
  • Row operations are row interchange, non-zero row scaling and row replacement.
  • Always apply a row operation to the constant column too.
  • The inverse method is X=A⁻¹B.
  • The inverse method requires det(A)≠0.
  • A row equivalent to 0=nonzero signals no solution.
  • A zero row with free variables may signal infinitely many solutions.
  • Keep the variable order consistent in every equation and matrix.
  • Substitute the answer back into the original equations for a final check.

16. Diagram Practice

  • Two intersecting straight lines representing a unique 2×2 solution.
  • Equation-to-AX=B conversion diagram.
  • 3×3 determinant expansion with +, −, + signs.
  • Cramer column-replacement diagram for two variables.
  • Cramer column-replacement diagram for three variables.
  • Row-reduction flowchart.
  • Inverse-matrix method flowchart.
  • Unique/no/infinite solution geometry for two equations.

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