100% FREE Updated: Apr 2026 Vectors, Matrices and 3D Geometry Matrices and Determinants

Determinants

Comprehensive study notes on Determinants for CMI BS Hons preparation. This chapter covers key concepts, formulas, and examples needed for your exam.

Determinants

This chapter rigorously introduces determinants, essential scalar values derived from square matrices, covering their definition and evaluation across various orders. Mastery of determinant calculation and properties is fundamental for solving systems of linear equations, understanding matrix invertibility, and is frequently tested in CMI examinations. These concepts form a cornerstone for advanced topics in linear algebra.

---

Chapter Contents

|

| Topic |

|---|-------| | 1 | Determinants of order 2 | | 2 | Determinants of order 3 | | 3 | Evaluation techniques | | 4 | Properties of determinants |

---

We begin with Determinants of order 2.

Part 1: Determinants of order 2

Determinants of Order 2

Overview

A determinant of order 2 is the simplest determinant, but it already carries important algebraic and geometric information. It tests invertibility, area scaling, row-operation effects, and parameter conditions. In exam problems, the challenge is not the formula itself, but knowing what the determinant tells you. ---

Learning Objectives

❗ By the End of This Topic

After studying this topic, you will be able to:

  • Compute determinants of 2Γ—22\times 2 matrices quickly.

  • Use the determinant to test singularity and invertibility.

  • Understand the effect of row and column operations on determinants.

  • Use determinants geometrically for area.

  • Solve parameter-based determinant equations.

---

Basic Formula

πŸ“ Determinant of Order 2

For the matrix

(abcd)\qquad \begin{pmatrix} a & b\\ c & d \end{pmatrix}

the determinant is

∣abcd∣=adβˆ’bc\qquad \begin{vmatrix} a & b\\ c & d \end{vmatrix} = ad-bc

This must be memorized exactly. ---

Invertibility Criterion

❗ When Is a 2Γ—22\times 2 Matrix Singular?

A 2Γ—22\times 2 matrix is singular if and only if its determinant is zero.

So
∣abcd∣=0\qquad \begin{vmatrix} a & b\\ c & d \end{vmatrix}=0
means the matrix is non-invertible.

If the determinant is nonzero, the matrix is invertible.

---

Geometric Meaning

πŸ“ Area Interpretation

If the rows or columns of a 2Γ—22\times 2 matrix are treated as vectors in the plane, then the absolute value of the determinant gives the area of the parallelogram formed by them.

So for vectors (a,b)(a,b) and (c,d)(c,d), area is

∣adβˆ’bc∣\qquad \left|ad-bc\right|

The area of the triangle formed by the same two vectors is 12∣adβˆ’bc∣\qquad \dfrac{1}{2}|ad-bc| ::: ---

Row and Column Effects

πŸ“ Important Properties

  • Swapping two rows changes the sign of the determinant.

  • If two rows are equal, the determinant is zero.

  • Multiplying one row by kk multiplies the determinant by kk.

  • Adding a multiple of one row to the other row does not change the determinant.

These are fundamental and often more useful than direct expansion. ---

Minimal Worked Examples

Example 1 Compute ∣2314∣\qquad \begin{vmatrix}2 & 3\\1 & 4\end{vmatrix} Using adβˆ’bcad-bc: 2β‹…4βˆ’3β‹…1=8βˆ’3=5\qquad 2\cdot 4 - 3\cdot 1 = 8-3=5 --- Example 2 Find kk such that ∣k236∣=0\qquad \begin{vmatrix}k & 2\\3 & 6\end{vmatrix}=0 We get 6kβˆ’6=0\qquad 6k-6=0 So k=1\qquad k=1 ---

Standard Patterns

πŸ“ High-Value Patterns

  • direct computation:

adβˆ’bc\qquad ad-bc

  • singular matrix:

determinant =0=0

  • invertible matrix:

determinant β‰ 0\ne 0

  • area of parallelogram:

∣adβˆ’bc∣\qquad |ad-bc|

  • area of triangle:

12∣adβˆ’bc∣\qquad \dfrac{1}{2}|ad-bc|

---

Common Mistakes

⚠️ Avoid These Errors
    • ❌ Writing determinant as bcβˆ’adbc-ad
βœ… Correct formula is adβˆ’bcad-bc
    • ❌ Forgetting the sign change after row swap
    • ❌ Thinking determinant zero only means β€œsmall”
βœ… It means the rows or columns are linearly dependent
    • ❌ Forgetting absolute value when interpreting area
---

CMI Strategy

πŸ’‘ How to Attack These Questions

  • First see whether direct computation is enough.

  • If a parameter is involved, set the determinant equal to zero or nonzero as needed.

  • In geometric problems, convert the given points into difference vectors first.

  • Use determinant properties when simplification is easier than direct expansion.

  • Keep sign discipline very carefully.

---

Practice Questions

:::question type="MCQ" question="The value of ∣2314∣\begin{vmatrix}2 & 3\\1 & 4\end{vmatrix} is" options=["55","1111","βˆ’5-5","88"] answer="A" hint="Use adβˆ’bcad-bc." solution="Using the formula, 2β‹…4βˆ’3β‹…1=8βˆ’3=5\qquad 2\cdot 4 - 3\cdot 1 = 8-3=5 Hence the correct option is A\boxed{A}." ::: :::question type="NAT" question="Find the value of kk for which ∣k236∣=0\begin{vmatrix}k & 2\\3 & 6\end{vmatrix}=0." answer="1" hint="Set 6kβˆ’6=06k-6=0." solution="The determinant is 6kβˆ’2β‹…3=6kβˆ’6\qquad 6k-2\cdot 3 = 6k-6 Setting this equal to zero: 6kβˆ’6=0\qquad 6k-6=0 k=1\qquad k=1 Hence the answer is 1\boxed{1}." ::: :::question type="MSQ" question="Which of the following are true?" options=["Swapping two rows changes the sign of the determinant","If two rows are equal, the determinant is zero","The determinant of \begin{pmatrix}a & b\c & d\end{pmatrix} is bcβˆ’adbc-ad","A 2Γ—22\times 2 matrix is invertible exactly when its determinant is nonzero"] answer="A,B,D" hint="One formula is written with the wrong sign order." solution="1. True.
  • True.
  • False. The correct formula is adβˆ’bcad-bc.
  • True.
  • Hence the correct answer is A,B,D\boxed{A,B,D}." ::: :::question type="SUB" question="Find all real values of xx for which the matrix (x12x)\begin{pmatrix}x & 1\\2 & x\end{pmatrix} is singular." answer="x=Β±2x=\pm \sqrt{2}" hint="Set the determinant equal to zero." solution="The matrix is singular when its determinant is zero. So ∣x12x∣=x2βˆ’2\qquad \begin{vmatrix}x & 1\\2 & x\end{vmatrix}=x^2-2 Set this equal to zero: x2βˆ’2=0\qquad x^2-2=0 Hence x=Β±2\qquad x=\pm \sqrt{2} Therefore the required values are x=Β±2\boxed{x=\pm\sqrt{2}}." ::: ---

    Summary

    ❗ Key Takeaways for CMI

    • For a 2Γ—22\times 2 matrix, determinant is adβˆ’bcad-bc.

    • Determinant zero means singularity.

    • Nonzero determinant means invertibility.

    • Absolute value of determinant gives area of a parallelogram.

    • Sign discipline matters in every determinant problem.

    ---

    πŸ’‘ Next Up

    Proceeding to Determinants of order 3.

    ---

    Part 2: Determinants of order 3

    Determinants of Order 3

    Overview

    Determinants of order 33 are the first nontrivial determinants where structure matters. Unlike order 22, direct expansion can become messy if done carelessly. In exam problems, this topic is tested through direct evaluation, row/column observation, factor extraction, parameter values for zero determinant, and geometric interpretation such as coplanarity or area/volume-type reasoning. ---

    Learning Objectives

    ❗ By the End of This Topic

    After studying this topic, you will be able to:

    • Evaluate a 3Γ—33\times 3 determinant correctly.

    • Expand along a suitable row or column to reduce computation.

    • Detect special structures that simplify a determinant immediately.

    • Use determinant zero conditions to solve parameter problems.

    • Recognise the cyclic and sign pattern in cofactor expansion.

    ---

    Core Definition

    πŸ“– Determinant of a 3Γ—33\times 3 Matrix

    For
    <br>∣<br>abc<br>def<br>ghi<br>∣<br>\qquad <br>\begin{vmatrix}<br>a & b & c\\ <br>d & e & f\\ <br>g & h & i <br>\end{vmatrix} <br>

    the determinant is

    <br>a(eiβˆ’fh)βˆ’b(diβˆ’fg)+c(dhβˆ’eg)<br>\qquad <br>a(ei-fh)-b(di-fg)+c(dh-eg) <br>

    This is the standard expansion along the first row. ---

    Standard Expansion Formula

    πŸ“ Expansion Along First Row

    <br>∣<br>abc<br>def<br>ghi<br>∣<br>=<br>a∣efhi∣<br>βˆ’b∣dfgi∣<br>+c∣degh∣<br>\qquad <br>\begin{vmatrix}<br>a & b & c\\ <br>d & e & f\\ <br>g & h & i <br>\end{vmatrix} <br>= <br>a\begin{vmatrix} e & f\\ h & i\end{vmatrix} <br>-b\begin{vmatrix} d & f\\ g & i\end{vmatrix} <br>+c\begin{vmatrix} d & e\\ g & h\end{vmatrix} <br>

    That is,

    <br>a(eiβˆ’fh)βˆ’b(diβˆ’fg)+c(dhβˆ’eg)<br>\qquad <br>a(ei-fh)-b(di-fg)+c(dh-eg) <br>

    The signs are: +βˆ’+\qquad +\quad -\quad + for first-row expansion. ---

    Sarrus-Type Memory Aid

    πŸ’‘ Useful Memory Aid

    For
    <br>∣<br>abc<br>def<br>ghi<br>∣<br>\qquad <br>\begin{vmatrix}<br>a & b & c\\ <br>d & e & f\\ <br>g & h & i <br>\end{vmatrix} <br>

    a quick pattern is:

    aei+bfg+cdhβˆ’(ceg+bdi+afh)\qquad aei+bfg+cdh - (ceg+bdi+afh)

    This is a memory aid only. In formal work, cofactor expansion is more reliable.

    ---

    When the Determinant is Zero Immediately

    πŸ“ Quick Zero Cases

    A 3Γ—33\times 3 determinant is zero if:

    • any two rows are equal

    • any two columns are equal

    • one row or column is all zero

    • one row is a scalar multiple of another

    • one column is a scalar multiple of another

    • one row or column is a linear combination of the others

    These are high-value observations in exam problems. ---

    Expansion Strategy

    πŸ’‘ Choose the Best Row or Column

    Although every row or column expansion gives the same answer, some are much easier.

    Prefer expansion along a row or column with:

      • zeros

      • simpler entries

      • repeated structure

      • parameter terms arranged advantageously

    ---

    Minimal Worked Examples

    Example 1 Evaluate $\qquad \begin{vmatrix} 1 & 2 & 3\\ 0 & 1 & 4\\ 5 & 6 & 0 \end{vmatrix} $ Expand along the first row: $\qquad 1\begin{vmatrix}1&4\\6&0\end{vmatrix} -2\begin{vmatrix}0&4\\5&0\end{vmatrix} +3\begin{vmatrix}0&1\\5&6\end{vmatrix} $ $\qquad =1(0-24)-2(0-20)+3(0-5) $ $\qquad =-24+40-15=1 $ So the determinant is 1\boxed{1}. --- Example 2 Evaluate $\qquad \begin{vmatrix} 1 & 1 & 1\\ a & b & c\\ a^2 & b^2 & c^2 \end{vmatrix} $ This is a standard Vandermonde-type determinant, and it equals (bβˆ’a)(cβˆ’a)(cβˆ’b)\qquad (b-a)(c-a)(c-b) up to sign convention. In the ordered form above it is (bβˆ’a)(cβˆ’a)(cβˆ’b)\qquad (b-a)(c-a)(c-b) This is important in factor-detection problems. ::: ---

    Special Patterns

    πŸ“ Triangular Form

    If a 3Γ—33\times 3 matrix is upper triangular or lower triangular, then its determinant is the product of the diagonal entries.

    Example:

    <br>∣<br>a<em></em><br>0bβˆ—<br>00c<br>∣<br>=abc<br>\qquad <br>\begin{vmatrix}<br>a & <em> & </em>\\ <br>0 & b & *\\ <br>0 & 0 & c <br>\end{vmatrix} <br>=abc <br>

    πŸ“ Row/Column Common Factor

    If one row has a common factor kk, then the determinant has a factor kk.

    Similarly for columns.

    ---

    Parameter Questions

    ❗ Determinant Zero Often Means Dependence

    Questions of the form
    det⁑(A)=0\qquad \det(A)=0
    usually ask you to:

    • compute the determinant as an algebraic expression

    • solve for the parameter values making it zero


    Geometrically, det⁑=0\det=0 often indicates dependence, coplanarity, or non-invertibility.

    ---

    Common Mistakes

    ⚠️ Avoid These Errors
      • ❌ Forgetting the negative sign on the middle term in first-row expansion
    βœ… The sign pattern is +β€‰βˆ’β€‰++\,-\,+
      • ❌ Mixing minors and cofactors
    βœ… Cofactor includes the sign; minor does not
      • ❌ Expanding along a complicated row when a simpler one exists
    βœ… Choose zeros when possible
      • ❌ Arithmetic slip in 2Γ—22\times 2 minors
    βœ… Recompute minors carefully
    ---

    CMI Strategy

    πŸ’‘ How to Attack Order-3 Determinants

    • First inspect for zero-value structure.

    • If not immediate, choose the easiest row/column for expansion.

    • Compute the 2Γ—22\times 2 minors carefully.

    • Keep the sign pattern fixed.

    • In parameter questions, simplify only after getting the correct algebraic expression.

    ---

    Practice Questions

    :::question type="MCQ" question="The sign pattern in expansion along the first row of a 3Γ—33\times 3 determinant is" options=["+,+,++,+,+","+,βˆ’,++,-,+","βˆ’,+,βˆ’-,+,-","+,βˆ’,βˆ’+,-,-"] answer="B" hint="Recall cofactor signs." solution="The cofactor signs in the first row are +β€‰βˆ’β€‰+\qquad +\,-\,+ Hence the correct option is B\boxed{B}." ::: :::question type="NAT" question="Find ∣100230456∣\begin{vmatrix}1 & 0 & 0\\2 & 3 & 0\\4 & 5 & 6\end{vmatrix}." answer="18" hint="Use triangular structure." solution="The matrix is lower triangular, so the determinant is the product of diagonal entries: 1β‹…3β‹…6=18\qquad 1\cdot 3\cdot 6=18 Hence the answer is 18\boxed{18}." ::: :::question type="MSQ" question="Which of the following conditions force a 3Γ—33\times 3 determinant to be zero?" options=["Two rows are equal","One row is all zero","Two columns are proportional","The diagonal entries are all nonzero"] answer="A,B,C" hint="Think about dependence of rows/columns." solution="1. True.
  • True.
  • True.
  • False. Nonzero diagonal entries do not by themselves force determinant zero.
  • Hence the correct answer is A,B,C\boxed{A,B,C}." ::: :::question type="SUB" question="Evaluate ∣123213321∣\begin{vmatrix}1 & 2 & 3\\2 & 1 & 3\\3 & 2 & 1\end{vmatrix}." answer="88" hint="Expand along the first row." solution="Expand along the first row: $\qquad \begin{vmatrix} 1&2&3\\ 2&1&3\\ 3&2&1 \end{vmatrix} = 1\begin{vmatrix}1&3\\2&1\end{vmatrix} -2\begin{vmatrix}2&3\\3&1\end{vmatrix} +3\begin{vmatrix}2&1\\3&2\end{vmatrix} $ Now compute the minors: $\qquad \begin{vmatrix}1&3\\2&1\end{vmatrix}=1-6=-5 $ $\qquad \begin{vmatrix}2&3\\3&1\end{vmatrix}=2-9=-7 $ $\qquad \begin{vmatrix}2&1\\3&2\end{vmatrix}=4-3=1 $ So βˆ’5βˆ’2(βˆ’7)+3(1)=βˆ’5+14+3=12\qquad -5 -2(-7)+3(1) = -5+14+3=12 Hence the determinant is 12\boxed{12}." ::: ---

    Summary

    ❗ Key Takeaways for CMI

    • A 3Γ—33\times 3 determinant is usually evaluated by cofactor expansion.

    • The first-row sign pattern is +β€‰βˆ’β€‰++\,-\,+.

    • Structural simplifications can save a lot of time.

    • Zero determinants often signal dependence.

    • Accuracy in minors and signs matters more than speed.

    ---

    πŸ’‘ Next Up

    Proceeding to Evaluation techniques.

    ---

    Part 3: Evaluation techniques

    Evaluation Techniques

    Overview

    Many determinant questions are not meant to be expanded directly. Instead, they are designed to reward observation and transformation. Evaluation techniques include row and column operations, factor extraction, creating zeros, symmetry spotting, and reducing the determinant to a standard form. In exam problems, the best solution is often the one that avoids brute-force expansion. ---

    Learning Objectives

    ❗ By the End of This Topic

    After studying this topic, you will be able to:

    • Use elementary row/column operations to simplify determinants.

    • Extract common factors efficiently.

    • Create zeros before expansion.

    • Detect and exploit symmetry or antisymmetry.

    • Recognise standard forms such as Vandermonde-type determinants.

    ---

    Main Principle

    ❗ Do Not Expand Too Early

    Direct expansion of an order-33 determinant is sometimes fine, but many exam problems become far easier after one or two smart operations.

    Good evaluation technique means:

      • reduce first

      • expand later

    ---

    High-Value Operations

    πŸ“ Row and Column Operations That Help

    • Add a multiple of one row to another row

    • Add a multiple of one column to another column

    • Factor out common terms from a row or column

    • Swap rows or columns if that creates a better structure

    • Make one row or column sparse, then expand

    These techniques are useful because they often preserve the determinant or change it in a controlled way. ---

    Factor Extraction

    πŸ“ Extract Common Factors

    If a row has common factor kk, then

    det⁑=kΓ—(determinantΒ ofΒ simplifiedΒ matrix)\qquad \det = k \times (\text{determinant of simplified matrix})

    Similarly for columns.

    If multiple rows/columns have factors, extract all of them first.

    This often reveals hidden polynomials or standard forms. ---

    Creating Zeros

    πŸ’‘ The Most Practical Technique

    If you can make two entries of a row or column zero, expansion becomes very fast.

    Typical moves:

      • R2β†’R2βˆ’R1R_2 \to R_2 - R_1

      • C3β†’C3βˆ’C1C_3 \to C_3 - C_1

      • subtract neighbouring rows or columns in symmetric problems

    ---

    Standard Patterns

    πŸ“ Frequently Appearing Forms

    • Repeated linear expressions:

    create differences

    • Polynomial rows like

    1,Β a,Β a2\qquad 1,\ a,\ a^2
    suggest Vandermonde structure

    • Symmetric rows/columns:

    use subtraction to expose dependence

    • Nearly triangular structure:

    finish by expansion or direct product

    ---

    Minimal Worked Examples

    Example 1 Evaluate $\qquad \begin{vmatrix} 1&1&1\\ 2&3&4\\ 5&7&9 \end{vmatrix} $ Use column differences: C2β†’C2βˆ’C1,C3β†’C3βˆ’C2\qquad C_2 \to C_2-C_1,\quad C_3 \to C_3-C_2 A more systematic move is: $\qquad \begin{vmatrix} 1&1&1\\ 2&3&4\\ 5&7&9 \end{vmatrix} \overset{C_2-C_1,\ C_3-C_2}{\longrightarrow} \begin{vmatrix} 1&0&0\\ 2&1&1\\ 5&2&2 \end{vmatrix} $ Now expand along the first row: $\qquad 1\begin{vmatrix}1&1\\2&2\end{vmatrix}=0 $ So the determinant is 0\boxed{0}. --- Example 2 Evaluate $\qquad \begin{vmatrix} x&x&x\\ y&y&y\\ z&z&z \end{vmatrix} $ All columns are identical, so the determinant is immediately 0\boxed{0}. ---

    Vandermonde-Type Recognition

    πŸ“ A Standard Form

    A very useful determinant is

    <br>∣<br>111<br>abc<br>a2b2c2<br>∣<br>\qquad <br>\begin{vmatrix}<br>1 & 1 & 1\\ <br>a & b & c\\ <br>a^2 & b^2 & c^2 <br>\end{vmatrix} <br>

    This equals

    (bβˆ’a)(cβˆ’a)(cβˆ’b)\qquad (b-a)(c-a)(c-b)

    up to the ordering convention.

    This should be recognised quickly in exam settings.

    ---

    Parameter Evaluation

    ❗ Parameter-Based Problems

    When a determinant depends on a parameter:

    • simplify structurally first

    • extract factors if possible

    • then solve for values giving zero or a target value


    This is usually much easier than direct full expansion at the start.

    ---

    Common Mistakes

    ⚠️ Avoid These Errors
      • ❌ Expanding immediately when a zero-creating move is available
    βœ… First simplify
      • ❌ Forgetting whether an operation preserves the determinant or changes it
    βœ… Track factor extraction and swaps carefully
      • ❌ Missing repeated columns/rows
    βœ… Always inspect structure before computing
      • ❌ Doing several operations without writing them clearly
    βœ… Keep row/column operations readable
    ---

    CMI Strategy

    πŸ’‘ How to Evaluate Smartly

    • Inspect for identical/proportional rows or columns.

    • Extract obvious factors.

    • Create zeros using subtraction.

    • Look for a standard pattern.

    • Expand only after the determinant becomes sparse or recognisable.

    ---

    Practice Questions

    :::question type="MCQ" question="In determinant evaluation, the most efficient first step is often" options=["direct expansion every time","checking for simplification opportunities","multiplying all entries","changing signs randomly"] answer="B" hint="Think about why evaluation techniques exist." solution="The purpose of evaluation techniques is to simplify before expanding. Hence the correct option is B\boxed{B}." ::: :::question type="NAT" question="Evaluate ∣111222333∣\begin{vmatrix}1 & 1 & 1\\2 & 2 & 2\\3 & 3 & 3\end{vmatrix}." answer="0" hint="Look at the columns." solution="All three columns are identical, so the determinant is 0\boxed{0}." ::: :::question type="MSQ" question="Which of the following are useful evaluation techniques for determinants?" options=["Creating zeros","Extracting common factors","Recognising standard patterns","Ignoring row/column structure"] answer="A,B,C" hint="Think about what reduces computation." solution="1. True.
  • True.
  • True.
  • False.
  • Hence the correct answer is A,B,C\boxed{A,B,C}." ::: :::question type="SUB" question="Evaluate ∣111\abc\a+bb+cc+a∣\begin{vmatrix}1 & 1 & 1\a & b & c\a+b & b+c & c+a\end{vmatrix}." answer="(aβˆ’c)(bβˆ’c)(a-c)(b-c)" hint="Use a column operation or first-row expansion after simplification." solution="Expand along the first row: $\qquad \begin{vmatrix} 1&1&1\\ a&b&c\\ a+b&b+c&c+a \end{vmatrix} = 1\begin{vmatrix}b&c\\ b+c&c+a\end{vmatrix} -1\begin{vmatrix}a&c\\ a+b&c+a\end{vmatrix} +1\begin{vmatrix}a&b\\ a+b&b+c\end{vmatrix} $ Now compute each minor: b(c+a)βˆ’c(b+c)=abβˆ’c2\qquad b(c+a)-c(b+c)=ab-c^2 a(c+a)βˆ’c(a+b)=a2βˆ’bc\qquad a(c+a)-c(a+b)=a^2-bc a(b+c)βˆ’b(a+b)=acβˆ’b2\qquad a(b+c)-b(a+b)=ac-b^2 So the determinant is (abβˆ’c2)βˆ’(a2βˆ’bc)+(acβˆ’b2)\qquad (ab-c^2) - (a^2-bc) + (ac-b^2) =abβˆ’c2βˆ’a2+bc+acβˆ’b2\qquad = ab-c^2-a^2+bc+ac-b^2 This can be regrouped as βˆ’(a2+b2+c2βˆ’abβˆ’bcβˆ’ca)+2ac\qquad -(a^2+b^2+c^2-ab-bc-ca) + 2ac A cleaner route is to simplify first: Take C3β†’C3βˆ’C2\qquad C_3 \to C_3-C_2 Then C2β†’C2βˆ’C1\qquad C_2 \to C_2-C_1 The determinant becomes $\qquad \begin{vmatrix} 1&0&0\\ a&b-a&c-b\\ a+b&c-a&a-b \end{vmatrix} $ Now expand along the first row: $\qquad \begin{vmatrix} b-a & c-b\\ c-a & a-b \end{vmatrix} $ This equals $\qquad (b-a)(a-b) - (c-b)(c-a) = -(b-a)^2 - (c-b)(c-a) $ Expanding and simplifying gives $\qquad ab+ac+bc-a^2-b^2-c^2 $ Hence the determinant is ab+ac+bcβˆ’a2βˆ’b2βˆ’c2\qquad \boxed{ab+ac+bc-a^2-b^2-c^2}" ::: ---

    Summary

    ❗ Key Takeaways for CMI

    • Good determinant evaluation is mostly good simplification.

    • Create zeros before expanding whenever possible.

    • Extract factors and detect repeated structure early.

    • Standard forms should be recognised immediately.

    • Direct expansion is a last resort, not the default method.

    ---

    πŸ’‘ Next Up

    Proceeding to Properties of determinants.

    ---

    Part 4: Properties of determinants

    Properties of Determinants

    Overview

    The power of determinants lies not only in computation, but in their properties. These properties explain how determinants change under row and column operations, when they become zero, and how they behave under scalar multiplication or matrix products. In exam problems, many determinant questions are solved more by properties than by expansion. ---

    Learning Objectives

    ❗ By the End of This Topic

    After studying this topic, you will be able to:

    • Use fundamental row and column properties of determinants.

    • Predict how a determinant changes under swaps, scaling, or row addition.

    • Recognise conditions forcing a determinant to vanish.

    • Use determinant properties to simplify evaluation.

    • Apply determinant properties in proof-style problems.

    ---

    Core Properties

    πŸ“ Basic Determinant Properties

    For determinants of any order:

    • Interchanging two rows changes the sign of the determinant.

    • Interchanging two columns changes the sign of the determinant.

    • If two rows are equal, the determinant is zero.

    • If two columns are equal, the determinant is zero.

    • If one row is multiplied by kk, the determinant is multiplied by kk.

    • If one column is multiplied by kk, the determinant is multiplied by kk.

    • Adding a multiple of one row to another row does not change the determinant.

    • Adding a multiple of one column to another column does not change the determinant.

    These are the most frequently used determinant properties in exams. ---

    Zero Conditions

    ❗ When a Determinant Must Be Zero

    A determinant is zero if:

      • two rows are equal

      • two columns are equal

      • one row is a scalar multiple of another

      • one column is a scalar multiple of another

      • one row or column is zero

      • one row or column is a linear combination of others

    These all express dependence. ---

    Sign Change and Scaling

    πŸ“ Controlled Changes
      • Swapping two rows: multiply by βˆ’1-1
      • Swapping two columns: multiply by βˆ’1-1
      • Multiplying one row by kk: multiply determinant by kk
      • Multiplying one column by kk: multiply determinant by kk
    If two such changes happen, combine their effects multiplicatively.
    ---

    Invariance Under Row Addition

    ❗ One of the Most Useful Properties

    If you replace a row by

    Ri+Ξ»Rj\qquad R_i + \lambda R_j

    where i≠ji\ne j, then the determinant remains unchanged.

    Similarly for columns.

    This is a major simplification tool because it lets you create zeros without changing the determinant.

    ---

    Triangular and Diagonal Cases

    πŸ“ Triangular Determinants

    For an upper or lower triangular matrix, the determinant is the product of the diagonal entries.

    For a diagonal matrix
    diag⁑(d1,d2,…,dn)\qquad \operatorname{diag}(d_1,d_2,\dots,d_n),

    det⁑=d1d2β‹―dn\qquad \det = d_1d_2\cdots d_n

    ---

    Determinant of a Product

    πŸ“ Multiplicative Property

    For square matrices AA and BB of the same order,

    det⁑(AB)=det⁑(A)det⁑(B)\qquad \det(AB)=\det(A)\det(B)

    This is an important theoretical property and appears in proof-style questions. ---

    Minimal Worked Examples

    Example 1 If two rows of a determinant are equal, then the determinant is 00. Reason: swapping those equal rows changes the sign, but the determinant remains the same matrix. So det⁑=βˆ’det⁑\qquad \det = -\det hence det⁑=0\qquad \det=0 --- Example 2 Evaluate $\qquad \begin{vmatrix} 1&2&3\\ 2&4&6\\ 1&0&1 \end{vmatrix} $ The second row is 22 times the first row, so the determinant is immediately 0\boxed{0}. ---

    Linearity View

    ❗ Determinant is Linear in Each Row Separately

    If all rows except one are fixed, then the determinant is linear in the remaining row.

    This explains why adding a multiple of one row to another does not change the determinant and why a common factor can be pulled out of a row.

    You do not always need to state linearity explicitly, but it is the idea behind many standard properties. ---

    Common Mistakes

    ⚠️ Avoid These Errors
      • ❌ Thinking row addition changes the determinant
    βœ… Adding a multiple of one row to another leaves it unchanged
      • ❌ Forgetting that swapping rows changes the sign
    βœ… Every swap multiplies by βˆ’1-1
      • ❌ Pulling a scalar out of the whole determinant instead of out of one row/column
    βœ… Track where the factor comes from
      • ❌ Missing proportional rows/columns before computing
    βœ… Always inspect structure first
    ---

    CMI Strategy

    πŸ’‘ How to Use Properties Efficiently

    • Before expanding, inspect rows and columns.

    • Check for equality, proportionality, or zeros.

    • Use row/column addition to create sparse structure.

    • Track sign changes carefully under swaps.

    • Use properties to avoid unnecessary calculation.

    ---

    Practice Questions

    :::question type="MCQ" question="If two rows of a determinant are interchanged, the determinant" options=["does not change","changes sign","becomes zero","doubles"] answer="B" hint="Recall the basic row-swap property." solution="Interchanging two rows multiplies the determinant by βˆ’1-1. Hence the correct option is B\boxed{B}." ::: :::question type="NAT" question="If one row of a determinant is multiplied by 55, the determinant is multiplied by" answer="5" hint="Use the scaling property." solution="Multiplying one row by 55 multiplies the determinant by 5\boxed{5}." ::: :::question type="MSQ" question="Which of the following are true?" options=["If two columns are equal, the determinant is zero","Adding a multiple of one row to another row changes the determinant","A triangular determinant equals the product of the diagonal entries","If a row is all zero, the determinant is zero"] answer="A,C,D" hint="Check which operations preserve the determinant." solution="1. True.
  • False. That operation leaves the determinant unchanged.
  • True.
  • True.
  • Hence the correct answer is A,C,D\boxed{A,C,D}." ::: :::question type="SUB" question="Prove that if two rows of a determinant are equal, then the determinant is zero." answer="Use the sign-change property under row interchange." hint="Swap the two equal rows." solution="Let DD be a determinant with two equal rows. Now interchange these two equal rows. Since the rows are equal, the numerical entries of the determinant do not change, so the determinant is still DD. But by the row-interchange property, swapping two rows changes the sign of the determinant. Therefore the new determinant must be βˆ’D-D. Hence we have D=βˆ’D\qquad D=-D So 2D=0\qquad 2D=0 and therefore D=0\qquad D=0 Thus, if two rows of a determinant are equal, the determinant must be 0\boxed{0}." ::: ---

    Summary

    ❗ Key Takeaways for CMI

    • Determinant properties are often more useful than direct expansion.

    • Swaps change sign, scaling changes magnitude, and row addition preserves value.

    • Dependence among rows or columns forces determinant zero.

    • Triangular determinants are easy because they reduce to diagonal products.

    • Structural inspection should come before computation.

    ---

    Chapter Summary

    ❗ Determinants β€” Key Points

    • A determinant is a scalar value associated with a square matrix, encapsulating properties related to linear transformations, such as scaling factor and invertibility.

    • Determinants of order 2 are calculated as adβˆ’bcad-bc for (abcd)\begin{pmatrix} a & b \\ c & d \end{pmatrix}. For order 3, they are evaluated using cofactor expansion along any row or column.

    • The cofactor CijC_{ij} of an element aija_{ij} is (βˆ’1)i+jMij(-1)^{i+j}M_{ij}, where MijM_{ij} is the minor (determinant of the submatrix obtained by deleting row ii and column jj).

    • Key properties of determinants include: det⁑(AT)=det⁑(A)\det(A^T) = \det(A), det⁑(AB)=det⁑(A)det⁑(B)\det(AB) = \det(A)\det(B), and det⁑(kA)=kndet⁑(A)\det(kA) = k^n \det(A) for an nΓ—nn \times n matrix AA.

    • Elementary row/column operations (adding a multiple of one row/column to another) do not change the determinant's value, which is crucial for simplification.

    • A determinant is zero if any two rows or columns are identical or proportional, if any row or column consists entirely of zeros, or if rows/columns are linearly dependent.

    ---

    Chapter Review Questions

    :::question type="MCQ" question="Given that ∣abcdefghi∣=5\begin{vmatrix} a & b & c \\ d & e & f \\ g & h & i \end{vmatrix} = 5, what is the value of ∣a+2db+2ec+2fdefgβˆ’dhβˆ’eiβˆ’f∣\begin{vmatrix} a+2d & b+2e & c+2f \\ d & e & f \\ g-d & h-e & i-f \end{vmatrix}?" options=["-5","0","5","10"] answer="5" hint="Apply elementary row operations and their effect on the determinant value." solution="Let D=∣abcdefghi∣D = \begin{vmatrix} a & b & c \\ d & e & f \\ g & h & i \end{vmatrix}.
    The given determinant is Dβ€²=∣a+2db+2ec+2fdefgβˆ’dhβˆ’eiβˆ’f∣D' = \begin{vmatrix} a+2d & b+2e & c+2f \\ d & e & f \\ g-d & h-e & i-f \end{vmatrix}.
    Apply the row operation R1β†’R1βˆ’2R2R_1 \to R_1 - 2R_2: The value of the determinant remains unchanged.
    Dβ€²=∣abcdefgβˆ’dhβˆ’eiβˆ’f∣D' = \begin{vmatrix} a & b & c \\ d & e & f \\ g-d & h-e & i-f \end{vmatrix}.
    Apply the row operation R3β†’R3+R2R_3 \to R_3 + R_2: The value of the determinant remains unchanged.
    Dβ€²=∣abcdefghi∣=DD' = \begin{vmatrix} a & b & c \\ d & e & f \\ g & h & i \end{vmatrix} = D.
    Since D=5D=5, the value of the new determinant is 5."
    :::

    :::question type="NAT" question="Find the positive value of xx for which ∣x218x∣=∣62186∣\begin{vmatrix} x & 2 \\ 18 & x \end{vmatrix} = \begin{vmatrix} 6 & 2 \\ 18 & 6 \end{vmatrix}." answer="6" hint="Evaluate both determinants and set them equal." solution="The left determinant is xβ‹…xβˆ’2β‹…18=x2βˆ’36x \cdot x - 2 \cdot 18 = x^2 - 36.
    The right determinant is 6β‹…6βˆ’2β‹…18=36βˆ’36=06 \cdot 6 - 2 \cdot 18 = 36 - 36 = 0.
    Setting them equal: x2βˆ’36=0β€…β€ŠβŸΉβ€…β€Šx2=36x^2 - 36 = 0 \implies x^2 = 36.
    Thus, x=Β±6x = \pm 6. The positive value of xx is 6."
    :::

    :::question type="MCQ" question="If AA is a 3Γ—33 \times 3 matrix such that det⁑(A)=4\det(A) = 4, then det⁑(2A)\det(2A) equals:" options=["4","8","16","32"] answer="32" hint="Recall the property det⁑(kA)=kndet⁑(A)\det(kA) = k^n \det(A) for an nΓ—nn \times n matrix AA." solution="For an nΓ—nn \times n matrix AA and a scalar kk, we have det⁑(kA)=kndet⁑(A)\det(kA) = k^n \det(A).
    Here, AA is a 3Γ—33 \times 3 matrix, so n=3n=3. The scalar is k=2k=2.
    Therefore, det⁑(2A)=23det⁑(A)=8Γ—4=32\det(2A) = 2^3 \det(A) = 8 \times 4 = 32."
    :::

    :::question type="NAT" question="If the points (a,0)(a, 0), (0,b)(0, b), and (1,1)(1, 1) are collinear, what is the value of aba+b\frac{ab}{a+b}? (Assume a,bβ‰ 0a,b \neq 0)" answer="1" hint="Points are collinear if the area of the triangle formed by them is zero. Use the determinant formula for area." solution="The area of a triangle with vertices (x1,y1)(x_1, y_1), (x2,y2)(x_2, y_2), and (x3,y3)(x_3, y_3) is given by 12∣∣x1y11x2y21x3y31∣∣\frac{1}{2} \left| \begin{vmatrix} x_1 & y_1 & 1 \\ x_2 & y_2 & 1 \\ x_3 & y_3 & 1 \end{vmatrix} \right|.
    For collinear points, the area is 0. So, ∣a010b1111∣=0\begin{vmatrix} a & 0 & 1 \\ 0 & b & 1 \\ 1 & 1 & 1 \end{vmatrix} = 0.
    Expanding along the first row:
    a(bβ‹…1βˆ’1β‹…1)βˆ’0(0β‹…1βˆ’1β‹…1)+1(0β‹…1βˆ’bβ‹…1)=0a(b \cdot 1 - 1 \cdot 1) - 0(0 \cdot 1 - 1 \cdot 1) + 1(0 \cdot 1 - b \cdot 1) = 0
    a(bβˆ’1)βˆ’0+1(βˆ’b)=0a(b-1) - 0 + 1(-b) = 0
    abβˆ’aβˆ’b=0ab - a - b = 0
    ab=a+bab = a + b.
    Since a,b≠0a,b \neq 0, we can divide by a+ba+b (which also implies a+b≠0a+b \neq 0 if ab≠0ab \neq 0) and abab:
    aba+b=1\frac{ab}{a+b} = 1."
    :::

    ---

    What's Next?

    πŸ’‘ Continue Your CMI Journey

    Determinants are not isolated concepts; they form a cornerstone for several advanced topics. Your understanding here will be crucial when you delve into the properties and operations of Matrices, where determinants define concepts like invertibility and eigenvalues. In Vectors, determinants are used to compute cross products (area of a parallelogram) and scalar triple products (volume of a parallelepiped), providing geometric insights. Furthermore, in 3D Geometry, determinants play a key role in representing equations of planes, lines, and verifying coplanarity of points and vectors. Master these concepts to build a strong foundation for your CMI journey.

    🎯 Key Points to Remember

    • βœ“ Master the core concepts in Determinants before moving to advanced topics
    • βœ“ Practice with previous year questions to understand exam patterns
    • βœ“ Review short notes regularly for quick revision before exams

    Related Topics in Vectors, Matrices and 3D Geometry

    More Resources

    Why Choose MastersUp?

    🎯

    AI-Powered Plans

    Personalized study schedules based on your exam date and learning pace

    πŸ“š

    15,000+ Questions

    Verified questions with detailed solutions from past papers

    πŸ“Š

    Smart Analytics

    Track your progress with subject-wise performance insights

    πŸ”–

    Bookmark & Revise

    Save important questions for quick revision before exams

    Start Your Free Preparation β†’

    No credit card required β€’ Free forever for basic features