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Minor (linear algebra)

Minor (linear algebra) is a mathematics topic covered in the lgStudy science library. This page brings together a partial reference excerpt, illustrations, worked examples, real-world applications and a short study plan, so you can understand Minor (linear algebra) rather than just read about it. In short: In linear algebra, a minor of a matrix A is the determinant of some smaller square matrix generated from A by removing one or more of its rows and columns. Minors obtained by removing just one row and one column from square matrices (first minors) are useful for calculating matrix cofactors, which are useful for computing both the determinant and inverse of square matrices.

Key takeaways

  • Minor (linear algebra) belongs to mathematics; place it in that map before memorising details.
  • Learn the definition first, then one example that makes the definition concrete.
  • Connect Minor (linear algebra) to a quantity you can measure, compute or draw — that is where exam questions come from.
  • Reproduce the core statement of Minor (linear algebra) from memory before moving on to harder problems.

Reference excerpt

In linear algebra, a minor of a matrix A is the determinant of some smaller square matrix generated from A by removing one or more of its rows and columns. Minors obtained by removing just one row and one column from square matrices (first minors) are useful for calculating matrix cofactors, which are useful for computing both the determinant and inverse of square matrices. The requirement that the square matrix be smaller than the original matrix is often omitted in the definition. The cofactors C i j {\displaystyle C_{ij}} are also the partial derivatives with respect to the matrix entries of the determinant map det : Mat ( n , R ) → R {\displaystyle {\text{det}}:{\text{Mat}}(n,\mathbb {R} )\to \mathbb {R} } which takes a matrix ( a i , j ) i , j ∈ { 1 , … , n } {\displaystyle (a_{i,j})_{i,j\in \{1,\dots ,n\}}} to its determinant:

d ( det ) d a i j = C i j {\displaystyle {\frac {{\text{d}}({\text{det}})}{{\text{d}}a_{ij}}}=C_{ij}}

Definition and illustration

First minors If A is a square matrix, then the minor of the entry in the i-th row and j-th column (also called the (i, j) minor, or a first minor) is the determinant of the submatrix formed by deleting the i-th row and j-th column. This number is often denoted Mi, j. The (i, j) cofactor is obtained by multiplying the minor by (−1)i + j, and is often denoted Ci, j. To illustrate these definitions, consider the following 3 × 3 matrix,

[ 1 4 7 3 0 5 − 1 9 11 ] {\displaystyle {\begin{bmatrix}1&4&7\\3&0&5\\-1&9&11\\\end{bmatrix}}}

To compute the minor M2,3 and the cofactor C2,3, we find the determinant of the above matrix with row 2 and column 3 removed.

M 2 , 3 = det [ 1 4 ◻ ◻ ◻ ◻ − 1 9 ◻ ] = det [ 1 4 − 1 9 ] = 9 − ( − 4 ) = 13 {\displaystyle M_{2,3}=\det {\begin{bmatrix}1&4&\Box \\\Box &\Box &\Box \\-1&9&\Box \\\end{bmatrix}}=\det {\begin{bmatrix}1&4\\-1&9\\\end{bmatrix}}=9-(-4)=13}

So the cofactor of the (2,3) entry is

C 2 , 3 = ( − 1 ) 2 + 3 ( M 2 , 3 ) = − 13. {\displaystyle C_{2,3}=(-1)^{2+3}(M_{2,3})=-13.}

… excerpt ends here. Continue reading the full article.

Worked examples

Example 1 — a first encounter with Minor (linear algebra)

Start with the simplest possible case. Write down what Minor (linear algebra) claims or describes in one sentence, then invent the smallest concrete situation in which that sentence is true. In mathematics, the smallest case is usually a single object, a single equation or a single measurement. Check that every symbol or term in your sentence has a meaning in that case.

Example 2 — changing one variable

Take the situation from Example 1 and change exactly one quantity: double it, halve it, or set it to zero. Predict what should happen to Minor (linear algebra) before you calculate. Comparing your prediction with the result is the fastest way to find out whether you understand the idea or only the words.

Example 3 — an exam-style question

Typical questions about Minor (linear algebra) ask you to (a) state it precisely, (b) apply it to given data, and (c) explain a limitation. Practise writing all three answers in under five minutes; the third part is what separates a full-mark answer from an average one.

Applications of Minor (linear algebra)

In research
Minor (linear algebra) appears in mathematics research whenever the underlying quantities have to be modelled precisely. Papers usually cite it as a starting assumption and then explore where it breaks down.
In technology and industry
Engineering practice reuses Minor (linear algebra) in design rules, simulations and safety margins. Knowing the idea lets you read a specification sheet and understand why the numbers look the way they do.
In the classroom
Minor (linear algebra) is common in secondary-school and first-year university syllabi. It links to neighbouring topics Determinants, Matrix theory, so understanding it makes those chapters shorter.
In everyday life
Look for Minor (linear algebra) outside the textbook — in sport, cooking, traffic, electronics or the sky above you. An example you found yourself is remembered far longer than one you were given.
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How to study Minor (linear algebra) in 20 minutes

  1. Read the reference excerpt below once, without taking notes.
  2. Close the page and write down what Minor (linear algebra) means in your own words.
  3. Compare your version with the excerpt and mark what you missed.
  4. Work through the three examples above with pen and paper.
  5. Explain Minor (linear algebra) out loud to somebody else — or to Teacher Smith in the lgStudy chat.

Frequently asked questions

What is Minor (linear algebra) in simple terms?

In linear algebra, a minor of a matrix A is the determinant of some smaller square matrix generated from A by removing one or more of its rows and columns. Minors obtained by removing just one row and one column from square matrices (first minors) are useful for calculating matrix cofactors, which…

Why does Minor (linear algebra) matter?

Because it connects several mathematics ideas at once: it gives you a definition you can apply, a quantity you can calculate, and a way to check whether a result is plausible.

How should I study Minor (linear algebra)?

Read the excerpt, restate it from memory, then work through the examples and applications listed on this page. The five-step study plan above takes about twenty minutes.

What does this page cover?

It gives you a compact reference excerpt plus original lgStudy explanations, examples, applications and study material on Minor (linear algebra).

Tags

  • Determinants
  • Matrix theory

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