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Perplex
Perplex
  • Dashboard
Topics
Exponents & LogarithmsRounding & ErrorSequences & SeriesFinancial MathematicsMatricesComplex Numbers
Cartesian plane & linesFunction TheoryModellingTransformations & asymptotes
2D & 3D GeometryVoronoi DiagramsTrig equations & identitiesVectorsGraph Theory
ProbabilityDescriptive StatisticsBivariate StatisticsDistributions & Random VariablesInference & Hypotheses
DifferentiationIntegrationDifferential Equations
Paper 3
Plus
Calculator Skills
Review VideosFormula BookletAll Study Sets
BlogLanding Page
Sign UpLogin
Perplex
/
Matrices
/
Foundations of Matrices
Identity, Inverses & Determinants
Foundations of Matrices
Matrices

Foundations of Matrices

0 of 0 exercises completed

Matrix notation and order ​m×n, together with addition and subtraction of matrices of the same order, scalar multiplication, matrix multiplication and its required dimensions, the zero matrix, and the properties of multiplication including non-commutativity, associativity and distributivity, with calculator use for numeric matrices.

Want a deeper conceptual understanding? Try our interactive lesson!

Matrix notation
AHL AI 1.14

A matrix is simply a rectangular array of numbers written in rows and columns. For example, the matrix

<ul>
<li>A purple rectangular array enclosed in round brackets with two horizontal rows of three entries each.</li>
<li>Left-side labels: “row 1” aligned with the top row and “row 2” aligned with the bottom row.</li>
<li>Slanted labels above the array: “col1”, “col2”, “col3” positioned over the first, second, and third columns.</li>
<li>Entries:
<ul>
<li>Top row: 1, a, π</li>
<li>Bottom row: x, −5, 0</li>
</ul>
</li>
<li>Variables (a, x) and symbols (π) are in the same purple color as the numbers and labels.</li>
</ul>

has ​2​ rows and ​3​ columns. We can reference a specific entry using the notation ​Mi,j​​ where ​i​ is the row and ​j​ the column. For example, ​M1,3​​ is the first row and thirs column, which is ​π.

Order of a matrix
AHL AI 1.14

The order of a matrix denotes its dimensions. We say a matrix has order ​n×m​ (read "​n​ by ​m​") to denote that it has ​n​ rows and ​m​ columns. For example, the matrix

<ul>
<li>A 2-by-3 matrix written with round parentheses, containing six lowercase entries arranged as:
<ul>
<li>First row: a, b, c</li>
<li>Second row: d, e, f</li>
</ul>
</li>
<li>A curly brace above spans the three columns and is labeled “3 columns.”</li>
<li>A curly brace to the right spans the two rows and is labeled “2 rows.”</li>
<li>All elements, braces, and labels are in purple.</li>
</ul>

has order ​2×3.

Adding & subtracting matrices
AHL AI 1.14

When matrices have the same order ​m×n, we can add or subtract them by simply adding or subtracting the components:

​
(13​24​)+(57​68​)=(1+53+7​2+64+8​)=(610​812​)
​
Scalar multiplication of a matrix
AHL AI 1.14

We can multiply a matrix by a scalar by simply multiplying each entry by a scalar:

​
2(13​24​)=(2×12×3​2×22×4​)=(26​48​)
​
Matrix multiplication
AHL AI 1.14

If ​A​ has order ​m×n​ and ​B​ has order ​n×p, then the product ​AB​ is defined and will have order ​m×p. 

<ul>
<li>A typographic expression: (m × n)(n × p) → (m × p).</li>
<li>The n in the first parenthesis is outlined with a purple rectangle.</li>
<li>Two large purple curved arrows sweep around the expression: one above and one below, both curving from the left side toward the right side near the arrow pointing to (m × p).</li>
</ul>

For matrix multiplication in general, the number of columns in the first matrix must equal the number of rows in the second matrix.


Each entry of ​AB​ is the dot product of a row of ​A​ with a column of ​B.

For example, if we multiply a ​2×2​ matrix ​A​ by a ​2×3​ matrix ​B, the product will be ​2×3:

​
(13​24​)(58​69​710​)  ​=(1⋅5+2⋅83⋅5+4⋅8​1⋅6+2⋅93⋅6+4⋅9​1⋅7+2⋅103⋅7+4⋅10​) =(2147​2454​2761​)​
​

<ul>
<li>Center: a 3×3 matrix multiplied by a 3×2 matrix equals a 3×2 matrix.
<ul>
<li>Left matrix: rows are (2, 0, 2), (1, 3, 0), (1, 1, 2). The first row is outlined in orange; the third row is outlined in blue.</li>
<li>Right matrix: columns are (1, 0, 0) and (2, 1, 0). The first column is outlined in orange; the second column is outlined in blue.</li>
<li>Resulting matrix shown as
( 2  4
1  5
1  3 )
with the entry 2 at the top-left colored/orange and the entry 3 at the bottom-right colored/blue.</li>
</ul>
</li>
<li>Top: an orange dot-product computation (2, 0, 2) · (1, 0, 0) = 2 with an orange arrow pointing down to the orange 2 in the result.</li>
<li>Bottom: a blue dot-product computation (1, 1, 2) · (2, 1, 0) = 3 with a blue arrow pointing up to the blue 3 in the result.</li>
<li>Color-coding links: orange highlights pair the first row (left) with the first column (right) and its resulting entry; blue highlights pair the third row with the second column and its resulting entry.</li>
</ul>
Matrix multiplication is not commutative
AHL AI 1.14

In general, for matrices ​A​ and ​B,

​
AB=BA
​

Note: this does not mean ​AB​ is never equal to ​BA, just that it is not in general.

Matrix multiplication is associative
AHL AI 1.14

For all matrices ​A,B​ and ​C, it is true that

​
A(BC)=(AB)C
​
Matrix multiplication is distributive
AHL AI 1.14

For all matrices ​A,B​ and ​C, it is true that

​
A(B+C)=AB+AC
​
Zero Matrix
AHL AI 1.14

A matrix with all ​0​ entries is called the "zero" matrix, regardless of order. We denote it ​0.

​
0=(00​00​00​)
​
Matrix math with technology
AHL AI 1.14

When you have matrices with only numbers and no parameters (eg ​k​), you can add, multiply, and find powers of matrices using your calculator.

Nice work completing Foundations of Matrices, here's a quick recap of what we covered:

Skills covered

Mixed Practice

Exercises checked off

I'm Plex, here to help you understand this concept!
/
Matrices
/
Foundations of Matrices
Identity, Inverses & Determinants
Foundations of Matrices
Matrices

Foundations of Matrices

0 of 0 exercises completed

Matrix notation and order ​m×n, together with addition and subtraction of matrices of the same order, scalar multiplication, matrix multiplication and its required dimensions, the zero matrix, and the properties of multiplication including non-commutativity, associativity and distributivity, with calculator use for numeric matrices.

Want a deeper conceptual understanding? Try our interactive lesson!

Matrix notation
AHL AI 1.14

A matrix is simply a rectangular array of numbers written in rows and columns. For example, the matrix

<ul>
<li>A purple rectangular array enclosed in round brackets with two horizontal rows of three entries each.</li>
<li>Left-side labels: “row 1” aligned with the top row and “row 2” aligned with the bottom row.</li>
<li>Slanted labels above the array: “col1”, “col2”, “col3” positioned over the first, second, and third columns.</li>
<li>Entries:
<ul>
<li>Top row: 1, a, π</li>
<li>Bottom row: x, −5, 0</li>
</ul>
</li>
<li>Variables (a, x) and symbols (π) are in the same purple color as the numbers and labels.</li>
</ul>

has ​2​ rows and ​3​ columns. We can reference a specific entry using the notation ​Mi,j​​ where ​i​ is the row and ​j​ the column. For example, ​M1,3​​ is the first row and thirs column, which is ​π.

Order of a matrix
AHL AI 1.14

The order of a matrix denotes its dimensions. We say a matrix has order ​n×m​ (read "​n​ by ​m​") to denote that it has ​n​ rows and ​m​ columns. For example, the matrix

<ul>
<li>A 2-by-3 matrix written with round parentheses, containing six lowercase entries arranged as:
<ul>
<li>First row: a, b, c</li>
<li>Second row: d, e, f</li>
</ul>
</li>
<li>A curly brace above spans the three columns and is labeled “3 columns.”</li>
<li>A curly brace to the right spans the two rows and is labeled “2 rows.”</li>
<li>All elements, braces, and labels are in purple.</li>
</ul>

has order ​2×3.

Adding & subtracting matrices
AHL AI 1.14

When matrices have the same order ​m×n, we can add or subtract them by simply adding or subtracting the components:

​
(13​24​)+(57​68​)=(1+53+7​2+64+8​)=(610​812​)
​
Scalar multiplication of a matrix
AHL AI 1.14

We can multiply a matrix by a scalar by simply multiplying each entry by a scalar:

​
2(13​24​)=(2×12×3​2×22×4​)=(26​48​)
​
Matrix multiplication
AHL AI 1.14

If ​A​ has order ​m×n​ and ​B​ has order ​n×p, then the product ​AB​ is defined and will have order ​m×p. 

<ul>
<li>A typographic expression: (m × n)(n × p) → (m × p).</li>
<li>The n in the first parenthesis is outlined with a purple rectangle.</li>
<li>Two large purple curved arrows sweep around the expression: one above and one below, both curving from the left side toward the right side near the arrow pointing to (m × p).</li>
</ul>

For matrix multiplication in general, the number of columns in the first matrix must equal the number of rows in the second matrix.


Each entry of ​AB​ is the dot product of a row of ​A​ with a column of ​B.

For example, if we multiply a ​2×2​ matrix ​A​ by a ​2×3​ matrix ​B, the product will be ​2×3:

​
(13​24​)(58​69​710​)  ​=(1⋅5+2⋅83⋅5+4⋅8​1⋅6+2⋅93⋅6+4⋅9​1⋅7+2⋅103⋅7+4⋅10​) =(2147​2454​2761​)​
​

<ul>
<li>Center: a 3×3 matrix multiplied by a 3×2 matrix equals a 3×2 matrix.
<ul>
<li>Left matrix: rows are (2, 0, 2), (1, 3, 0), (1, 1, 2). The first row is outlined in orange; the third row is outlined in blue.</li>
<li>Right matrix: columns are (1, 0, 0) and (2, 1, 0). The first column is outlined in orange; the second column is outlined in blue.</li>
<li>Resulting matrix shown as
( 2  4
1  5
1  3 )
with the entry 2 at the top-left colored/orange and the entry 3 at the bottom-right colored/blue.</li>
</ul>
</li>
<li>Top: an orange dot-product computation (2, 0, 2) · (1, 0, 0) = 2 with an orange arrow pointing down to the orange 2 in the result.</li>
<li>Bottom: a blue dot-product computation (1, 1, 2) · (2, 1, 0) = 3 with a blue arrow pointing up to the blue 3 in the result.</li>
<li>Color-coding links: orange highlights pair the first row (left) with the first column (right) and its resulting entry; blue highlights pair the third row with the second column and its resulting entry.</li>
</ul>
Matrix multiplication is not commutative
AHL AI 1.14

In general, for matrices ​A​ and ​B,

​
AB=BA
​

Note: this does not mean ​AB​ is never equal to ​BA, just that it is not in general.

Matrix multiplication is associative
AHL AI 1.14

For all matrices ​A,B​ and ​C, it is true that

​
A(BC)=(AB)C
​
Matrix multiplication is distributive
AHL AI 1.14

For all matrices ​A,B​ and ​C, it is true that

​
A(B+C)=AB+AC
​
Zero Matrix
AHL AI 1.14

A matrix with all ​0​ entries is called the "zero" matrix, regardless of order. We denote it ​0.

​
0=(00​00​00​)
​
Matrix math with technology
AHL AI 1.14

When you have matrices with only numbers and no parameters (eg ​k​), you can add, multiply, and find powers of matrices using your calculator.

Nice work completing Foundations of Matrices, here's a quick recap of what we covered:

Skills covered

Mixed Practice

Exercises checked off

I'm Plex, here to help you understand this concept!

Generating starter questions...

1 free

Generating starter questions...

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