Matrix Multiplication: a complete example
A 2×3 matrix times a 3×2 matrix produces a 2×2 matrix. This Matrix Multiplication example can be compared with vector action.
Multiply compatible matrices using row-by-column dot products. Formula and matrix product remain visible in one place for independent verification.
A 2×3 matrix times a 3×2 matrix produces a 2×2 matrix. This Matrix Multiplication example can be compared with vector action.
A matrix product AB exists when A has as many columns as B has rows; each result entry is a row-column dot product.
Reading matrix product correctly starts with the mathematical structure described here.
Write the output dimensions, pair every A row with every B column, multiply components, and add.
AB usually differs from BA, and BA may not even be dimensionally defined. If the Matrix Multiplication assumptions do not fit, consider repeated product.
Reversing the displayed steps offers a quick independent check on this matrix multiplication result.
Composition of transformations, linear systems, graphics, networks, and Markov models relies on multiplication.
The input labels—matrix a and matrix b—encode the model used on this page. Write those labels beside source values when transferring a problem from paper or a spreadsheet. That small step catches transposed quantities and mixed units before they become a polished-looking matrix product.
Changing an interior dimension invalidates the product unless the other matrix changes with it. A one-field trial makes this relationship visible without reworking the entire example.
Choose rounding after considering how the result will be used. Comparison may need only a few significant digits, while a later multi-step calculation benefits from carrying more. In either case, retain the page's formula with the matrix product so the underlying definition remains visible.
Matrix-vector multiplication is the one-column special case. The distinction determines whether this page fits the original question.
If the number moves into a spreadsheet, give its cell a matrix product heading and retain the source values matrix a and matrix b nearby. Context matters more than extra displayed digits.
The working inputs for Matrix Multiplication are Matrix A, and Matrix B. Confirm that A columns equal B rows, then recompute one output entry as a row of A dotted with a column of B.
For Matrix Multiplication, record pivot choices and any row swaps when elimination affects the result.
A matrix product AB exists when A has as many columns as B has rows; each result entry is a row-column dot product.
Composition of transformations, linear systems, graphics, networks, and Markov models relies on multiplication.
AB usually differs from BA, and BA may not even be dimensionally defined.
Write the output dimensions, pair every A row with every B column, multiply components, and add.