Matrices of the same order are added or subtracted entry by entry: (A±B)ij=aij±bij. A scalar k multiplies every entry: (kA)ij=kaij.
The transposeA′ swaps rows and columns; an m×n matrix becomes n×m, and (A′)′=A.
A square matrix is symmetric if A′=A and skew-symmetric if A′=−A (forcing all diagonal entries to 0). Every square matrix splits uniquely into a symmetric part 21(A+A′) and a skew-symmetric part 21(A−A′) whose sum is A again — a standard construction worth being able to reproduce from scratch.
Apply the row-by-column rule to each of the four entries of the product.
AB=(410612).
Each entry is a row of A dotted with a column of B.
✓Final answer
AB=(410612).
Both matrices are 2×2, so AB exists and is 2×2. Using the row-by-column rule: AB=(1(2)+2(1)3(2)+4(1)1(0)+2(3)3(0)+4(3))=(2+26+40+60+12)=(410612).
Verification of the (2,1) entry. Row 2 of A is (3,4) and column 1 of B is (2,1): 3(2)+4(1)=6+4=10, matching the value above.
✓Final answer
AB=(410612).
A frequent slip is to multiply entrywise (like addition), giving 12, 20, etc. Matrix multiplication is row-by-column: each product entry is a SUM of products, not a single product.