Example 21: Verify
If
verify that .
. Hence verified.
Want the reason behind every step, the basics and the checks?
The transpose of a product is the product of the transposes in the reverse order: , not . The orders tell the story. is and is , so is . Their transposes are and , so is again , while would be only . Only the reversed product can match.
- Given
- A column matrix of order and a row matrix of order .
- To show
- .
- Plan
- (1) Check is defined and compute all nine entries. (2) Transpose it. (3) Separately find , and compute all nine entries of . (4) Compare entry by entry.
Basics you need
is defined when the number of columns of equals the number of rows of . If is and is , then is . Basics: pair up, multiply, add
The entry of is row of times column of : multiply matching entries and add. When the inner size is 1, each row and column has a single entry, so each entry of is just one product .
is with rows turned into columns; its entry is . The transpose of a column is a row and vice versa. Basics: reading a table sideways
Solution
Check that is defined and find its order
is and is . The number of columns of (which is 1) equals the number of rows of (also 1), so is defined, and its order is (rows of ) (columns of ) .
A product can only be formed when each row of the first matrix has exactly as many entries as each column of the second, so that they can be paired off. Checking the orders first also tells us the shape of the answer before we compute anything.Compute all nine entries of
Row of is the single number and column of is the single number , so . With , , and , , :
With an inner size of 1, "row times column" has only one pair to multiply, so there is nothing to add. Row of is therefore times the row : row 1 is times , and so on. Watch the signs: .Transpose : the left side
is , so is . Row 1 of () becomes column 1, row 2 () becomes column 2, and row 3 () becomes column 3:
For a square matrix the order does not change under transpose, but the entries off the main diagonal swap across it: the entry of becomes the entry of . The diagonal entries stay in place.Find and , and check is defined
The column becomes a row, and the row becomes a column:
is and is : the columns of (1) match the rows of (1), so is defined and has order , the same as .
Checking the order now is a first test of the rule: if were not it could not possibly equal . It also shows why the reverse order is needed (see the Common mistakes box).Compute all nine entries of : the right side
Write for the entry. Each is (entry of the column ) times (entry of the row ):
This is computed from scratch, without looking at , so the comparison in the next step is a real check rather than a copy.Compare
Both matrices are , and all nine entries agree: row 1 is , row 2 is , row 3 is in each. Hence .
Why it works in general: the entry of is the entry of , that is . The entry of is . These are the same products of numbers, only written in the other order, and multiplication of numbers is commutative.Property (iv) of Section 3.5.1: .
The property is verified for the given and .
A quick sum test: the nine entries of add up to , and so do the nine entries of , as they must, since transposing only moves entries. More directly, multiplies "each entry of " by "each entry of ": the sum of all entries is . Both checks agree.
- Writing . Here is and is , so is : it equals . A matrix cannot equal a one. The order of the factors must reverse.
- Thinking a column times a row is a single number. A matrix times a matrix is . It is ( times ) that is .
- Sign slips. and are positive.
- Transpose reverses products: . Like taking off socks and shoes, the last thing done is the first undone.
- Always check orders. They tell you at once that cannot be the answer here.
- A column times a row (an "outer product") gives a full matrix whose entry is simply .
Every fact used, and where it comes from
| Fact | Used in | Source |
|---|---|---|
| Column and row matrices; order | Steps 1, 4 | Sections 3.2.1 and 3.3 (Lesson: types of matrices) |
| defined when columns of = rows of ; order ; entry rule | Steps 1, 2, 4, 5 | Section 3.4.5 (Lesson: matrix multiplication) |
| Transpose | Steps 3, 4 | Definition 3, Section 3.5 (Lesson: transpose) |
| Equal matrices: same order, equal entries | Step 6 | Definition 2, Section 3.3.1 |
| Step 6 | Section 3.5.1, property (iv) |
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