All three results can be useful. The intended output shape decides which operation belongs in your script.
State what the three positions represent
This original fictional calculation pairs three measured readings with three corresponding calibration factors. The source contract says position 1 pairs with position 1, and similarly for positions 2 and 3:
readings = [2 4 6];
factors = [10 20 30];
calibrated = readings .* factors;
assert(isequal(size(calibrated), [1 3]));
assert(isequal(calibrated, [20 80 180]));
The expected products are 2×10, 4×20 and 6×30. These authored values can expose a wrong operation without requiring the full measurement file. No claim is made that ChatGPT or MATLAB executed this snippet here.
MathWorks' array-versus-matrix operations documentation, checked October 24, 2026, distinguishes elementwise operations from linear-algebra operations. For matrix multiplication, the left operand's column count must match the right operand's row count. Two 1-by-3 rows do not meet that condition for readings * factors.
A transpose can change the question
For these real-valued inputs, factors.' changes the row to a column without conjugation:
factor_column = factors.';
dot_total = readings * factor_column;
expanded = readings .* factor_column;
The expected dot_total is 280: one sum of the three matching products. That scalar loses the per-sample values required by the calibration task.
In MATLAB versions supporting implicit expansion, expanded has size 3-by-3. Each factor in the column multiplies every reading in the row:
20 40 60
40 80 120
60 120 180
Adding a dot before the asterisk therefore does not by itself guarantee the right fix. A shape assertion catches nine values where the task requires three, even though the elementwise expression is valid. On an older MATLAB version without this implicit expansion behavior, the shape mismatch can instead produce an error; include the actual version in your request.
Request a dimension trace and sample assertions
Review this MATLAB multiplication expression.
MATLAB version: [ENTER]
Small input definitions, actual size output and exact expression: [PASTE]
Meaning and ordering of each dimension: [ENTER]
Required output size and one expected value: [ENTER]
Inputs real or complex: [ENTER]
Explain the dimensions at each operation. Distinguish matrix product,
elementwise product, dot product and any implicit expansion that the
actual version supports. Propose the smallest correction matching the
stated meaning. Keep sample identities and ordering unchanged; do not
transpose or reshape merely to remove an error. Include size and
value assertions. State unresolved pairing rules before writing code.
Do not claim a MATLAB run or a tested performance improvement.
For complex data, state whether a transpose should conjugate; do not generalize this real-valued example to a different mathematical contract.
Run the assertions in the actual script after applying the accepted expression. If sample IDs arrive in different orders, settle their pairing before multiplying: matching lengths cannot prove matching records. The pandas alignment guide illustrates that identity problem in a different data structure. For this MATLAB task, keep the 1-by-3 shape and the three expected products beside the maintained calculation.