A rectangle has a length of 64 inches and a width of 32 inches. What is the area, in square...
GMAT Geometry & Trigonometry : (Geo_Trig) Questions
A rectangle has a length of \(64\) inches and a width of \(32\) inches. What is the area, in square inches, of the rectangle?
Solution
The area of a rectangle is calculated using the formula:
\(\mathrm{Area} = \mathrm{Length} \times \mathrm{Width}\)
\(\mathrm{Area} = 64 \times 32\)
\(\mathrm{Area} = 2048\)
The area of the rectangle is \(2048\) square inches.
1. TRANSLATE the problem information
- Given information:
- Length of rectangle = 64 inches
- Width of rectangle = 32 inches
- Need to find: Area in square inches
2. INFER the approach
- Since we need the area of a rectangle and have both dimensions, we should use the rectangle area formula
- The area formula will give us a direct path to the answer
3. Apply the area formula
- Rectangle area formula: \(\mathrm{A = length \times width}\)
- Substitute the known values: \(\mathrm{A = 64 \times 32}\)
- Calculate: \(\mathrm{A = 2048}\)
Answer: 2048 square inches
Why Students Usually Falter on This Problem
Most Common Error Path:
Conceptual confusion: Students mix up area and perimeter formulas
Some students remember rectangle formulas but confuse which one to use. They might calculate perimeter instead: \(\mathrm{P = 2(length + width) = 2(64 + 32) = 2(96) = 192}\). This leads to selecting an incorrect answer or confusion when 192 doesn't appear among typical answer choices.
Second Most Common Error:
Weak SIMPLIFY execution: Arithmetic errors in multiplication
Students know the correct formula but make computational mistakes when calculating \(\mathrm{64 \times 32}\). Common errors include getting 1024 (mixing up place values) or other incorrect products. This causes them to select wrong answer choices or abandon their systematic approach.
The Bottom Line:
This problem tests whether students can distinguish between area and perimeter concepts and execute basic multiplication accurately. Success requires both conceptual clarity and computational precision.