Which statement best describes the parity method of error detection used in digital communication links?

Introduction / Context:
Parity is a classic, low-overhead error-detection technique. Systems append one parity bit to a data word to enforce an overall even or odd count of 1s. Understanding what parity can and cannot detect is essential for selecting appropriate integrity checks.

Given Data / Assumptions:

• We consider single parity (even or odd), not more advanced codes.
• Transmission errors are modeled as bit flips.
• Goal is detection, not correction.

Concept / Approach:
With even parity, the transmitter sets the parity bit so the total number of 1s is even. The receiver recomputes parity; a mismatch indicates an error. Single-bit errors flip parity from even to odd (or vice versa) and are always detected. However, two-bit errors restore the original parity and therefore evade detection. Parity does not provide error correction; it only flags potential corruption.

Step-by-Step Solution:
1) Define parity rule (even or odd) across data + parity bit.2) Transmit data; compute parity at receiver.3) If exactly one bit flips, parity mismatches → error detected.4) If two bits flip, parity may match → error not detected.

Verification / Alternative check:
Truth tables show that parity detects all odd-numbered bit errors and misses even-numbered bit errors. Therefore, it is best for single-bit error detection but not double-bit detection.

Why Other Options Are Wrong:
(b) Double-bit errors are not reliably detected.

(c) False; parity excels at single-bit detection.

(d) Parity does not correct errors; codes like Hamming are needed for correction.

(e) It does not correct automatically; it only detects odd-error counts.

Common Pitfalls:
Overestimating parity's power. For stronger guarantees, use CRCs or ECC like Hamming, BCH, or Reed–Solomon.

Final Answer:
Parity checking is best suited for detecting single-bit errors in transmitted codes.