Distinguish between systematic error and random error in measurements.

• A. Systematic error is a consistent bias in measurements; random error varies unpredictably and averages out with repeated trials.
• B. Systematic error averages out with repeated trials; random error is a consistent bias.
• C. Both types of error can be eliminated by better instruments.
• D. Systematic error only occurs in theoretical measurements.

Answer: (A)

The main idea is how errors affect a measurement: bias versus precision. Systematic error is a consistent bias that shifts all measurements the same way, often due to instrument calibration, faulty procedure, or biased observation. It changes the reported values in the same direction every time. Random error, by contrast, comes from unpredictable fluctuations in the measurement process—tiny, moment-to-moment variations that make repeated measurements scatter around the true value.

Because of that, systematic error does not fade away with more trials; it leaves a persistent offset. Random error, however, tends to average out as you take more measurements, improving precision. You can reduce systematic error by calibration, correcting flaws in method, or using better instruments. Random error is reduced by increasing the number of measurements or refining measurement techniques, though it can’t be eliminated completely.

So the statement that best describes the distinction is that one is a consistent bias and the other consists of unpredictable fluctuations that average out with repetition. The other options fail because they misstate how these errors behave or what can cause them.