Which type of error is eliminated by good experimental methods and more than one calibration step?

• A. Gross error
• B. Systematic error
• C. Personal error
• D. Random error

Answer: (B)

Systematic errors are biases that consistently skew all measurements in one direction due to instrument bias, flaws in the method, or environmental factors. Good experimental practice—using properly calibrated equipment, following standardized procedures, and performing multiple calibration steps—helps reveal and correct these biases, bringing results closer to the true value. In contrast, random errors fluctuate unpredictably from one measurement to the next and aren’t removed by calibration steps (they’re reduced by averaging many trials). Very large mismatches or misreadings are more like gross errors, often addressed by careful technique and data checks rather than calibration. Technique-related biases from the experimenter (personal error) can also be mitigated by standardization and calibration, but the essential point is that the calibration process specifically targets systematic bias, which is why it’s the best fit here.