What is meant by bias in measurement data?

Bias in measurement data refers to the systematic error that occurs when the average location of results deviates from the true value or target. It indicates whether measurements consistently lean towards a certain direction—either higher or lower than the actual value—due to factors such as flawed methodology, instrument calibration issues, or environmental influences. This concept is crucial in radon measurement because accurate assessment of radon levels is essential for health and safety decisions.

Understanding bias helps technicians identify and address potential systematic errors in their measurement processes. By recognizing that bias can affect the validity of results, professionals can implement corrective actions, leading to more reliable readings. This aspect is fundamental in radon measurements, where outcomes influence public health measures and regulations. The other choices pertain to different aspects of measurement, such as random variations or precision, but do not specifically encapsulate the concept of bias as representing a systematic error in relation to the expected target value.