Bias

Bias refers to measurement error. For example, a sensor may always measure a little higher or lower than the true concentration. The systematic (non-random) or persistent disagreement between the concentrations reported by the sensor and reference instrument. It is often determined using the linear regression slope and intercept of a simple linear regression, fitting sensor measurements (y-axis) to reference measurements (x-axis). Bias is a systematic (built-in) error in data measurement that makes all the measurements wrong by a certain amount. It is a persistent error in the measurement process that causes all measured values to be too high or too low by a certain amount, compared to the true (reference) value. This is the intercept value (b) in the slope-intercept equation y = mx + b.