Systematic error refers to consistent, repeatable errors associated with faulty equipment or flawed experiment design. These errors lead to measurements that are consistently off in the same direction from the true value, either higher or lower. Systematic errors are predictable and typically caused by issues in the measurement system, such as calibration errors, biased sampling methods, or environmental factors affecting the measurement process.

Random error refers to the unpredictable and unavoidable fluctuations that occur in measurement processes. These errors are caused by random variations in the measurement environment, the measurement instrument, or the observer. Unlike systematic errors, random errors do not follow a consistent pattern and can cause measurements to vary in both directions around the true value.

Variability: The error varies in magnitude and direction with each measurement.

Lack of Bias: Random errors do not consistently skew measurements in one direction; they can lead to both overestimates and underestimates.

Reduction Through Averaging: Random errors can be reduced by increasing the number of measurements and averaging the results, as their effects tend to cancel out over many observations.

Consistency: The error is consistent across repeated measurements.

Bias: Systematic error introduces a bias into the results, as it skews measurements in a particular direction.

Detectability and Correction: Once identified, systematic errors can often be corrected or minimized by recalibrating instruments, adjusting procedures, or using different methodologies.