Systematic errors are consistent, repeatable mistakes that occur in measurements or observations. Unlike random errors, which vary unpredictably, systematic errors arise from flaws in the measurement system, such as faulty equipment or biased data collection methods. These errors can lead to inaccurate results that skew the overall findings. Identifying and correcting systematic errors is crucial for improving the reliability of experiments and data analysis. Common sources include calibration issues with instruments like thermometers or scales, and human biases in interpreting data. Addressing these errors helps ensure that conclusions drawn from research are valid and trustworthy.