Define systematic and random errors.

Systematic errors are consistent, predictable errors, while random errors are unpredictable fluctuations in measurements.

Systematic errors, also known as biases, are errors that are consistently present in a particular direction. They are predictable and typically caused by faulty equipment or flawed experimental design. For example, if a scale is not properly calibrated and always measures 1 gram too heavy, this is a systematic error. These errors can be identified and corrected by calibrating the measuring instrument or improving the experimental procedure. However, if not identified, they can significantly skew the results and lead to inaccurate conclusions.

On the other hand, random errors are unpredictable and occur without any consistent pattern. They are caused by unpredictable and inherently variable factors, such as slight changes in temperature, electrical interference, or human error in reading measurements. For instance, if you measure the length of a table multiple times with a ruler and get slightly different results each time, these are random errors. Unlike systematic errors, random errors cannot be corrected, but their impact can be reduced by increasing the number of measurements and using statistical analysis.

In the context of physics experiments, understanding the difference between systematic and random errors is crucial. Systematic errors can lead to a consistent deviation from the true value, which can be misleading. Random errors, while they may cause individual measurements to deviate from the true value, tend to average out over a large number of measurements, leading to a more accurate estimate of the true value. Therefore, it's important to identify and minimise systematic errors as much as possible, and to use appropriate statistical methods to deal with random errors.