1.3.1 Differentiate between systematic and random errors.

SYSTEMATIC ERROR:

Systematic error (also called systematic bias) is consistent, repeatable error associated with faulty equipment or a flawed experiment design. These errors are usually caused by measuring instruments that are incorrectly calibrated or are used incorrectly. However, they can creep into your experiment from many sources, including:

1. A worn out instrument. For example, a plastic tape measure becomes slightly stretched over the years, resulting in measurements that are slightly too high.

2. An incorrectly calibrated or tared instrument, like a scale that doesn’t read zero when nothing is on it.

3. A person consistently takes an incorrect measurement. For example, they might think the 3/4″ mark on a ruler is the 2/3″ mark.

Systematic Errors produce consistent errors, either a fixed amount (like 1 lb) or a proportion (like 105% of the true value). If you repeat the experiment, you’ll get the same error.

RANDOM ERROR:

Random error (also called unsystematic error, system noise or random variation) has no pattern. One minute your readings might be too small. The next they might be too large. You can’t predict random error and these errors are usually unavoidable.

Random errors are (like the name suggests) completely random. They are unpredictable and can’t be replicated by repeating the experiment again.