How do you calculate percent error?
Percent error = |measured − actual| ÷ |actual| × 100. Take the absolute difference between your measured (or estimated) value and the true value, divide by the true value, and multiply by 100. Example: measuring 9.5 cm when the true length is 10 cm gives |9.5 − 10| ÷ 10 × 100 = 5% error.
What is the difference between percent error and percent difference?
Percent error compares a measurement against a known true or accepted value — it measures accuracy. Percent difference compares two equally valid measurements against their average — it measures agreement when neither value is the reference. Use percent error in labs and quality control where a standard exists; percent difference when comparing two experimental results.
Can percent error be negative?
The standard percent error uses absolute values, so it is always positive. However, the signed (relative) error keeps the direction: positive means an overestimate, negative means an underestimate. This calculator shows both — the signed error is useful for spotting systematic bias, such as an instrument that consistently reads high.
What is an acceptable percent error?
It depends entirely on context. In high-school chemistry labs, under 5–10% is generally considered good. Engineering tolerances are often under 1%, and analytical chemistry or metrology may require under 0.1%. In business forecasting, errors of 10–20% can be normal. Always compare your error against the standard for your field.
Should I report percent error or absolute error?
Both, where you can. Absolute error keeps its units and is what matters when the accepted value sits near zero — a reading that is 0.2 out from a true value of 0.05 gives a percent error of 400%, which is technically correct and practically useless. Percent error is the better measure when you want to compare accuracy across measurements of very different sizes, since being 5 grams out on a kilogram and 5 grams out on 20 grams are completely different achievements. Most laboratory reports expect the percentage, but stating the absolute figure alongside it costs nothing and prevents misreading.
What actually causes the error in a measurement?
Two distinct things, and percent error alone cannot tell them apart. Systematic error shifts every reading in the same direction — an uncalibrated scale with a zero offset, a thermometer reading consistently high, parallax from viewing a meniscus at the wrong height. Repeating the measurement will not remove it, because it repeats too. Random error scatters readings either side of the true value through fluctuations you cannot control, and it does average out as you take more readings. If your percent error stays stubbornly the same across many trials, suspect a systematic cause and check the instrument before you blame the technique.