Random & systematic errors
- Measurements of quantities are made with the aim of finding the true value of that quantity
- In reality, it is impossible to obtain the true value of any quantity, there will always be a degree of uncertainty
- The uncertainty is an estimate of the difference between a measurement reading and the true value
- Random and systematic errors are two types of measurement errors which lead to uncertainty
Random error
- Random errors cause unpredictable fluctuations in an instrument’s readings as a result of uncontrollable factors, such as environmental conditions
- This affects the precision of the measurements taken, causing a wider spread of results about the mean value
- To reduce random error: repeat measurements several times and calculate an average from them
Systematic error
- Systematic errors arise from the use of faulty instruments used or from flaws in the experimental method
- This type of error is repeated every time the instrument is used or the method is followed, which affects the accuracy of all readings obtained
- To reduce systematic errors: instruments should be recalibrated or the technique being used should be corrected or adjusted
A graph showing the precision and accuracy of different sets of measurements
Precision can only be used to describe multiple measurements - it tells us how close together those measurements are. Imprecise measurements will have a large range, as shown by the accurate but imprecise black line.
Zero error
- Zero error is a type of systematic error which occurs when an instrument gives a non-zero reading when the true reading is zero
- An example may be a set of mass scales showing a reading of 0.200 g when nothing is on the scales
- This introduces a fixed error into readings which must be accounted for when the results are recorded