Random Error vs Systematic Error
When we do an experiment in the lab, our main focus is to minimize the errors and do it accurately as possible to get good results. However, there are a number of ways where there can be errors. Although we try to eliminate all the errors, it is impossible to do so. Always, there is a degree of inaccuracy incorporated. One reason for errors may be due to the equipments we are using. With time, the equipment tends to have faults and this affects the measurements. Sometimes, the equipment is made to work in some environmental conditions and when these conditions are not supplied it won’t work accurately. Other than the equipment errors, there can be errors in people who are handling them. Especially, we make mistakes when taking readings. Sometimes, if those doing the experiment are not experienced, there can be various errors in the methods. On the other hand, errors may result due to improper material or reactants used. Though we cannot eliminate all these errors 100%, we should try to eliminate them as much as possible, in order to get a result closer to the real results. Sometimes these errors are the reason why we don’t get measurements or results according to the theoretical values. When we are taking a measurement or doing an experiment, we try to repeat it several times in order to reduce the error. Else, sometimes by changing the experimenter, by changing the place, or by changing the equipments and materials used, we try to do the same experiments several times. There are mainly two types of errors that can occur in an experiment. They are random error and systematic error.
Random Error
As the name suggests, random errors are unpredictable. These are the errors caused by unknown and unpredictable changes in the experiment. Although the experimenter do the same experiment in the same way using the same equipment and, if he cannot get the same result (same number if it is a measurement), then it is due to random error. This may be in the equipment or due to the environmental conditions. For example, if you measure the weight of a piece of iron by the same balance and get three different reading in three times, that is a random error. In order to minimize the error, large number of the same measurements can be taken. By taking the average value of all, a value closer to the real value can be obtained. Since random errors have a Gaussian normal distribution, this method of getting the average gives a precise value.
Systematic Error
Systematic errors are predictable, and this error will be there for all the readings taken. They are reproducible errors and are always in the same direction. For an experiment, systematic errors will be persistent throughout the experiment. For example, systematic error may be caused due to an imperfect calibration of an instrument, or else, if we use a tape, which has elongated due to the usage, to measure lengths, the error will be same for all the measurements.
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What is the difference between Random Error and Systematic Error? • Random errors are unpredictable, and they are the errors caused by the unknown and unpredictable changes in the experiment. In contrast, systematic errors are predictable. • If we can identify the sources of systematic errors we can easily eliminate it, but random errors cannot be easily eliminated like that. • Systematic errors affect all the readings in the same way, whereas random errors vary on each measurement.
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