How many types of errors are occured in physics experiment?

most effective error is how can you take measurement of the experiment.one example , some time you need reading measuring at right angle to your eyes but some time need parallel to your eyes. so you should understand the theory correctly . And there always remain instrumental error which can you avoid my measuring instrumental error function. read less

Errors occur in all physical measurements. When a measurement is used in a calculation, the error in the measurement is therefore carried through into the result. The two different types of error that can occur in a measured value are: Systematic error – this occurs to the same extent in each one of a series of measurements eg zero error, where for instance the needle of a voltmeter is not correctly adjusted to read zero when no voltage is present. Random error – this occurs in any measurement as a result of variations in the measurement technique (eg parallax error, limit of reading, etc). When we report errors in a measured quantity we give either the absolute error, which is the actual size of the error expressed in the appropriate units or the relative error, which is the absolute error expressed as a fraction of the actual measured quantity. Relative errors can also be expressed as percentage errors. So, for instance, we may have measured the acceleration due to gravity as 9.8 m/s2 and determined the error to be 0.2 m/s2. So, we say the absolute error in the result is 0.2 m/s2 and the relative error is 0.2 / 9.8 = 0.02 (or 2%). Note relative errors have no units. We would then say that our experimentally determined value for the acceleration due to gravity is in error by 2% and therefore lies somewhere between 9.8 read less

Errors are normally classified in three categories: systematic errors, random errors, and blunders. Systematic Errors Systematic errors are due to identified causes and can, in principle, be eliminated. Errors of this type result in measured values that are consistently too high or consistently too low. Systematic errors may be of four kinds: 1. Instrumental. For example, a poorly calibrated instrument such as a thermometer that reads 102 oC when immersed in boiling water and 2 oC when immersed in ice water at atmospheric pressure. Such a thermometer would result in measured values that are consistently too high. 2. Observational. For example, parallax in reading a meter scale. 3. Environmental. For example, an electrical power ìbrown outî that causes measured currents to be consistently too low. 4. Theoretical. Due to simplification of the model system or approximations in the equations describing it. For example, if your theory says that the temperature of the surrounding will not affect the readings taken when it actually does, then this factor will introduce a source of error. Random Errors Random errors are positive and negative fluctuations that cause about one-half of the measurements to be too high and one-half to be too low. Sources of random errors cannot always be identified. Possible sources of random errors are as follows: 1. Observational. For example, errors in judgment of an observer when reading the scale of a measuring device to the smallest division. 2. Environmental. For example, unpredictable fluctuations in line voltage, temperature, or mechanical vibrations of equipment. Random errors, unlike systematic errors, can often be quantified by statistical analysis, therefore, the effects of random errors on the quantity or physical law under investigation can often be determined. Example to distinguish between systematic and random errors is suppose that you use a stop watch to measure the time required for ten oscillations of a pendulum. One source of error will be your reaction time in starting and stopping the watch. During one measurement you may start early and stop late; on the next you may reverse these errors. These are random errors if both situations are equally likely. Repeated measurements produce a series of times that are all slightly different. They vary in random vary about an average value. If a systematic error is also included for example, your stop watch is not starting from zero, then your measurements will vary, not about the average value, but about a displaced value. Blunders A final source of error, called a blunder, is an outright mistake. A person may record a wrong value, misread a scale, forget a digit when reading a scale or recording a measurement, or make a similar blunder. These blunder should stick out like sore thumbs if we make multiple measurements or if one person checks the work of another. Blunders should not be included in the analysis of data. read less