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Errors in Measurement System
Definition
*An error may be defined as the difference
between the measured value and the actual/true
value.
*The actual/true value is the average value of an
infinite number of measured values.
*Measured value is the estimated value of true
value that can be found by taking several
measured values during an experiment.
Calculation of % error
*Absolute error = measured value - exact value
= ‫׀‬VA - VE ‫׀‬
*Relative error = [measured value - exact value] /
exact value
= ‫׀‬VA - VE / VE ‫׀‬
*Percentage error = [measured value - exact value] /
exact value x 100%
*Percentage error = ‫׀‬VA - VE / VE ‫×׀‬ 100%
Types of Errors in Measurement System
Gross Errors
*Gross errors are caused by mistake in using instruments
or meters, calculating measurement and recording data
results. (human errors)
*Such errors may end up in calculation of the final results,
thus deviating results.
Systematic errors
*Systematic errors occur due to fault in the measuring
device.
*Usually they are called as Zero Error – a positive or
negative error.
*These errors can be removed by correcting the
measurement device.
Systematic errors are classified into
*Observational Errors: These occur due to wrong
observations or reading in the instruments. (most
common parallax error)
*Environmental Errors: These occur due to some
external conditions of the instrument. (change in
temperature, humidity etc.)
*Instrumental Errors: These occur due to wrong
construction of the measuring instruments.
Instrumental errors may occur due to:
*Hysteresis or friction.
*Loading effect and
*Misuse of the instruments.
Random errors
*Random errors are caused by the sudden change in experimental
conditions. These errors are due to unknown causes.
*They are generally accumulation of a large number of small effects
and may be of real concern.
*These errors can be analysed statistically.
*Noise can cause random errors in measurements.
Hence, it is important to know the types of errors and minimise them
so that measured data is interpreted properly.
The End

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Types of errors

  • 2. Definition *An error may be defined as the difference between the measured value and the actual/true value. *The actual/true value is the average value of an infinite number of measured values. *Measured value is the estimated value of true value that can be found by taking several measured values during an experiment.
  • 3. Calculation of % error *Absolute error = measured value - exact value = ‫׀‬VA - VE ‫׀‬ *Relative error = [measured value - exact value] / exact value = ‫׀‬VA - VE / VE ‫׀‬ *Percentage error = [measured value - exact value] / exact value x 100% *Percentage error = ‫׀‬VA - VE / VE ‫×׀‬ 100%
  • 4. Types of Errors in Measurement System
  • 5. Gross Errors *Gross errors are caused by mistake in using instruments or meters, calculating measurement and recording data results. (human errors) *Such errors may end up in calculation of the final results, thus deviating results.
  • 6. Systematic errors *Systematic errors occur due to fault in the measuring device. *Usually they are called as Zero Error – a positive or negative error. *These errors can be removed by correcting the measurement device.
  • 7. Systematic errors are classified into *Observational Errors: These occur due to wrong observations or reading in the instruments. (most common parallax error) *Environmental Errors: These occur due to some external conditions of the instrument. (change in temperature, humidity etc.) *Instrumental Errors: These occur due to wrong construction of the measuring instruments.
  • 8. Instrumental errors may occur due to: *Hysteresis or friction. *Loading effect and *Misuse of the instruments.
  • 9. Random errors *Random errors are caused by the sudden change in experimental conditions. These errors are due to unknown causes. *They are generally accumulation of a large number of small effects and may be of real concern. *These errors can be analysed statistically. *Noise can cause random errors in measurements. Hence, it is important to know the types of errors and minimise them so that measured data is interpreted properly.