Errors in measurement and its types | The Mechanical post

Today at The Mechanical post we'll take a look at what is meant by error, what are its types and some preventive measures.

Errors in measurement

Introduction to error

Measurement is an integral part of human nature. Humans tend to measure everything and then take further decisions. 

Take for eg, You live in an apartment, the electricity consumed by your apartment is measured and then you need to pay for the electric bill. 

Similarly, you own an automobile, and when you refill the gas that to is given to you in measured quantity. 

The food you eat, the data (internet) you consume, and almost everything is measured in one way or another. Thus measurement plays a very important role in our lives. And wherever measurement is present there is always some sort of error.

True value  and measured value of a quantity

The true value of a quantity is the actual or the perfect value of the quantity being measured. Whereas measured value is the value obtained by actually measuring the quantity. 

Take for example a slip gauge, the actual value of its height specified by its manufacturer using advanced measuring techniques is 60.00 mm.

Now you take a precise instrument like a vernier caliper or a screw gauge and get the following readings of 59.97 mm. So in this case, 60.00mm is the True value and 59.97mm is the measured value

The true value is the average of the many number of measurements taken, while the measured value is the precise value.

What is an error? 

In simple words, Error is defined as "The difference between the true value and the measured value of a quantity". 

Error is an inevitable part of the measurement. However, errors can be reduced significantly by taking proper precautions, fo that first we need to study errors and their types.

Classification of errors

Errors will somehow get into all measurements no matter how much care is taken. 

But it is the responsibility of the person performing the measurement to take proper care so that the errors can be minimized as much as possible.

Errors can be broadly classified into 3 categories which are:
  1. Random errors
  2. Systematic errors
  3. Gross errors

1. Random error

Random error as the name suggests is random in nature, and unlike systematic errors, they do not follow a uniform pattern which makes it even harder. It is hard to find out the source of a random error. 

Moreover, random errors cannot be controlled. Take for example sudden changes in the temperature of the surrounding. 

This may cause slight expansion of the instrument or the workpiece. This would result in errors in the measurement. 


Random errors cannot be eliminated, however, they can be minimized by increasing the number of measurements carried out on the same quantity as much as possible and then taking the average value as the reading. 

This method is not only useful for minimizing random errors but in general, it helps reduce error in the measurement.

2. Systematic errors

Systematic errors can be defined as the error which follows a uniform pattern and is systematic in nature.

 These errors can be identified and can be compensated for, something which cannot be done in case of random errors. 

Systematic errors are further classified into 3 types :
  • Instrumental errors
  • Observational errors
  • Environmental errors

Instrumental error

Instrumental error is defined as the error caused due to the usage of defective instruments. Due to external factors or due wear and tear the instrument losses its accuracy. 

This loss of accuracy means an increase in error. There are many factors that may lead to instrumental error like wear and tear of the instrument, improper calibration, expansion of instrument material due to surrounding temperature, manufacturing error, load on the instrument which can lead to creep and fatigue, etc.

Example of instrumental error : 

Let's take a simple case. A ruler scale (its scale is shifted +0.5 cm) reads 2 cm while the actual reading is 1.5 cm. 

This means that the ruler has a calibration error of +0.5 cm. So for every reading that this ruler takes 0.5 cm has to be deducted in order to get the correct reading. 

This too is a  case of systematic error because as the length increases the error of 0.5 cm remains uniform.

Observational errors

Observational error is a type of human error that is caused by the operator or the performer due to incorrectly reading the measuring instrument output.

Observational error is mostly caused by instruments with pointers and scales marked on them. This makes them prone to parallax error. 

Parallax error is the error caused due to the shifting of scales when viewed from a different angle. 

To prevent parallax error the observer's sight must be perpendicular to the pointer of the instrument and not at any other angle. 

Moreover, a mirror is provided behind the scale marking to help reduced parallax error.

Environmental Errors

Environmental errors happen due to the surrounding situation of the measuring instruments. 

These types of errors mostly happen due to the result of external factors like temperature, force, atmospheric pressure, moisture, dirt, vibration, electrostatic field or magnetic field, etc. 

By opting for automated and computed methods of measuring this error can be reduced to an extent.

Fun fact

The ideal condition for metrology lab or perfoming measurement is 20 degrees celcius room temperature and 760 mm of hg pressure.

3. Gross error

Gross errors can be defined as errors caused in the process of measurement on the observer's side due to various reasons. 

This can also be termed as personal error. This error can take place anytime during the measurement process. 

It may be while noting down the reading, or due to improper reading (for eg reading from vernier caliper is 20.60 cm while the observer reads 20.06 cm), lack of concentration, etc. 

These types of errors can be estimated and further corrected by careful reading as well as a recording of information and taking numerous readings of the instrument by different operators.

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