Errors in Measurement: Types, Sources & Comparison

In summary, Khashishi is correct. There are two types of errors, systematic and random. Random error is when the error varies and is equally likely to be positive or negative. Systematic error is when the error is constant and happens in every measurement. Khashishi mentioned that the surface of the hard board is not regular, which would cause a random error.
  • #1
shalikadm
63
0
Here's what I understand...

Types of errors

1.Systematic errors
  • Zero Error
  • errors due to slow stopwatches
  • errors due to incorrectly graduated scales
2.Random errors
  • error due to unevenness of the measuring item
  • parallax error

Ways of comparing errors
  1. Absolute error[itex]\rightarrow[/itex]error when reading scales=least count
  2. fractional error
  3. percent error
Is this grouping correct ?
 
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  • #2
Random error is wrong. I have no idea what "unevenness of the measuring item" means. Random errors are errors that will not reproduce themselves with repeated measurements using the same methodology. I guess parallax error could be due to either random or systematic causes. Shot noise is a very good example of random error.

Fractional error and percent error should be combined into "relative error" since they are the same thing.
 
  • #3
Khashishi said:
I have no idea what "unevenness of the measuring item" means
let's take that we're going to measure the thickness of a hard board..well if the surface is uneven then we get a wrong value..but we can minimize the error by getting measure from more than one place and calculating the mean..

Khashishi said:
Random error is wrong.
Why?..Isn't it a type of error..can't we divide errors into these two types...systematic and random...?

Khashishi said:
I guess parallax error could be due to either random or systematic causes.
How it can be systematic ?..I think it's not coming from the instrument...We can avoid parallax by positioning the eye in the correct way..

Can you suggest me a correct grouping please ?..Because many websites giving many many different groupings...
here's the words in my mind...
Systematic error,Zero Error,Random error,parallax error,Absolute error,fractional error,percent error,least count,error when reading scales..
can u pls group these for me ...help is much appreciated...thanks !
 
  • #4
From Squires' "Practical Physics" (which I highly recommend):

"A systematic error is one which is constant throughout a set of readings. A random error is one which varies and which is equally likely to be positive or negative."

These are the only two groupings you need.

A parallax error is systematic because if you keep measuring the same length and your head is in the same place, you're going to keep getting the same error. This is different to a random, for example when you can't justify quoting a value to any higher precision than about half the smallest division width on a ruler. Every measurement has that error, in addition to any systematic error.
 
  • #5
edited...
Types of errors

1.Systematic errors
  • Zero Error
  • errors due to slow stopwatches
  • errors due to incorrectly graduated scales
  • parallax error
2.Random errors
  • error due to unevenness of the measuring item

Ways of comparing errors
  1. Absolute error[itex]\rightarrow[/itex]error when reading scales=least count
  2. Relative error[itex]\rightarrow[/itex]percent error,fractional error

MikeyW said:
From Squires' "Practical Physics" (which I highly recommend):

"A systematic error is one which is constant throughout a set of readings. A random error is one which varies and which is equally likely to be positive or negative."
Can you give me some instances for random error rather than unevenness of the surface when we using MR,VC,MMSG,TM,SM instruments?
 
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  • #6
Unevenness of the measuring item will cause a systematic error if the unevenness doesn't change. Your warped ruler is going to still be warped the same amount from one measurement to the next, unless you have some uncontrolled humidity or something weird like that. In that case, it could be a random error, but it's a very bad example of one.
 
  • #7
Khashishi said:
Unevenness of the measuring item will cause a systematic error if the unevenness doesn't change.
How can that be ?...we can have some mean value for that...when we take the hard board..there are +error and -errors...so the mean value will reduce the quantity of error
 
  • #8
shalikadm said:
How can that be ?...we can have some mean value for that...when we take the hard board..there are +error and -errors...so the mean value will reduce the quantity of error

Khashishi seems to be correct. And what do you mean by - and + errors ? If the instruments are assumed to be perfect and all other errors are assumed to be eliminated , then maximum error can be due to least count of that measuring instrument. Thus observed value can be written within the limit as "True Value ± Least Count".
 
  • #9
sankalpmittal said:
Khashishi seems to be correct. And what do you mean by - and + errors ? If the instruments are assumed to be perfect and all other errors are assumed to be eliminated , then maximum error can be due to least count of that measuring instrument. Thus observed value can be written within the limit as "True Value ± Least Count".
You know the surface of the hard board is not regular(even)..
 
  • #10
shalikadm said:
You know the surface of the hard board is not regular(even)..

Now you're taking in account - "error due to imperfection" which comes under "systematic error". If you take this into account , then again observed value will be having more limit. Thus in your case :

Observed value : x (say.)

Then ,

true value - least count≥x≥true value + least value
 

1. What are the different types of errors in measurement?

There are three main types of errors in measurement: systematic, random, and human errors. Systematic errors are consistent and occur due to flaws in the measurement equipment or techniques. Random errors are unpredictable and can occur due to environmental factors or limitations of the measurement tools. Human errors are mistakes made by the person conducting the measurement.

2. What are the sources of errors in measurement?

The sources of errors in measurement can include instrument error, environmental factors, human error, and limitations of the measurement method. Instrument error can be caused by faulty equipment or incorrect calibration. Environmental factors such as temperature, humidity, and external forces can also affect the accuracy of measurements. Human error can occur due to mistakes in recording or reading data, or improper use of equipment. Lastly, limitations of the measurement method can also contribute to errors.

3. How do you compare errors in measurement?

Errors in measurement can be compared by calculating the percent error, which is the difference between the measured value and the true value, divided by the true value. This gives a percentage that can be used to compare the accuracy of different measurements. Another method is to calculate the standard deviation, which measures the spread of data around the mean and can help identify any outliers or inconsistencies in the measurements.

4. How can errors in measurement be reduced?

To reduce errors in measurement, it is important to use calibrated and accurate equipment, follow proper measurement techniques, and minimize environmental factors that can affect the measurements. It is also helpful to take multiple measurements and calculate the average, as this can reduce the impact of random errors. Additionally, having a thorough understanding of the limitations of the measurement method and taking appropriate precautions can also help reduce errors.

5. Why are errors in measurement important to consider?

Errors in measurement are important to consider because they can significantly impact the accuracy and reliability of scientific data and results. Even small errors can lead to incorrect conclusions and affect the validity of experiments. By understanding and accounting for errors in measurement, scientists can ensure the accuracy and credibility of their research findings.

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