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Propagation of Error - Data Analysis, CSIR-NET Physical Sciences | Physics for IIT JAM, UGC - NET, CSIR NET PDF Download

The analysis of uncertainties (errors) in measurements and calculations is essential in the physics laboratory.  For example, suppose you measure the length of a long rod by making three measurement x = xbest ± ∆x, y = ybest ± ∆y, and z = zbest ± ∆z.  Each of these measurements has its own uncertainty ∆x, ∆y, and ∆z  respectively.  What is the uncertainty in the length of the rod L = x + y + z?  When we add the measurements do the uncertainties ∆x, ∆y, ∆z cancel, add, or remain the same?  Likewise , suppose we measure the dimensions b = bbest ± ∆b, h = hbest ± ∆h, and w = wbest ± ∆w of a block.  Again, each of these measurements has its own uncertainty ∆b, ∆h, and ∆w  respectively.  What is the uncertainty in the volume of the block V = bhw? Do the uncertainties add, cancel, or remain the same when we calculate the volume?  In order for us to determine what happens to the uncertainty (error) in the length of the rod or volume of the block we must analyze how the error (uncertainty) propagates when we do the calculation.   In error analysis we refer to this as error propagation.

There is an error propagation formula that is used for calculating uncertainties when adding or subtracting measurements with uncertainties and a different error propagation formula for calculating uncertainties when multiplying or dividing measurements with uncertainties.  Let’s first look at the formula for adding or subtracting measurements with uncertainties. 

 

Adding or Subtracting Measurements with Uncertainties.

Suppose you make two measurements,  

x = xbest  ±  ∆x  
y = ybest  ±  ∆y 

What is the uncertainty in the quantity q = x + y or q = x – y?

To obtain the uncertainty we will find the lowest and highest probable value of q = x + y.  Note that we would like to state q in the standard form of q = qbest ± ∆q where              

qbest = xbest + ybest

(highest probable value of q = x + y):  

(xbest+ ∆x) + (ybest + ∆y) = (xbest+ ybest) + (∆x +∆y) = qbest + ∆q 

(lowest probable value of q = x + y):

(xbest- ∆x) + (ybest - ∆y) = (xbest+ ybest) - (∆x +∆y) = qbest – ∆q 

Thus, we that  

∆q = ∆x + ∆y 

is the uncertainty in q = x + y.  A similar result applies if we needed to obtain the uncertainty in the difference q = x – y.  If we had added or subtracted more than two  measurements  x, y, ......, z each with its own uncertainty ∆x, ∆y, ......... , ∆z  respectively , the result would be 

∆q = ∆x + ∆y + ......... + ∆z

Now, if the uncertainties ∆x, ∆y, ........., ∆z are random and independent, the result is  

Propagation of Error - Data Analysis, CSIR-NET Physical Sciences | Physics for IIT JAM, UGC - NET, CSIR NET

Ex. x = 3.52 cm ± 0.05 cm

 y = 2.35 cm ± 0.04 cm 

Calculate q = x + y  We would like to state q in the standard form of q = qbest ± ∆q 

xbest = 3.52cm, ∆x = 0.05cm

 ybest = 2.35cm, ∆y = 0.04cm

 qbest = xbest + ybest = 3.52cm + 2.35cm = 5.87cm 

Propagation of Error - Data Analysis, CSIR-NET Physical Sciences | Physics for IIT JAM, UGC - NET, CSIR NET

q = 5.87cm ± 0.06cm 

 

Multiplying or Dividing Measurements with Uncertainties

Suppose you make two measurements,  

x = xbest  ±  ∆x  
y = ybest  ±  ∆y 

What is the uncertainty in the quantity q = xy or q = x/y?

To obtain the uncertainty we will find the highest and lowest probable value of q = xy.  The result will be the same if we consider q = x/y. Again we would like to state q in the standard form of q = qbest ± ∆q where now qbest = xbest ybest

.(highest probable value of q = xy): 

(xbest+ ∆x)(ybest + ∆y) = xbestybest + xbest ∆y +∆x ybest + ∆x ∆y  = qbest + ∆q    

= xbestybest + (xbest ∆y + ∆x ybest) =  qbest + ∆q

(lowest probable value of q = xy):

(xbest- ∆x)(ybest - ∆y) = xbestybest - xbest ∆y - ∆x ybest + ∆x ∆y  = qbest – ∆q          

 = xbestybest – (xbest ∆y + ∆x ybest) =  qbest – ∆q 

Since the uncertainties ∆x and ∆y are assumed to be small, then the product ∆x ∆y ≈ 0.  Thus, we see that ∆q = xbest ∆y +∆x ybest in either case.  Dividing by xbestybest gives 

Propagation of Error - Data Analysis, CSIR-NET Physical Sciences | Physics for IIT JAM, UGC - NET, CSIR NET

Again, a similar result applies if we needed to obtain the uncertainty in the division of     q = x/y.  If we had multiplied or divided more than two measurements  x, y, ......, z each with its own uncertainty ∆x, ∆y, ......... , ∆z  respectively, the result would be 

Propagation of Error - Data Analysis, CSIR-NET Physical Sciences | Physics for IIT JAM, UGC - NET, CSIR NET

Now, if the uncertainties ∆x, ∆y, ........., ∆z are random and independent, the result is  

Propagation of Error - Data Analysis, CSIR-NET Physical Sciences | Physics for IIT JAM, UGC - NET, CSIR NET

Ex.  x = 49.52cm ± 0.08cm  
       y = 189.53cm ± 0.05cm  

Calculate q = xy  We would like to state q in the standard form of q = qbest ± ∆q

xbest = 49.52cm, ∆x = 0.08cm

ybest = 189.53cm, ∆y = 0.05cm

qbest = xbestybest = (49.52cm)(189.53cm)=9.38553 x 103 cm2

Propagation of Error - Data Analysis, CSIR-NET Physical Sciences | Physics for IIT JAM, UGC - NET, CSIR NET

∆q = (1.63691 x 10-3)qbest = (1.63691 x 10-3) (9.38553 x 103 cm2)

∆q = 15.3632cm2 ≈ 20 cm

 q = 9390 cm2 ± 20 cm2

 

Uncertainty for a Quantity Raised to a Power 

If a measurement x has uncertainty ∆x, then the uncertainty in q = xn, is given by the expression 

Propagation of Error - Data Analysis, CSIR-NET Physical Sciences | Physics for IIT JAM, UGC - NET, CSIR NET

Ex.  Let q = x3 where x = 5.75cm ± 0.08 cm.  

Calculate the uncertainty ∆q in the quantity q.  

We would like to state q in the standard form of q = qbest ± ∆q 

Propagation of Error - Data Analysis, CSIR-NET Physical Sciences | Physics for IIT JAM, UGC - NET, CSIR NET

Propagation of Error - Data Analysis, CSIR-NET Physical Sciences | Physics for IIT JAM, UGC - NET, CSIR NET 

The document Propagation of Error - Data Analysis, CSIR-NET Physical Sciences | Physics for IIT JAM, UGC - NET, CSIR NET is a part of the Physics Course Physics for IIT JAM, UGC - NET, CSIR NET.
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FAQs on Propagation of Error - Data Analysis, CSIR-NET Physical Sciences - Physics for IIT JAM, UGC - NET, CSIR NET

1. What is the concept of error propagation in data analysis?
Ans. Error propagation is the process of determining the uncertainty or error in the final result of a calculation when the measurements used in the calculation have uncertainties. It involves propagating the uncertainties of the input measurements through the mathematical operations to obtain the uncertainty of the final result.
2. How is error propagation useful in data analysis?
Ans. Error propagation allows us to quantitatively determine the uncertainty associated with the final result of a calculation. It helps in understanding the reliability and accuracy of the calculated value by considering the uncertainties in the input measurements. It is particularly important in scientific research and experimental measurements where accurate quantification of uncertainty is crucial.
3. What are the key factors affecting error propagation in data analysis?
Ans. There are several factors that can affect error propagation in data analysis. Some of the key factors include the uncertainties associated with the measured quantities, the mathematical operations involved in the calculation, the correlation between the measured quantities, and the assumptions made in the analysis. It is important to consider these factors to accurately estimate the uncertainty in the final result.
4. How can error propagation be performed in practice?
Ans. Error propagation can be performed using various mathematical techniques, such as the formula for propagation of errors, the Taylor series expansion method, or Monte Carlo simulations. These methods involve mathematical calculations based on the uncertainty values of the input measurements and the mathematical operations involved in the analysis. The specific method chosen depends on the complexity of the calculation and the available information.
5. What are the limitations of error propagation in data analysis?
Ans. Error propagation assumes that the uncertainties in the input measurements are independent and normally distributed. However, in practice, there may be correlations between the uncertainties or the distribution may not be strictly normal. Additionally, error propagation does not take into account systematic errors or biases in the measurements. It is important to consider these limitations and perform a comprehensive error analysis to obtain accurate and reliable results.
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