Density Error Propagation/Significant Figures Based on Extreme Values

In summary, the conversation discusses finding the error in density using extreme values and determining the number of significant figures in the calculated density. The upper and lower limits for mass and volume are used to calculate the extreme values for density, and it is suggested to calculate the density using all given digits to determine the appropriate number of significant figures.
  • #1
jchiz24
3
0

Homework Statement


The density of an object is found to be 976 g/L based on mass of 976 +/- 5g and volume of 1 +/- 0.01L.

Determine the error in the density using extreme values (upper limit of mass divided by lower limit of volume, etc)

Homework Equations


I'm having difficulty determining how to factor in significant figures here.

Use D = M / V

The Attempt at a Solution


Upper limit = (976 + 5) / (1 - 0.01)
Lower limit = (976 - 5) / (1 + 0.01)

My reasoning: since the numerator result has 3 significant figures, and the denominator has 1 significant figure (since 1 only has 1sigfig), the resultant densities have 1 sigfig. But this seems to cut off too many figures.
 
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  • #2
Not all zeros are insignificant. Calculate both densities using all given digits and decide from those values the number of significant digits of the density.

ehild
 

Related to Density Error Propagation/Significant Figures Based on Extreme Values

What is density error propagation?

Density error propagation is a method used to estimate the uncertainty in a calculated density value based on the uncertainties in the measurements used to calculate it.

How is density error propagation calculated?

Density error propagation is calculated using the formula:
δρ = ρ × √[(δm/m)2 + (δV/V)2],
where δρ is the uncertainty in density, ρ is the calculated density, δm is the uncertainty in mass, and δV is the uncertainty in volume.

What are significant figures and why are they important in density error propagation?

Significant figures are the digits in a number that are known with certainty plus one uncertain digit. They are important in density error propagation because they determine the precision of the calculated density value and should be taken into account when estimating the uncertainty.

Can extreme values affect the calculated density and its uncertainty?

Yes, extreme values can significantly affect the calculated density and its uncertainty. If there are extreme values in the measurements used to calculate density, they can result in a larger uncertainty and potentially skew the final result.

How can extreme values be accounted for in density error propagation?

Extreme values can be accounted for in density error propagation by using a more robust method, such as the Monte Carlo method, which takes into account the variability and distribution of the extreme values in the calculations.

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