What Is the Error of Log(mh) When m and h Have Known Relative Errors?

  • Thread starter excel000
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In summary, the question asks for the error of log(mh) given the relative error of m as 1% and h as 0.5%. Using the equations for the derivative of ln(x) and the error in ln(x), the attempt at a solution suggests taking the error of 0.43ln(m) + 0.43ln(h), resulting in a negative value of -4.26. However, this approach may not be correct as it is unclear how the 0.43 factor is relevant to the problem. To find the error in ln(mh), the relative error of m*h needs to be calculated and then substituted into the equation for the error in ln(x).
  • #1
excel000
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Homework Statement



If the relative error of m is 1% and of h is .5%, what is the error of log(mh)?

Homework Equations



d/dx(lnx)=1/x, [tex]\delta[/tex]lnx=[tex]\delta[/tex]x/x

The Attempt at a Solution


[tex]\delta[/tex](ln0.43(mh))=[tex]\delta[/tex](0.43lnm + 0.43lnh)
=[tex]\delta[/tex](0.43ln0.01 + 0.43ln0.005)
=-4.26

i'm pretty sure this isn't right since it's a negative number, i have no idea how to do this
 
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  • #2
I don't see how the 0.43 is coming into this.

First, what's the relative error in m*h?

Second, if you want the error in ln(x), replace x with x0(1±ε). (ε is the relative error in x).

See if you can work it from there.
 
  • #3


I understand that uncertainty and error are important factors to consider when making calculations or measurements. In this case, we are given the relative errors of two quantities, m and h, and are asked to find the error of log(mh).

To find the error of a function, we can use the formula: δf = |f'(x)| * δx, where δf is the error in the function, f'(x) is the derivative of the function, and δx is the error in the input variable.

In this case, the function we are interested in is log(mh). Using the formula above, we can write the error of log(mh) as:

δlog(mh) = |(1/mh) * (δm * h + m * δh)|

Substituting the given values for relative errors, we get:

δlog(mh) = |(1/mh) * (0.01 * h + m * 0.005)|

Since we do not have the values for m and h, we cannot calculate the exact error of log(mh). However, we can make some general observations based on the given information. The relative error of m is larger than that of h (1% vs 0.5%), which means that the error in m will have a greater impact on the overall error of log(mh). Additionally, since log(mh) is a product of m and h, the error will be a combination of the individual errors in m and h.

In conclusion, the error of log(mh) will depend on the values of m and h, but it will likely be larger than the individual errors of m and h due to their combined effect.
 

1. What is uncertainty/error in scientific research?

Uncertainty or error in scientific research refers to the unavoidable variations or limitations in measurements, observations, or calculations that affect the accuracy and precision of the results. It is the difference between the true value and the measured value.

2. What are the types of uncertainty/error in scientific research?

The two main types of uncertainty/error in scientific research are random uncertainty and systematic uncertainty. Random uncertainty is caused by natural variations in measurements, while systematic uncertainty is caused by flaws in the experimental design or equipment.

3. How do scientists account for uncertainty/error in their research?

Scientists use statistical methods and error analysis to quantify and account for uncertainty/error in their research. They also conduct multiple trials or replicate experiments to reduce the effects of uncertainty/error.

4. How does uncertainty/error affect the reliability of scientific results?

Uncertainty/error can affect the reliability of scientific results by introducing inaccuracies or inconsistencies. However, proper accounting and consideration of uncertainty/error can increase the reliability and validity of the results.

5. Can uncertainty/error ever be completely eliminated in scientific research?

No, uncertainty/error can never be completely eliminated in scientific research. However, it can be minimized through careful experimental design, precise measurements, and accurate data analysis. Scientists also continuously strive to reduce uncertainty/error through advancements in technology and techniques.

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