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By definition relative error is given by $\delta f / f$ so f here is sin30 and the numerator is the difference you have written in your question. To calculate percentage error just multiply relative error by 100.


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As a starting point, I would use a greedy algorithm. Initialize the m partition values to be close the individual fractional values. So in your example, the values (5,3,2) are naturally selected because they are each respectively the closest approximations to their fractional values. After having done this selection, you may find that you are off by some ...


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(a) 1 can be observed at the output if: (i) 1 is produced at the source and transmitted correctly OR (ii) 0 is produced at the source and is transmitted incorrectly. So, Pr[1 at target] = Pr[1 at source]*Pr[transmitted correctly] + Pr[0 at source]*Pr[transmitted incorrectly] i.e Pr[1 at target] = 0.7*(1-0.2) + 0.3*0.2 = 0.56 + 0.06 ...


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You have $$ x_{11}=1.10, x_{12}=1.15 \\ x_{21}=1.02, x_{22}= 1.05 \\ x_{31}=1.11, x_{32}=1.09 $$ Your question is unclear, because you did not state an statistical model, so we do not really know what are reasonable assumptions for your data. If you think all your data have a common mean, then you can just treat them as one sample with ...


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I have essentially a propagation-of-error problem First, a note about terminology: the correct term is uncertainty, not error (error is a different thing). And your problem is not really a problem about propagation of uncertainty. Evaluation of uncertainty is in general a difficult task, even in your case might not be that simple. To provide advice on ...


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Standard deviation is only a measurement of dispersion of your data in your 3 samples. All three samples will have the same standard deviation if they are supposed identical. In order to take precision of measurement into consideration, you have to calculate the standard error, which is basically the standard deviation divided by $\sqrt(n)$ where n is the ...



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