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only one problem (Exercise 1-11 only)
Uncertainties in Measurement and Propagation of Errors one measurement is made and often the peecision of the instrument is used as arn mate of the uncertainty. the instrument and the situation, the uncertainty Depending upon could be less than the precision of the instrument or it could be more. For example, in measuring we may estimate the distance between the small est subdivision (mm) if we rurn the meter stick onto its side to eliminate parallax. Therefore, the uncertainty in the measurement mighe be 05 mm or even 0.3 mm rather than the precision of the mete stick which is 1 mm. On the other hand, if we measure an objece that is not right next to the meter stick, the uncertainty might be 2 or 3 mm. Often İudgment is required in order to estimate the uncertainty in a single measurement We shall employ the same symbol, d,, to denote estimated uncertainty in this manual Reporting Uncertainties The uncertainty in an experimental quanticy muse be reported. Since there are a number of ways to do this we must state the meaning of theuncertainty. A common method is to report x ± σ together with the number of measurements n. The reader can quickly calculate d In the remain- der of this manual, we shall either quote the standard deviation or the estimated uncertainty as the uncertainty Table 1-2. Weight of a Bea ws- 1.96 x 10 -194x 30 W- 2.03 X 10 W-198 x 10 1.96 × 10 4 Wa-2.00 x 10 W 197 x 10 10 we-L95 × 10-4 Wu-2.00 10.4 wha= 1.97 × 10. W- 1.99x 10 12 Example 1-5. To illustrate these ideas, we might measure the weight of a lea twelve times with a balance of precision 0.01 X 10-*N. The results are tabulated in Table 1-2. The mean wecight, according to eq I1, is: = 1.96+1.94+ +197× 10 N Note that we have retained one more significant figure for W. for the purpose of cakculating (1.96-1.980)++1.97-1.980)x 10N 12 = 1.980× 10 N. the sample standard deviation, which is 12-I 0.02662874 × 10 N

Experiment 1 9 An uncertainty is really only relevant to one digit: if the 0.02 repeesents uncertainty, the following 6 in 0.026 is even more so. A common practice is to keep two digits and quote the resultsof the measurements as r-(1980 0.027)% 10-4 N, although W-(198 0.03) x 10-4 N is correct. The interval of to about Wincludes all values between 2.007 and 1.953 × 10-4 N. Checking Table 1-2, we see that 8 out of the 12 values, or 67%, fall within this spread, which is near the known result for a Gaussian in which case 68% of the measurements fall within to, of the mean. Turning to the estimated error of the mean, from eq. 1-5 σν--4-_ 0.0077x 10 N. (1-6) Thus our mean value of W. 1.980 × 10-4 N has a 68% chance ofbeingwithin 0.008 × 0-4 N of a mean computed from many experiments Exercise 1-9. Suppose that the flea weighing experiment had been terminated after 8 weighings. Find w and dw. Count how many values fall within w ơw and compare with the expected result from a Gaussian distribution. Exercise 1-10. Table 1-3 shows the results of tossing 10 pennies at once 84 different times. Draw a histogram to depict the results. On your histogram draw arrows to indicate your estimate of the mean value of the number of heads and the spread (see Fig. 1-2). Write down the estimated values of the mean number of heads and the standard deviation. Table 1-3. Tossing 10 pennies. Number of Heads Frequency Number of HeadsFrequency 12 14 16 19 10 Exercise 1-11. Find the mean number of heads and the sample standard deviation in Table 1-3 using eqs. 1-3 and 1-4. Compare your answers with your estimates in exercise 1-10. Propagation of Errors Practically all physical quantities of interest are calculated with a formula. For example, to measure a speed, v, we actually measure a distance, d, and the elapsed time, f, and compute vdit. Both d and t will have uncertainties. As a second example, if we want the area of a sheet of paper we would measure the length L and width W and calculate A = LW. To calculate either por A, we would use mean values of d and t or L and Wi however, we drop the bars indicating mean values for con- venience. In these two examples, what are the uncertainties in the calculated quantities v and A

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Mean and standard deviation of a frequency distribution table of number of heads in tosses of 10 pennies

Ne.ot lunar, tauntua 자 (*戊) to-5) 4440s 394361 13 41OS 370 2 1 4 1 6 1 9 12 8 2 4405 53.6044 42 40 29s06 640 3 1046 95 6 S59

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