Thus, for example, according to Benford's distribution, the probability that the first significant digit of a randomly chosen number is an 8 is
One use of this distribution is in auditing financial records. The idea is that if the books have been artificially altered, the distribution of the first significant digit will differ markedly from what is predicted by Benford's distribution. Suppose the IRS is auditing the financial records of a large company.
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This is convincing evidence, since if the records follow Benford's
law, we have observed a very rare (17/10000) occurrence.
It is also acceptable to construct a 95% confidence interval for p,
the population proportion of numbers having first digit 1. This
interval turns out to be (0.231,0.285), which, since it doesn't
contain 0.301, suggests that the data do not follow Benford's
distribution.
ANS: t15,0.975=2.1314. The interval is
ANS: Since it lies outside the prediction interval, we conclude it is flawed.
ANS: r2=0.7695
ANS: The slope is the change in predicted INTERVAL per unit change in DURATION. The intercept has no meaning of its own. If it did, it would be the predicted time until the next eruption when the present eruption lasts 0 minutes.
ANS: The fit looks good. The normal quantile plot of the Studentized residuals is straight and the residuals are randomly scattered versus fitted values. There are clearly still two groups of eruptions, but the line summarizes both well. r2 is nearly 0.77, which means that 77% of the variation in the time until the next eruption is explained by knowing the duration of the current eruption.
ANS: The actual interval is (42.46,66.91). Any student answers that are reasonably close to this are acceptable.