Recall that Benford's Law claims that numbers chosen from very large data files tend to have "1" as the first nonzero digit disproportionately often. In fact, research has shown that if you randomly draw a number from a very large data file, the probability of getting a number with "1" as the leading digit is about 0.301. Now suppose you are an auditor for a very large corporation. The revenue report involves millions of numbers in a large computer file. Let us say you took a random sample ofn=215numerical entries from the file andr=50of the entries had a first nonzero digit of 1. Letprepresent the population proportion of all numbers in the corporate file that have a first nonzero digit of 1.

(i) Test the claim thatpis less than 0.301. Use=0.10.

(a) What is the level of significance?

State the null and alternate hypotheses.

H₀:p< 0.301;H₁:p= 0.301

H₀:p= 0.301;H₁:p> 0.301

H₀:p= 0.301;H₁:p< 0.301

H₀:p= 0.301;H₁:p0.301

(b) What sampling distribution will you use?

The Student'st, sincenp< 5 andnq< 5.

The standard normal, sincenp> 5 andnq> 5.

The standard normal, sincenp< 5 andnq< 5.

The Student'st, sincenp> 5 andnq> 5.

What is the value of the sample test statistic? (Round your answer to two decimal places.)

(c) Find theP-value of the test statistic. (Round your answer to four decimal places.)

Sketch the sampling distribution and show the area corresponding to theP-value.

(d) Based on your answers in parts (a) to (c), will you reject or fail to reject the null hypothesis? Are the data statistically significant at level?

At the= 0.10 level, we reject the null hypothesis and conclude the data are statistically significant.

At the= 0.10 level, we reject the null hypothesis and conclude the data are not statistically significant.

At the= 0.10 level, we fail to reject the null hypothesis and conclude the data are statistically significant.

At the= 0.10 level, we fail to reject the null hypothesis and conclude the data are not statistically significant.

(e) Interpret your conclusion in the context of the application. There is sufficient evidence at the 0.10 level to conclude that the true proportion of numbers with a leading 1 in the revenue file is less than 0.301.

There is insufficient evidence at the 0.10 level to conclude that the true proportion of numbers with a leading 1 in the revenue file is less than 0.301.

(ii) Ifpis in fact less than 0.301, would it make you suspect that there are not enough numbers in the data file with leading 1's? Could this indicate that the books have been "cooked" by "pumping up" or inflating the numbers? Comment from the viewpoint of a stockholder. Comment from the perspective of the Federal Bureau of Investigation as it looks for money laundering in the form of false profits.

No. The revenue data file seems to include more numbers with higher first nonzero digits than Benford's law predicts.

Yes. The revenue data file does not seem to include more numbers with higher first nonzero digits than Benford's law predicts.

No. The revenue data file does not seem to include more numbers with higher first nonzero digits than Benford's law predicts.

Yes. The revenue data file seems to include more numbers with higher first nonzero digits than Benford's law predicts.

(iii) Comment on the following statement: If we reject the null hypothesis at level of significance, we have not provedH_oto be false. We can say that the probability isthat we made a mistake in rejectingH_o. Based on the outcome of the test, would you recommend further investigation before accusing the company of fraud?

We have not provedH₀to be false. Because our data lead us to reject the null hypothesis, more investigation is not merited.

We have provedH₀to be false. Because our data lead us to reject the null hypothesis, more investigation is not merited.

We have not provedH₀to be false. Because our data lead us to accept the null hypothesis, more investigation is not merited.

We have not provedH₀to be false. Because our data lead us to reject the null hypothesis, more investigation is merited.