People were polled on how many books they read the previous year. Initial survey results indicate that $\mathrm{s}=12.4$ books Complete parts (a) through (d) below.
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(c) What effect does doubling the required accuracy have on the sample size?
A. Doubling the required accuracy nearly quarters the sample size.
B. Doubling the required accuracy nearly halves the sample size.
C. Doubling the required accuracy nearly quadruples the sample size
D. Doubling the required accuracy nearly doubles the sample size.
(d) How many subjects are needed to estimate the mean number of books read the previous year within six books with $99 \%$ confidence?

This $99 \%$ confidence level requires $\square$ subjects. (Round up to the nearest subject.)

Step 1 ：For part (c), the effect of doubling the required accuracy on the sample size is that it nearly quadruples the sample size. This is because the required accuracy is inversely proportional to the square of the sample size.

Step 2 ：For part (d), we need to estimate the mean number of books read the previous year within six books with 99% confidence. To do this, we use the formula for the sample size in a confidence interval estimation for the mean, which is \(n = (Z*σ/E)^2\), where n is the sample size, Z is the Z-score (which depends on the confidence level), σ is the standard deviation, and E is the margin of error (which is the required accuracy).

Step 3 ：We know that σ = 12.4 books, E = 6 books, and the Z-score for a 99% confidence level is approximately 2.576. Substituting these values into the formula, we get \(n = (2.576*12.4/6)^2\).

Step 4 ：Calculating the above expression, we find that the required number of subjects to estimate the mean number of books read the previous year within six books with 99% confidence is \(\boxed{29}\).