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Statistical Inference: A Short Course
book

Statistical Inference: A Short Course

by Michael J. Panik
July 2012
Intermediate to advanced
400 pages
9h 33m
English
Wiley
Content preview from Statistical Inference: A Short Course

9.4 A Sample Size Requirements Formula

Given Equation (9.16), let us solve for n or

(9.17) equation

Let us refer to this expression as the sample size requirements formula. What are the requirements? As noted above when employing Equation (8.9), they are “precision” and “reliability.” Hence Equation (9.17) provides us with the sample size required for a degree of precision of ±w/2 with 100(1 − α)% reliability. (Note that w/2 should always be expressed as a decimal.)

Example 9.4

Suppose we would like to estimate the proportion of individuals with a particular characteristic to within ±3% of p (the population proportion of individuals displaying this characteristic) with 95% reliability. How large of a sample should be taken? Here img = img = 1.96 and ±w/2 = ±0.03. Then from Equation (9.17),

img

Since we do not as yet have our sample, we cannot determine img. (It seems we have found ourselves “up a tree without a creek.”) There are three possible ways to resolve this difficulty:

1. Use a prior estimate of
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