A research worker wishes to estimate the mean of a population by using sufficiently large sample. The probability is 0.95 that the sample mean will not differ from the true mean by more that 25% of the standard deviation. How large sample should be taken?
Solution:
We have "P(|\\bar{X}-\\mu|<\\sigma \/ 4)=0.95"
Divide by "\\sigma \/ \\sqrt{n}"
"{P}\\left(\\frac{\\bar{X}-\\mu}{\\sigma \/ \\sqrt{n}}<\\frac{\\sqrt n}{4}\\right)=0.95"
But "\\frac{\\bar{X}-\\mu}{\\sigma \/ \\sqrt{n}}" has a standard normal distribution.
And, "{P}(-1.96< \\text{Standard Normal} <1.96)=0.95"
So, "1.96=\\sqrt{n} \/ 4"
"\\Rightarrow 1.96\\times4=\\sqrt n\n\\\\ \\Rightarrow n=(7.84)^2=61.4656\n\\\\\\Rightarrow n=62"
So, a sample of 62 should be taken.
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