8.1 Estimation Using Normal

# Population mean known interval estimate of a

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Unformatted text preview: ignificance ◦ Interval Estimation ◦ ◦ (1–α) is the confidence coefficient zα 2 is the z value providing an area of α/2 in the upper tail of the standard normal probability distribution σ is the population standard deviation σ is the standard error of the sampling distribution of mn ean zα 2 ◦ σ n σ n is the margin of error margin of error is always found by multiplying the z value for 1 tail by the standard error. Population Mean: σ Known Interval Estimate of a Population Mean: σ Known Interval Estimate also called Confidence Interval x ± margin of error ◦ ◦ x is the sample mean α is the level of significance ◦ Interval Estimation ◦ ◦ (1–α) is the confidence coefficient σ n “We are 95% confident that the population mean is between… and …”” zα 2 is the z value providing an area of α/2 in the upper tail of the standard normal probability distribution σ is the population standard deviation σ is the standard error of the sampling distribution of mn ean zα 2 ◦ x ± zα 2 σ n is the margin of error Population Mean: σ Known KEY IDEA: Interval estimate is the point estimate ± value from probability distribution multipliedInterval Estimate by standard error— this is a reoccurring formula. of a Population Mean: σ Known x ± margin of error ◦ ◦ Interval Estimation ◦ ◦ is the sample mean α is the level of significance (1–α) is the confidence coefficient zα 2 is the z value providing an area of α/2 in the upper tail of the standard normal probability distribution σ is the population standard deviation σ is the standard error of the sampling distribution of mn ean zα 2 ◦ σ n x ◦ x ± zα 2 σ n is the margin of error σ Known Example If the sample mean is found to be 362.3, find the 95% confidence interval (i.e., interval estimate) for the population mean. Interval Estimation σ Known Example If the sample mean is found to be 362.3, find the 95% confidence interval (i.e., interval estimate) for the population mean. Population distribution: ◦ Normal distribution:...
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