3 grams given in problem standard error of the mean 3

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Unformatted text preview: Mean μ = ? grams—determine interval estimate Standard deviation σ = 15 grams 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: Mean μ = ? grams—determine interval estimate Standard deviation σ = 15 grams Sampling distribution for Sample Size n = 25: ◦ Normal distribution (population follows normal distribution): Interval Estimation Sample mean = 362.3 grams (given in problem) Standard error of the mean: σ =σ = 3 x 2 5 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: Mean μ = ? grams—determine interval estimate Standard deviation σ = 15 grams Sampling distribution for Sample Size n = 25: ◦ Normal distribution (population follows normal distribution): Interval Estimation Sample mean = 362.3 grams (given in problem) Standard error of the mean: σ =σ = 3 x 2 5 Confidence Interval . 3. 9 8 margin of error is 5.88: z σ z531 ⋅ = 8 α x=02 = 6 5 2 0 . 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: Mean μ = ? grams—determine interval estimate Standard deviation σ = 15 grams Sampling distribution for Sample Size n = 25: ◦ Normal distribution (population follows normal distribution): Interval Estimation Sample mean = 362.3 grams (given in problem) Standard error of the mean: σ =σ = 3 x 2 5 Confidence Interval ◦ . 3. 9 8 margin of error is 5.88: z σ z531 ⋅ = 8 α x=02 = 6 5 2 0 . ◦ therefore, interval is 3 23 58 6. ± . 8 3 64 ≤µ 3 81 5. 2 ≤ 6. 8 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: Mean μ = ?...
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This document was uploaded on 03/05/2014.

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