Confidence Intervals… continued
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Transcript of Confidence Intervals… continued
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Confidence Intervals…continued
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How confidence intervals behave What we would like:
High confidence Small margin of error
Remember: For confidence intervals for population mean
margin of error =
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Margin of error = How can we make it smaller?
1. Make z* smaller.
2. gets smaller.
3. n gets larger.
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Example 10.6, p. 550 Suppose that the manufacturer in Example 10.5
(p.546) wants 99% confidence rather than 90%. The critical value for 99% confidence is z* = 2.575. The 99% confidence interval for µ based on an SRS of 20 video monitors with mean mV is
306 . 3 ±(2 .575)43√20
=¿306 . 3 ± 24 .8=¿(281 . 5 , 331. 1)
From Example 10.5, we had a margin of error of 15.8, giving the 90% confidence interval of
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Example 10.6, p. 550 Suppose that the manufacturer in Example 10.5 (p.546) wants 99%
confidence rather than 90%. The critical value for 99% confidence is z* = 2.575. The 99% confidence interval for µ based on an SRS of 20 video monitors with mean mV is
99 % confidence interval of 90% confidence interval of
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Margin of error So how do we get a high confidence level with a
small margin of error?PLAN AHEAD!!!
We get to choose our sample size!!!!
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Determining Sample Size Example 10.7, p. 551Company management wants a report of the mean screen tension for the day’s production accurate to within ±5 mV with 95% confidence. How large a sample of video monitors must be measured to comply with this request?
So we want the margin of error (m) to be less than 5.
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Example 10.7, p. 551For the a 95% confidence level, the critical value is .
Example 10.5 told us that .
So take a sample of at 285 video screens.
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Sample Size for Desired Margin of Error
To determine the sample size n that will yield a confidence interval for a population mean with a specified margin of error m, set the expression for the margin of error to be less than or equal to m and solve for n:
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Some Cautions with Confidence Intervals
Any formula is correct only in specific circumstances: (some are listed on p. 553 in your book)
• Data must be from an SRS from the population.
• Formula not correct for more complex sampling designs
• Fancy formulas can’t rescue badly produced data
• Outliers can have a large effect on the confidence interval
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Some Cautions with Confidence Intervals
Most importantly: The margin of error in a confidence interval covers only random sampling errors.
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Homework P. 550: 10.8, 10.9 P. 552: 10.12 P. 554: 10.15, 10.17
DUE: Friday