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U-M STATS 250 - Confidence Intervals in Making Decisions
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STATS 250 1st Edition Lecture 8 Outline of Last Lecture I. CI Module 0: an Overview of Confidence IntervalsII. CI Module 1: Confidence Interval for a Population Proportion pOutline of Current Lecture I. CI Module 1: Confidence Interval for a Population Proportion p, part 2II. Using Confidence Intervals to Guide DecisionsCurrent LectureI. CI Module 1: Confidence Interval for a Population Proportion p, part 2a. What if we do not want a 95% confidence interval, but a different percentage?b. For each different % CI, there is a different multiplier, called z*i.ii. Therefore, if we want 90% confidence, we calculate pp ± 1.645√pp(1− pp)nc. By applying a margin of error, we create a conservative confidence interval for a population proportion: pp ± z∗¿2√n¿ = mi. This can be used to solve for sample size, n = z∗¿2 m¿¿2II. Using Confidence Intervals to Guide Decisionsa. Principle 1: a value not in the confidence interval can be rejected as a likely value of the population proportion. A value that is in a confidence interval is an “acceptable” possibility of a population proportionb. Principle 3: when the confidence intervals for proportions in two different populations do not overlap, it is reasonable to conclude that the two population proportions are differenti. If the intervals do not overlap, no conclusion can be


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U-M STATS 250 - Confidence Intervals in Making Decisions

Type: Lecture Note
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