Chapter7

Chapter7 - Chapter 7 Inferences Based on a Single Sample:...

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Chapter 7 Inferences Based on a Single Sample: Estimation with ConFdence Intervals 7.1 Identifying and Estimating the Target Parameter DeFnition 7.1 Target Parameter: The unknown population parameter (mean or pro- portion) that we are interested in estimating is called the target parameter. Parameter Phrases Data Type μ Mean (average) quantitative p Proportion (fraction, percentage) qualitative DeFnition 7.2 Point Estimator: A point estimator of a population parameter is a rule that tells you how to use the sample data to calculate a single number that can be used as an estimate of the population parameter. For example, the sample mean ¯ x is a point estimator for the population mean μ . DeFnition 7.3 Interval Estimator: An interval estimator of a population parameter is a rule that tells you how to calculate two numbers; an upper and a lower limit, based on the sample data, forming an interval within which the parameter is expected to lie. This pair of numbers is called an interval estimate or con±dence interval. The large number which located at the upper end of the interval, is called the upper conFdence limit (UCL) and the number that located at the lower extreme of the interval, is called the lower conFdence limit (LCL) . ConFdence width: The di²erence between UCL and LCL is called con±dence width. That is Con±dence width = UCL LCL 35
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7.2 Confdence Interval For a Population Mean: Nor- mal (z) Statistic Defnition 7.4 Confdence Coefficient: Confdence coefficient is the probability that a randomly selected confdence interval will enclose the parameter. The confdence coefficient measures the proportion oF samples that produce a confdence interval containing the pop- ulation parameter. A good confdence interval is as narrow as possible and has a confdence
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Chapter7 - Chapter 7 Inferences Based on a Single Sample:...

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