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Chapter Goals After completing this chapter, you should be able to: Distinguish between a point estimate and a confidence interval estimate Construct and interpret a confidence interval estimate for a single population mean using both the z and t distributions Determine the required sample size to estimate a single population mean or a proportion within a specified margin of error Form and interpret a confidence interval estimate for a single population proportion 8-2 Overview of the Chapter Builds upon the material from Chapter 1 and 7 Introduces using sample statistics to estimate population parameters Because gaining access to population parameters can be expensive, time consuming and sometimes not feasible Confidence Intervals for the Population Mean, μ when Population Standard Deviation σ is Known when Population Standard Deviation σ is Unknown Confidence Intervals for the Population Proportion, p Determining the Required Sample Size for means and proportions 8-3 Estimation Process Confidence Level Random Sample Mean (point estimate) I am 95% Population confident that Mean μ is between (mean, μ, is x = 50 40 & 60. unknown) Sample confidence interval 8-4 Point Estimate Suppose a poll indicate that 62% (sample mean) of the people favor limiting property taxes to 1% of the market value of the property. The 62% is the point estimate of the true population of people who favor the property-tax limitation. EPA tested average Automobile Mileage (point estimate) 8-5 Confidence Interval The point estimate (sample mean) is not likely to exactly equal the population parameter because of sampling error. Probability of “sample mean = population mean” is zero Problem: how far the sample mean is from the population mean. To overcome this problem, “confidence interval” can be used as the most common procedure. 8-6
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