Business Statistics A Decision-Making Approach, 6th ：业务统计决策方法，第六.ppt

Confidence Intervals and Hypothesis Testing Module Goals BASIC QUESTIONS: ? What is a STATISTIC? ? What is the DISTRIBUTION of a STATISTIC? ? What’s the difference between the DISTRIBUTION of a STATISTIC and the DISTRIBUTION of X, the Underlying r.v.? ? Why do we CARE ? Module Goals – Busy Version After completing this module, you should be able to: Explain what a statistic is, why we use it(them), and why it has a distribution Distinguish between a point estimate and a confidence interval estimate, and Construct and interpret a confidence interval estimate for a single population mean using both the z and t distributions Form and interpret a confidence interval estimate for a single population proportion Perform Hypothesis Testing Confidence Intervals Content of this chapter Confidence Intervals for the Population Mean, μ when Population Standard Deviation σ is Known when Population Standard Deviation σ is Unknown Determining the Required Sample Size Confidence Intervals for the Population Proportion, p Statistics X is r.v.,  T is statistic,  T is an ESTIMATOR of a parameter, e.g., m A statistic T has a distribution, e.g.  If know then you can make probability statements about the parameter you’re rtying to estimate. Point and Interval Estimates A point estimate is a single number, a confidence interval provides additional information about variability Point Estimates Confidence Intervals General Idea: How much uncertainty is associated with a point estimate of a population parameter? An interval estimate provides more information about a population characteristic than does a point estimate Such interval estimates are called confidence intervals Confidence Interval Estimate An interval gives a range of values: Takes into consideration variation in sample statistics from sample to sample Based on observation from 1 sample Gives information about closeness to unknown population parameters Stated in terms of level of confidence Never 100% sure Es