方差比置信区间示意图两个总体方差比的区间估计.PPT

Estimating Chapter 10 Chapter 12 Review 1.Random Variables 2.Sampling Distributions for Sample Proportions 3. Sampling Distributions for Sample Means 4. What to Expect in Other Situations: CLT 5.Sampling Distribution for Any Statistic Learning objectives We will learn how to use a realized value of a sample statistics to guess about the unknown value of the corresponding parameter. It is called estimation 1. Point Estimating: a single estimate of a population made by looking at sample statistics. [1] Moment Method, (MM) [2] Maximum Likelihood Estimate (MLE) 2. Interval Estimating: we can construct an interval estimate which adds more confidence to our estimation of the population mean or proportion. Confidence interval, an interval of estimates that is likely to capture the population value. The primary objective of this chapter is to describe how to calculate and interpret a confidence interval. Learning Contents , Emphases and Difficulties Confidence interval estimate [1] for one proportion [2] for one mean (or mean difference of pairs) [3] for difference between two means (un-pooled) [4] for difference between two means (pooled) [5] for difference between two proportions (independent sample) Teaching methods Both English and Chinese Both PPT and writing on blackboard Section 1: estimating proportions with confidence intervals 10.1 The Language and Notation of Estimation P330 1.Unit: an individual person or object to be measured. 2.Population (or universe): the entire collection of units about which we would like information or the entire collection of measurements we would have if we could measure the whole population. 3.Sample: the collection of units we will actually measure or the collection of measurements we will actually obtain. 4.Sample size: the number of units or measurements in the sample, denoted by n. More Language and Notation of Estimation 5.Population proportion: the fraction of the population that has a certain trait/characteristic o