总体特征抽样调查的设计与分析课件.ppt
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1、CHAPTER-6Sampling error and confidence intervalserrorSection 1 sampling error of meanSection 2 t distribution Section 3 confidence intervals for the population meanSection 1 sampling error of mean A simple random sample is a sample of size n drawn from a population of size N in such a way that every
2、 possible random samples n has the same probability of being selected.Variability among the simple random samples drawn from the same population is called sampling variability,and the probability distribution that characterizes some aspect of the sampling variability,usually the mean but not always,
3、is called a sampling distribution.These sampling distributions allow us to make objective statements about population parameters without measuring every object in the population.Example 1 The population mean of DBP in the Chinese adult men is 72mmHg with standard deviation 5mmHg.10 adult participant
4、s was chosen randomly from the Chinese adult men,here we can calculate the sample mean and sample standard deviation.Supposing sampling 100 times,whats the result?linkage5,72N11,SX22,SX33,SX001001,SX If random samples are repeatedly drawn from a population with a mean and standard deviation ,we can
5、find:1 the sample means are different from the others 2 The sample mean are not necessary equal to population mean 3 The distribution of sample mean is symmetric about HOW TO EXPLORE THE SAMPLING DISTRIBUTION FOR THE MEAN?The difference between sample statistics and population parameter or the diffe
6、rence among sample statistics are called sampling error.vIn real life we sample only once,but we realize that our sample comes from a theoretical sampling distribution of all possible samples of a particular size.The sampling distribution concept provides a link between sampling variability and prob
7、ability.Choosing a random sample is a chance operation and generating the sampling distribution consists of many repetitions of this chance operation.When sampling from a normally distributed population with mean,the distribution of the sample mean will be normal with mean Central limit TheoremXWhen
8、 sampling from a nonnormally distributed population with mean,the distribution of the sample mean will be approximately normal with mean as long as n is larger enough(n50).Central limit Theorem Standard error(SE)can be used to assess sampling error of mean.Although sampling error is inevitable,it ca
9、n be calculated accurately.Nxnssxtheoretical value of SEestimation of SECalculation of standard error(SE)sSEnSElinkagevExample 5.2 One analyst chose randomly a sample(n=100)and measured their weights with a mean of 72kg and standard deviation of 15kg.Question:what is the standard error?Solution:5.11
10、00/15/XnSS Exercise 5.1 Consider a sample of measurement 100 with mean 121cm and standard deviation 7cm drawn from a normal population.Try to compute its standard error.7.0100/7/SXnsSolution:Section 2 t distribution1.Definition /)(XZ N(,2)N(0,1)10 )()()(2211kksXsXsXRandom samplingXXZ/)(/)(XZXXSXXobv
11、iously,XSUsually standard deviation is unknown,so we can only get s,then we can calculate 1nondistributitsXx,This sampling distribution was developed by W.S Gossett and published under the pseudonym“student”in 1908.it is,therefore,sometimes called the“students t distribution and is really a family o
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