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Unformatted text preview: Outline Some Sampling Concepts Random Variables and Statistical Populations Lecture 2 Chapter 1: Basic Statistical Concepts Michael Akritas Michael Akritas Lecture 2 Chapter 1: Basic Statistical Concepts Outline Some Sampling Concepts Random Variables and Statistical Populations Some Sampling Concepts Simple Random and Stratified Sampling Sampling With and Without Replacement Nonrepresentative Sampling Random Variables and Statistical Populations Random variables Statistical Populations Michael Akritas Lecture 2 Chapter 1: Basic Statistical Concepts Outline Some Sampling Concepts Random Variables and Statistical Populations Simple Random and Stratified Sampling Sampling With and Without Replacement Nonrepresentative Sampling Michael Akritas Lecture 2 Chapter 1: Basic Statistical Concepts Outline Some Sampling Concepts Random Variables and Statistical Populations Simple Random and Stratified Sampling Sampling With and Without Replacement Nonrepresentative Sampling In Lecture 1 it was mentioned that sample properties approximate those of the population if the sample is suitably drawn. Michael Akritas Lecture 2 Chapter 1: Basic Statistical Concepts Outline Some Sampling Concepts Random Variables and Statistical Populations Simple Random and Stratified Sampling Sampling With and Without Replacement Nonrepresentative Sampling In Lecture 1 it was mentioned that sample properties approximate those of the population if the sample is suitably drawn. Here we explore this issue further. The key word is representativeness . Michael Akritas Lecture 2 Chapter 1: Basic Statistical Concepts Outline Some Sampling Concepts Random Variables and Statistical Populations Simple Random and Stratified Sampling Sampling With and Without Replacement Nonrepresentative Sampling In Lecture 1 it was mentioned that sample properties approximate those of the population if the sample is suitably drawn. Here we explore this issue further. The key word is representativeness . I For valid statistical inference the sample must be representative of the population. Michael Akritas Lecture 2 Chapter 1: Basic Statistical Concepts Outline Some Sampling Concepts Random Variables and Statistical Populations Simple Random and Stratified Sampling Sampling With and Without Replacement Nonrepresentative Sampling In Lecture 1 it was mentioned that sample properties approximate those of the population if the sample is suitably drawn. Here we explore this issue further. The key word is representativeness . I For valid statistical inference the sample must be representative of the population. For example, a sample of PSU basketball players is not representative of PSU students, if the characteristic of interest is height....
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This note was uploaded on 03/19/2009 for the course STAT 401 taught by Professor Akritas during the Spring '00 term at Penn State.
 Spring '00
 Akritas

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