b.lect2 - Outline Some Sampling Concepts Random Variables...

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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 Non-representative 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 Non-representative 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 Non-representative 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 Non-representative 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 Non-representative 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 Non-representative 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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b.lect2 - Outline Some Sampling Concepts Random Variables...

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