101A_SE_in_paired_and_two_sample_tests_and_review_v2_F08

101A_SE_in_paired_and_two_sample_tests_and_review_v2_F08 -...

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Statistics 101A Professor Esfandiari Effect of independent and dependent data on standard error Review of material discussed so far I The effect of independent and dependent data on standard error In the previous lecture we talked about the two-sample and paired sample test of the mean. We explained that in two-sample tests the data are independent, whereas, in the case of paired data such as pre-post data or more generally repeated measures data or in the case of paired data (such as twins), the data are dependent or correlated with each other. This is an important distinction to make both from a design and a mathematical point of view and how it impacts the calculation of standard error. From a design point of view in the two-sample case the subjects are randomly assigned to the two groups and a subjects who appears in one group cannot appear in the other group and the selection of one subject does not depend on the selection of any other subject. Whereas, in the case of “repeated measures” the same subject is measured twice. In the case of “paired sample”, the choice of one subject is dependent on the choice of the other subject in the pair. For instance if a twin gets selected to participate in the study, automatically the other twin will also be in the study or if a husband gets selected to be in the study, the wife will automatically become part of the study. Let us take a numerical example: (control = 0, experimental = 1) Group Pre post gain 1 20 30 10 1 22 33 11 1 23 32 9 1 24 33 9 1 25 35 10 1 26 34 8 1 27 36 11 1 28 37 10 1 29 39 10 0 30 40 10 0 21 22 1 0 22 24 2 0 23 25 2 0 24 26 2 0 25 25 0 0 26 27 1 0 27 28 1 0 28 28 0 0 29 30 1 0 30 31 1 1
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GROUP: 1.00 ex perimental
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This note was uploaded on 06/22/2011 for the course STAT 101 taught by Professor Esfandi during the Spring '11 term at UCLA.

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101A_SE_in_paired_and_two_sample_tests_and_review_v2_F08 -...

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