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Section 9.1 Confidence Intervals: The Basics Point Estimator and
Section 9.1 Confidence Intervals: The Basics Point Estimator and

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... With careful random sampling, there’s a good chance that the %’s in the sample will be close to the %’s in the population of interest. But the “answers” we get are random (because of the random sampling). Each different sample is going to give a different answer. In Statistics we use what we know ab ...
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STAT 3321 Test 2 – Summer 2008 – Name:

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... 4.) Suppose you have a random sample of 100 SFU students. In response to a short survey, each student reported the usual number of hours per week that he/she spent working off-campus (Xi), and the usual number of hours per week that he/she spent engaged in social activities (Yi). The university has ...
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Resampling (statistics)

In statistics, resampling is any of a variety of methods for doing one of the following: Estimating the precision of sample statistics (medians, variances, percentiles) by using subsets of available data (jackknifing) or drawing randomly with replacement from a set of data points (bootstrapping) Exchanging labels on data points when performing significance tests (permutation tests, also called exact tests, randomization tests, or re-randomization tests) Validating models by using random subsets (bootstrapping, cross validation)Common resampling techniques include bootstrapping, jackknifing and permutation tests.
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