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Statistical Reasoning for Everyday Life
Statistical Reasoning for Everyday Life

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Chapter 1: Statistics

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... are confident that the estimate from just one sample is likely to be accurate. On the other hand, if our estimated parameter changes quite markedly for different samples of data, then we are not at all confident that the estimate from just one sample is likely to be accurate. Whenever we report an e ...
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... The Excel worksheet states p-value = 4.501E-11 6. Determine whether to reject H0. Because p–value <  = .01, we reject H0. ...
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... considered as a binomial experiment. As we learned from Ch 8.2, the best point estimate of p , the population proportion, is a x sample proportion, pˆ  , provided the sample is obtained by n 1) simple random sampling ; 2) np0 (1  p0 )  10 to guarantee that a normal distribution can be used to tes ...
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6. Sampling and Estimation

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Sample size determination

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MATH371 – Introduction to Probability and Statistics

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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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