... – randomly "sample" all the m+n observations so there
are m in group1 and n in group2.
– compute the difference between the means of the two
groups of the "sampled" vector, D.
– repeat this procedure a large number of times (1000
or larger). For an upper-tailed test, calculate the
empirical p-value: ...
... A sampling method is independent when the individuals selected for one sample do not
dictate which individuals are in a second sample.
Randomly divide seniors into two groups then test using different curriculums.
Randomly divide patients into two groups and test a new medication giving one
... Example. We can use your height data to test the hypothesis that the mean height of a male Gonzaga undergraduate is 70
inches (because a web site told me that the mean height of a 20 year old American male is about 70 inches). Formally, we'll
test Ho : p = 70 against Hi : p 0 70. We assume that the ...
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.