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Basic Analysis and Graphing - SAS

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Chapter 9<br />

Bootstrapping<br />

Approximate the Distribution of Statistics<br />

Bootstrapping is a re-sampling method for approximating the sampling distribution of a statistic. The data<br />

is re-sampled with replacement <strong>and</strong> the statistic is computed. This process is repeated to produce a<br />

distribution of values for the statistic.<br />

Bootstrapping is useful when estimating properties of a statistic (mean, st<strong>and</strong>ard error, <strong>and</strong> so on) <strong>and</strong><br />

performing inference, in the following situations:<br />

• The theoretical distribution of the statistic is complicated or unknown.<br />

• The sample size is too small for regular statistical inference.<br />

• Inference using parametric methods is not possible due to violations of assumptions.<br />

JMP provides bootstrapping for statistical platforms that support Frequency columns in which the rows are<br />

assumed to be independent.<br />

The Bootstrap option is on the right-click menu, separate from st<strong>and</strong>ard platform comm<strong>and</strong>s.<br />

Figure 9.1 Example of the Distribution for Bootstrapping Results

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