Basic Analysis • Bootstrapping
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Bootstrapping
Approximate the Distribution of a Statistic through Resampling
Bootstrapping is available only in JMP Pro.
Bootstrapping is a resampling method for approximating the sampling distribution of a statistic. You can use bootstrapping to estimate the distribution of a statistic and its properties, such as its mean, bias, standard error, and confidence intervals. Bootstrapping is especially useful in the following situations:
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The theoretical distribution of the statistic is complicated or unknown.
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Inference using parametric methods is not possible because of violations of assumptions.
Note: Bootstrap is available only from a right-click in a report. It is not a platform command.
Figure 10.130 Bootstrapping Results for a Slope Parameter
Contents 
Overview of Bootstrapping
Example of Bootstrapping
Bootstrapping Window Options
Stacked Results Table
Unstacked Bootstrap Results Table
Analysis of Bootstrap Results
Additional Example of Bootstrapping
Statistical Details for Bootstrapping
Calculation of Fractional Weights
Bias-Corrected Percentile Intervals

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Help created on 10/11/2018