- Contents
- Learn about JMP
- Introduction to Basic Analysis
- Distributions
- Using the Distribution Platform
- Overview of the Distribution Platform
- Example of the Distribution Platform
- Launch the Distribution Platform
- The Distribution Report
- Distribution Platform Options
- Options for Categorical Variables
- Options for Continuous Variables
- Fit Distributions
- Additional Examples of the Distribution Platform
- Statistical Details for the Distribution Platform
- Statistical Details for Standard Error Bars
- Statistical Details for Quantiles
- Statistical Details for Summary Statistics
- Statistical Details for the Normal Quantile Plot
- Statistical Details for the Wilcoxon Signed Rank Test
- Statistical Details for the Standard Deviation Test
- Statistical Details for Normal Quantiles
- Statistical Details for Saving Standardized Data
- Statistical Details for Prediction Intervals
- Statistical Details for Tolerance Intervals
- Statistical Details for Capability Analysis
- Statistical Details for Continuous Fit Distributions
- Statistical Details for Discrete Fit Distributions
- Statistical Details for Fitted Quantiles
- Statistical Details for Fit Distribution Options
- Introduction to Fit Y by X
- Bivariate Analysis
- Examine Relationships between Two Continuous Variables
- Example of Bivariate Analysis
- Launch the Bivariate Platform
- The Bivariate Plot
- Fitting Commands and General Options
- Fit Mean
- Fit Line and Fit Polynomial
- Fit Special
- Fit Spline
- Kernel Smoother
- Fit Each Value
- Fit Orthogonal
- Density Ellipse
- Nonpar Density
- Fit Robust
- Histogram Borders
- Group By
- Fitting Menus
- Additional Examples of the Bivariate Platform
- Statistical Details for the Bivariate Platform
- Statistical Details for Fit Line
- Statistical Details for Fit Spline
- Statistical Details for Fit Orthogonal
- Statistical Details for the Summary of Fit Report
- Statistical Details for the Lack of Fit Report
- Statistical Details for the Parameter Estimates Report
- Statistical Details for the Smoothing Fit Reports
- Statistical Details for the Correlation Report
- Oneway Analysis
- Examine Relationships between a Continuous Y and a Categorical X Variable
- Overview of Oneway Analysis
- Example of Oneway Analysis
- Launch the Oneway Platform
- The Oneway Plot
- Oneway Platform Options
- Quantiles
- Means/Anova and Means/Anova/Pooled t
- Analysis of Means Methods
- Compare Means
- Nonparametric
- Unequal Variances
- Equivalence Test
- Robust Fit
- Power
- Normal Quantile Plot
- CDF Plot
- Densities
- Matching Column
- Additional Examples of the Oneway Platform
- Example of an Analysis of Means Chart
- Example of an Analysis of Means for Variances Chart
- Example of the Each Pair, Student’s t Test
- Example of the All Pairs, Tukey HSD Test
- Example of the With Best, Hsu MCB Test
- Example of the With Control, Dunnett’s Test
- Example Contrasting All of the Compare Means Tests
- Example of the Unequal Variances Option
- Example of an Equivalence Test
- Example of the Robust Fit Option
- Example of the Power Option
- Example of a Normal Quantile Plot
- Example of a CDF Plot
- Example of the Densities Options
- Example of the Matching Column Option
- Statistical Details for the Oneway Platform
- Contingency Analysis
- Examine Relationships between Two Categorical Variables
- Example of Contingency Analysis
- Launch the Contingency Platform
- The Contingency Report
- Contingency Platform Options
- Mosaic Plot
- Contingency Table
- Tests
- Analysis of Means for Proportions
- Correspondence Analysis
- Cochran-Mantel-Haenszel Test
- Agreement Statistic
- Relative Risk
- Two Sample Test for Proportions
- Measures of Association
- Cochran Armitage Trend Test
- Exact Test
- Additional Examples of the Contingency Platform
- Example of Analysis of Means for Proportions
- Example of Correspondence Analysis
- Example of a Cochran Mantel Haenszel Test
- Example of the Agreement Statistic Option
- Example of the Relative Risk Option
- Example of a Two Sample Test for Proportions
- Example of the Measures of Association Option
- Example of the Cochran Armitage Trend Test
- Statistical Details for the Contingency Platform
- Logistic Analysis
- Examine Relationships between a Categorical Y and a Continuous X Variable
- Overview of Logistic Regression
- Example of Nominal Logistic Regression
- Launch the Logistic Platform
- The Logistic Report
- Logistic Platform Options
- Additional Examples of Logistic Regression
- Statistical Details for the Logistic Platform
- Matched Pairs Analysis
- Compare Measurements on the Same Subject
- Overview of the Matched Pairs Platform
- Example of Comparing Matched Pairs
- Launch the Matched Pairs Platform
- The Matched Pairs Report
- Matched Pairs Platform Options
- Example Comparing Matched Pairs across Groups
- Statistical Details for the Matched Pairs Platform
- Bootstrapping
- Tabulate
- References
- Index
Chapter 10
Bootstrapping
Approximate the Distribution of a Statistic through Resampling
About Bootstrapping
Bootstrapping is a re-sampling method for approximating the sampling distribution of a statistic. The data is re-sampled with replacement and the statistic is computed. This process is repeated to produce a distribution of values for the statistic.
Bootstrapping is useful when estimating properties of a statistic (mean, standard error, and so on) and performing inference, in the following situations:
• The theoretical distribution of the statistic is complicated or unknown.
• The sample size is too small for regular statistical inference.
• Inference using parametric methods is not possible due to violations of assumptions.
JMP provides bootstrapping for statistical platforms that support Frequency columns in which the rows are assumed to be independent.
The Bootstrap option is on the right-click menu, separate from standard platform commands.
Figure 10.1 Example of the Distribution for Bootstrapping Results
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