DATASET BOOTSTRAP SAMPLING

Performs bootstrap resampling on a dataset to estimate statistical properties (mean, standard deviation, or raw samples) for selected columns with a configurable confidence interval. Use this worker when you need robust distributional estimates or confidence bounds from an existing tabular dataset without making parametric assumptions.

When to use

Classification: process.

Tagged: bootstrap, confidence_interval, mean, monte_carlo, resampling, sampling, standard_deviation, statistics.

Inputs

Label ID Type Default Required Description
Dataset dataset_1 dataset   Input tabular dataset to be bootstrap-resampled; must contain at least the columns specified in the ‘columns’ input.
Columns columns scalar One or more column names from dataset_1 on which bootstrap statistics will be computed; multi-select list populated dynamically from the connected dataset.
Number of Samples num_samples scalar 5000   Number of bootstrap resample iterations to draw; default is 5000 — increase for tighter confidence estimates, decrease to reduce runtime.
Confidence Interval conf_int select 90   Confidence interval level (%) used to compute lower and upper bounds on the bootstrapped statistic; choose 90, 95, or 99 (default 90).
Stat Type stat_type select mean   Statistic to compute across bootstrap samples: ‘mean’ (default), ‘standard deviation’, or ‘samples’ to return the raw resampled values.
Track Raw Samples track_raw select no   Whether to retain all raw bootstrap sample values in the output (‘yes’) or return only the aggregated statistic and confidence bounds (‘no’, default).
Return Type return_type select mean    

Outputs

Label ID Type Description
Output dataset_output dataset Output dataset containing the bootstrapped statistic (mean or std dev) and confidence-interval bounds for each selected column, or the full raw resampled values if track_raw is enabled.

Disciplines

  • data.dataset.transform
  • data.statistics
  • design_exploration.reliability

Runnable example

A runnable example is registered for this worker. Open the example workflow on the d3VIEW canvas: /api/workflow/example?id=dataset_bootstrap_sampling


Auto-generated from transformation schema. Worker id: dataset_bootstrap_sampling. Schema hash: 1a4be3a0bf7f. Hand-curated docs in workerexamples/ override this page when present.