Statistical Analysis Techniques
Carlo methods, the
bootstrap is a computationally intensive method but differs in that it
rely on an assumed data generation process.
Instead it relies on taking samples from an existing
data set. It
involves the following steps:
- Generate a random sample (with replacement) from the
original data set. The
sample should be
the same size as the original data set.
- Calculate the values for the test statistics or
using this randomly generated sample, and store the results.
- Repeat steps 1 and 2 many times (often thousands of
- Evaluate the performance of the estimator or the
the test statistic based on the set of stored results e.g. find the
standard error of the stored results.