Overview of Bootstrapping for 2-sample means

Use Bootstrapping for 2-sample means to explore the sampling distribution of the difference between two population means of two independent groups and to estimate a confidence interval for the difference. You can also use Bootstrapping for 2-sample means to illustrate important statistical concepts. For observations to be independent, the value of a particular observation does not depend on any previous observation. If your observations are not independent, your results may not be valid. For more information, go to How are dependent and independent samples different?.

For example, a healthcare consultant wants to estimate the difference in patient satisfaction ratings of two hospitals. The consultant uses a bootstrap for 2-sample mean to examine the sampling distribution of the difference and to estimate a confidence interval for the difference in satisfaction ratings.

The confidence interval provides a range of likely values for the difference between the mean ratings.
The histogram shows the variation and shape of the sampling distribution.
Resampling techniques can show the effect of sample size on the sampling distribution.

For more detail on bootstrapping and resampling techniques, go to What is bootstrapping?

Where to find this analysis

Calc > Resampling > Bootstrapping for 2-Sample Means

When to use an alternate analysis

To determine whether the population means of two independent groups differ, use Randomization test for 2-sample means.