In summary, an (1-alpha) confidence interval for the mean is
an interval (a, b) such that the mean of the population, µ,
is inside it (i.e. a < µ < b) with (1-alpha) "confidence."
In The Concept
of Confidence Interval for the Mean we used one method of
calculating a and b. In this tutorial we present another method,
resampling, that produces a confidence interval called a bootstrap
confidence interval for the mean.
See Introduction
to The Bootstrap for more on resampling and the bootstrap.
We will use JMP.
First, make sure JMP is installed in this computer.(JMP is installed on all UT public computers)
To start JMP and open the data table we use as an example in the tutorial click Sample B data
The data table just opened looks like this:
Be sure to leave this data table open.
Then click JMP Bootstrap Macro
to get the following pop-up window:
Click Open to obtain the following JMP Bootstrap Macro dialog:
To generate 5000 bootstrap samples, using resampling, of the 62 observations in sample B complete this dialog box as follows:
Click OK and you will get the following JMP output:
To obtain the 95% bootstrap confidence interval for the mean proceed as follows:
Bootstarap confidence intervals depend on the resamples (5,000?)
that we obtain.
So if you do the steps above again you most likely get another
97.5% and 2.5% percentiles.and thus another
bootstrap confidence interval for the mean.
To create a bootstrap confidence interval for your data close all open JMP data tables and open the JMP data table with your data.
Then click JMP Bootstrap Macro and proceed as above.