Bootstrapping is a statistical procedure that resamples a single dataset to create many simulated samples. This process allows you to calculate standard errors, construct confidence intervals, and perform hypothesis testing for numerous types of sample statistics. Bootstrap methods are alternative approaches to traditional hypothesis testing and are notable for being easier to understand and valid for more conditions.
This repo aims to show how to use MATLAB for bootstrapping.
The example is based on Spiegelhalter, David. 2019. The Art of Statistics: Learning from Data, Pelican Books, ISBN 978-0241398630.
The dataset used is available at dspiegel29/ArtofStatistics: Code for 'The Art of Statistics'- Copyright (c) 2019 David Spiegelhalter
Instructions to Run:
- Open the bootstrapping_data.mlx Live script.
- Read through the Live script to understand the context and the application and run the file to execute the code.
Live scripts are program files that contain your code, output, and formatted text together in a single interactive environment called the Live Editor. In live scripts, you can write your code and view the generated output and graphics along with the code that produced it. Add formatted text, images, hyperlinks, and equations to create an interactive narrative that you can share with others.
MathWorks Products (https://www.mathworks.com)
Requires MATLAB release R2024a or newer
The license is available in the License.txt file in this GitHub repository.