A Comparison between Normal and Non-Normal Data in Bootstrap

In the area of statistics, bootstrapping is a general modern approach to resampling methods. Bootstrapping is a way of estimating an estimator such as a variance when sampling from a certain distribution. The approximating distribution is based on the observed data. A set of observations is a popula...

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Main Author: Asmala, A.
Format: Article
Language:English
Published: HIKARI LTD 2012
Subjects:
Online Access:http://eprints.utem.edu.my/id/eprint/3613/
http://eprints.utem.edu.my/id/eprint/3613/1/ahmadAMS89-92-2012_published.pdf
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author Asmala, A.
author_facet Asmala, A.
author_sort Asmala, A.
building UTeM Institutional Repository
collection Online Access
description In the area of statistics, bootstrapping is a general modern approach to resampling methods. Bootstrapping is a way of estimating an estimator such as a variance when sampling from a certain distribution. The approximating distribution is based on the observed data. A set of observations is a population of independent and observed data identically distributed by resampling; the set is random with replacement equal in size to that of the observed data. The study starts with an introduction to bootstrap and its procedure and resampling. In this study, we look at the basic usage of bootstrap in statistics by employing R. The study discusses the bootstrap mean and median. Then there will follow a discussion of the comparison between normal and non-normal data in bootstrap. The study ends with a discussion and presents the advantages and disadvantages of bootstraps.
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spelling utem-36132021-10-01T12:25:21Z http://eprints.utem.edu.my/id/eprint/3613/ A Comparison between Normal and Non-Normal Data in Bootstrap Asmala, A. QA Mathematics In the area of statistics, bootstrapping is a general modern approach to resampling methods. Bootstrapping is a way of estimating an estimator such as a variance when sampling from a certain distribution. The approximating distribution is based on the observed data. A set of observations is a population of independent and observed data identically distributed by resampling; the set is random with replacement equal in size to that of the observed data. The study starts with an introduction to bootstrap and its procedure and resampling. In this study, we look at the basic usage of bootstrap in statistics by employing R. The study discusses the bootstrap mean and median. Then there will follow a discussion of the comparison between normal and non-normal data in bootstrap. The study ends with a discussion and presents the advantages and disadvantages of bootstraps. HIKARI LTD 2012 Article PeerReviewed application/pdf en http://eprints.utem.edu.my/id/eprint/3613/1/ahmadAMS89-92-2012_published.pdf Asmala, A. (2012) A Comparison between Normal and Non-Normal Data in Bootstrap. Applied Mathematical Sciences, 6 (92). 4547 -4560. ISSN 1312-885X http://www.m-hikari.com/
spellingShingle QA Mathematics
Asmala, A.
A Comparison between Normal and Non-Normal Data in Bootstrap
title A Comparison between Normal and Non-Normal Data in Bootstrap
title_full A Comparison between Normal and Non-Normal Data in Bootstrap
title_fullStr A Comparison between Normal and Non-Normal Data in Bootstrap
title_full_unstemmed A Comparison between Normal and Non-Normal Data in Bootstrap
title_short A Comparison between Normal and Non-Normal Data in Bootstrap
title_sort comparison between normal and non-normal data in bootstrap
topic QA Mathematics
url http://eprints.utem.edu.my/id/eprint/3613/
http://eprints.utem.edu.my/id/eprint/3613/
http://eprints.utem.edu.my/id/eprint/3613/1/ahmadAMS89-92-2012_published.pdf