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Exploring central limit theorem on world population density data

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

We do some exploration to Central Limit Theorem on a real dataset. We intend to conduct this study to a real data which has non-normal distribution. Under common sense, it is known that world population density data has right-skewed distribution. A resampling mechanism is done to the original data by varying sample size to study the properties of well-known Central Limit Theorem, such as normality of the sampling distribution and reduction of the standard deviation of sample data due to larger sample size.

Original languageEnglish
Title of host publicationAIP Conference Proceedings
EditorsNazrina Aziz, Haslinda Ibrahim, Jafri Zulkepli, Nazihah Ahmad, Syariza Abdul Rahman
PublisherAmerican Institute of Physics Inc.
Pages737-741
Number of pages5
ISBN (Electronic)9780735412743
DOIs
Publication statusPublished - 2014
Event3rd International Conference on Quantitative Sciences and Its Applications: Fostering Innovation, Streamlining Development, ICOQSIA 2014 - Langkawi, Kedah, Malaysia
Duration: 12 Aug 201414 Aug 2014

Publication series

NameAIP Conference Proceedings
Volume1635
ISSN (Print)0094-243X
ISSN (Electronic)1551-7616

Conference

Conference3rd International Conference on Quantitative Sciences and Its Applications: Fostering Innovation, Streamlining Development, ICOQSIA 2014
Country/TerritoryMalaysia
CityLangkawi, Kedah
Period12/08/1414/08/14

Keywords

  • central limit theorem
  • normal distribution
  • sample size

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