mailto:uumlib@uum.edu.my 24x7 Service; AnyTime; AnyWhere

Robust statistical normality transformation method with outlier consideration in bitcoin exchange rate analysis

Abu Bakar, Nashirah and Rosbi, Sofian (2017) Robust statistical normality transformation method with outlier consideration in bitcoin exchange rate analysis. International Journal of Advances in Scientific Research and Engineering, 3 (9). pp. 80-91. ISSN 24548006

[thumbnail of IJASRE 3 9 2019 80 91.pdf] PDF
Restricted to Registered users only

Download (602kB) | Request a copy

Abstract

Bitcoin is the first decentralized peer-to middlemen. The objective of this study is to evaluate the normality of data distribution for exchange rate of Bitcoin. The method implemented in this study is Shapiro the data distribution of exchange rate for Bitcoin follows non important to make sure the distribution of data follows normal distribution. The normal distribution is very crucial as the requirement for validity of statistical test.N distribution and to compute how likely it is for a random variable underlying the data set to be normally distributed. implemented two-stages of outliers detection and deletion process.The final results shows the distribution of rate with first difference is follow normal distribution with probability of 0.722.Result concluded the distribution of data after second stages of outlies deletion treatment data is highly volatile with existence of many outliers. The transformation process is highly important to make sure the Bitcoin data follows normal distribution that underlying critical assumption for statistical tests.

Item Type: Article
Uncontrolled Keywords: Crypto currency, Bitcoin, Exchange rate Outliers, Normality test.
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Divisions: Islamic Business School
Depositing User: Mrs. Norazmilah Yaakub
Date Deposited: 06 Aug 2019 08:31
Last Modified: 06 Aug 2019 08:31
URI: https://repo.uum.edu.my/id/eprint/26295

Actions (login required)

View Item View Item