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

• Main Authors: Abu Bakar, Nashirah, Rosbi, Sofian
• Format: Article
• Language: English
• Published: IJASRE 2017
• Subjects: QA75 Electronic computers. Computer science
• Online Access: http://repo.uum.edu.my/26295/1/IJASRE%203%209%202019%2080%2091.pdf; http://repo.uum.edu.my/26295/; http://doi.org/10.7324/IJASRE.2017.32522
• Institution: Universiti Utara Malaysia

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.