Analyzing Bitcoin Blockchain Data: Insights, Coefficients and Model Adequacy

Abstract

The investigation examines the analysis of data derived from the Bitcoin blockchain with the aim of uncovering noteworthy facts pertaining to its behavior. The present research used regression analysis as a methodological framework to investigate the relationship that exists between the median confirmation time, the logarithm of the number of transactions that occur in a block, and the average transaction cost. This was done in order to determine whether or not there is a correlation between these three variables. The model's coefficients 0, 1, and 2 provide insightful information regarding the influence that these factors have on the confirmation times experienced by users of the Bitcoin network. Nevertheless, the study demonstrates that the chosen indicators, when examined in isolation, do not provide a comprehensive rationale for the observed variations in confirmation durations during the entire year of 2015. This observation implies the existence of uncontrolled variables that have not been taken into consideration. Further investigation is required to determine these variables and enhance the model's explanatory power. The procedure may involve the inclusion of additional variables, the analysis of non-linear transformations, and the evaluation of potential outliers. This study highlights the complexity of Bitcoin's confirmation time dynamics and underscores the need for a deeper understanding of the factors at play inside this growing cryptocurrency ecosystem.