A Justification for Using Statistics

Statistics is "the discipline that concerns the collection, organization, analysis, interpretation and presentation of data" (Wikipedia, 2025).  It seems therefore prudent (and perhaps even enjoyable) to attempt applying the approaches and tools of such a discipline to the data set offered by Drupal.  

Digging deeper, Statistics to be the ideal discipline to turn to in circumstances where data has been deemed uncertain, considering that "Statistics is both the science of uncertainty and the technology of extracting information from data" (Hand, 2010), which are the two overriding considerations of undertaking this work. 

Two more things make Statistics stand out as the ideal tool to help power this investigation:  Data Quality, an important sub-discipline of Statistics, was developed to help improve the quality of data sets so as to increase "the capability of data to be used effectively, economically and rapidly to inform and evaluate decisions" (Karr et al, 2002).  Also, Exploratory Data Analysis, yet another sub-discipline of Statistics and one that is frequently used in conjunction with Data Quality, was developed, according to IBM (2025), to:

"...help look at data before making any assumptions. It can help identify obvious errors, as well as better understand patterns within the data, detect outliers or anomalous events, find interesting relations among the variables."

With a defence as to the relevance and efficacy of applying Statistics to the Drupal data set finished, we can now move on to the fun stuff:  Examining and interpreting the Usage statistics for the Drupal core data set for the period December 22 - 28, 2024.