Samuel Berger

Abstract:

Data Science focuses on the mathematics and statistical relationships to help filter the data and make accurate analysis as raw data can prove deceptive not by design, but by the methods of collection, processing and interpretation.  Analyzing data is its own science for many inherent reasons such as understanding of how to normalize the data using Relational Algebra [1].  The importance of creating precise data structures when handling, processing and manipulating mass amounts of data cannot be understated and can only be achieved accurately using Relational Algebra for a host of reasons.  You must also master how to query the data using standard query language and how to analyze the data using advanced statistical methods such as regression testing, etc.

In this lecture you will see a major universal world-wide problem [2] analyzed from a different prospective.  We will also look at other objective related data [3] [4] to see if the raw data may prove to be misleading prior to initializing our studies. This data you have all seen in raw form and now you will see how a data scientist brakes down and analyzes the underlying data to give new insights and even point to new studies and research.