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Good day Professor and Classmates,
My major at Berkeley College is IT Management concentrating on data or network analysis as an opportunity choice in the IT field. Data analysis is very close to scientific process because it involves understanding the technology programming in depth. I will be reading charts that involves understanding the math behind the data. Data science has a variety form of field, it may subject from health diagnosis or social behavior in a project that may involve statistical distributions.
Data analysis involves math such as Statistics, Linear Algebra, Calculus, Discrete Math, Optimization, operation research topics, functions, variables, equations, and graphs. In understanding all these subjects are serious to make a data analysis successful. I must prepare myself to understand most of these mathematical subjects to make my job a bit easier in analyzing any data.
Functions, variables, equations and graphs are used in data science studies during binary search. One needs to understand the dynamics of logarithms and recurrence equations. Even analyzing a time sequence, I would have to review periodic functions. A function gives an affiliation in an equation between perceptions or objects in a mathematical form. Variables can measure the quantity in a problem especially on an economic data.
Statistics and probability may give an initial identity in a debate of any resolutions needed to be solved in a mathematic sense. When a data scientist needs to find how to serve the business in reducing expense cost and increase revenues a statistic math is used for this case. Statistic is the basic understanding needed for data scientists to be able to describe basic algorithms.

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