# Good day Professor and Classmates

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 understanding scientific procedure. For Data Analysis I will be reading charts that involves understanding the situations or comparison in a math form behind the data involved in a statistical distribution.
Data analysis involves math such as Statistics, Linear Algebra, Calculus, Discrete Math, Optimization, operation research topics, functions, variables, equations, and graphs. By understanding all of these mathematical subjects I can become a successful Data Analysis. I must prepare myself to understand most of these mathematical subjects to make my job a bit easier in analyzing any data situation, that may involve from clinical studies, social lifestyle, business development, shopping or retail and etc.
Functions, variables, equations and graphs are used in data science studies during a 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” (Sarker, 2018). 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” (Sarker, 2018). Statistic is the basic understanding needed for data scientists to be able to describe basic algorithms. I may have to read some graphs to also understand probability on a case matter of event in any studies that I will have to describe its equation. (Rogojan, 2017)