Question

What are distinctions between big data, applied math, (finance/ economics) and statistics?

Answer 1

There are many distinct things which differs big data, applied math, (finance/ economics) and statistics ,

i)

Data science combines the application of subjects namely computer science, software engineering, mathematics and statistics, programming, economics, and business management. Data science is based on the collection, preparation,analysis, management, visualization, and storage of large volumes of information hence many of the concept in statistics which is used in big data analytics

ii)

in other hand statistics usually means statistical inference the use of probability to make generalization

After collecting sample data and to characterize the likelihood that the generalization true.

iii)

Big data is closely integrated with data science and in fact, has evolved with big data in different applications and use cases. We are aware that, big data is mostly available in unstructured formats and contains non-numeric data.

iv) in applied mathematics data should be numeric ,whereas it can't happen in case of big data

v)

Useful information easily gets buried in big data and statistics which is made up of blogs, audio/video files, images, text messages, social networks,where's mathematics is a pure science

vi)

data scientists are considered to be familiar with business models and paradigms, who ask good business questions to obtain meaningful insights from given data sets.

In other hand

Statistics is another broad subject which deals with the study of data and is widely applied in numerous fields. Statistics provides the methodology for making conclusions from data. It gives different methods to gather data, analyze them and interpret results and is widely used by scientists, researchers, and mathematicians in solving problems

Though statistics provides the methods for data collection and analysis, it helps to obtain information from numerical and categorical data. Categorical data refers to unique data, examples are blood group of a person, marital status, etc. Statistics is highly significant in data related studies because it helps in,

• Deciding the type of data required to address a given problem
• Organizing and summarizing data

It not happen in case of big data and applied mathematics.

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