Deep Data Stat - A Survey Analysis on Impact of Statistics in Data Science for Students

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Mohammed Harun Babu R
Shebana M


Data science is the most developing technology in recent years. The need of Data science is most important thing for the development of institutions. It is the process of analyzing, interpreting and decision making of data. There are various methods are included in the analysis of data science. Among those components, Statistics plays an important role. Without the help of statistics, the data cannot be analyzed. The arrangement and visualization of the data are also done with the use of Statistics. This paper explains the basic statistical methods used in the process of analyzing the data in Data science. As the basic terminologies are explained in the beginning, the advanced tools such as Hypothesis testing, Analysis of variance, t test, F test and Chi square tests are discussed. Then, the interconnection between the Data science and Statistics are explained with the calculations of two tests such as Tukey test and Dunnet test. Finally, the future development and the impact of Statistics in Data science have been explained.


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How to Cite
M. Babu R and S. M, “Deep Data Stat - A Survey Analysis on Impact of Statistics in Data Science for Students”, DataSCI, vol. 3, no. 1, pp. 17-22, Dec. 2020.