The week's pick
Random Articles
Reseach Article
The Impact and Importance of Statistics in Data Science
| International Journal of Computer Applications |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 176 - Number 24 |
| Year of Publication: 2020 |
| Authors: Pallavi Gupta, Nitin V. Tawar |
10.5120/ijca2020920215
|
Pallavi Gupta, Nitin V. Tawar . The Impact and Importance of Statistics in Data Science. International Journal of Computer Applications. 176, 24 ( May 2020), 10-14. DOI=10.5120/ijca2020920215
Abstract
With the massive amount of data pouring in, the data science has become one of the most challenging yet promising field to deal with such tremendous quantity of data and bring out the quality information out for strategic business decisions. The way to data science begins with collection of huge amount of data which should be managed enough to start processing on it to analyze it. The statistics plays a vital role from molding data into the required format to final presentation of results to make it easy for the operations to be carried out on data almost in every step of data science. In this paper, we give a manifestation of how important the statistics is to provide the necessary tools and methods to handle data to provide deep insights into the data and how useful statistics is for quantification and analysis of data. We will discuss various tools and techniques of statistics used in data science beginning from measures of dispersion to advanced tools for visualization of results to be able to understand the role and importance of statistical approaches in data processing and analysis.
References
- Aggarwal, C.C. (ed.): Data Classification: Algorithms and Applications. CRC Press, Boca Raton (2014)
- Claus Weihs, Katja Ickstadt, Data Science: the impact of statistics, International Journal of Data Science and Analytics, Springer, https://doi.org/10.1007/s41060-018-0102-5
- Aue, A., Horváth, L.: Structural breaks in time series. J. Time Ser. Anal. 34(1), 1–16 (2013)
- Brown, M.S.: Data Mining for Dummies. Wiley, London (2014)
- Cao, L.: Data science: a comprehensive overview. ACM Comput. Surv. (2017). https://doi.org/10.1145/3076253
- Lütkepohl, H.: New Introduction to Multiple Time Series Analysis. Springer, Berlin (2010)
- Wu, J.: Statistics = data science? http://www2.isye.gatech.edu/ ~jeffwu/presentations/datascience.pdf (1997)
- https://www.edureka.co/blog/math-and-statistics-for-data-science/
- https://link.springer.com/journal/11634
- https://onlinecourses.nptel.ac.in/noc20_cs46 /unit?unit=16&lesson=17
- https://statistics.laerd.com/statistical-guides /descriptive-inferential- statistics.php
Index Terms
Keywords