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Data Analysis in Context-Based Statistical Modeling in Predictive Analytics

Data Analysis in Context-Based Statistical Modeling in Predictive Analytics
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Author(s): Selvan C. (National Institute of Technology, Tiruchirappalli, India) and S. R. Balasundaram (National Institute of Technology, Tiruchirappalli, India)
Copyright: 2021
Pages: 19
Source title: Handbook of Research on Engineering, Business, and Healthcare Applications of Data Science and Analytics
Source Author(s)/Editor(s): Bhushan Patil (Independent Researcher, India) and Manisha Vohra (Independent Researcher, India)
DOI: 10.4018/978-1-7998-3053-5.ch006

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Abstract

Data analysis is a process of studying, removing non-required data in the view level, and converting to needed patterns for sub decisions to make an aggregated decision. Statistical modeling is the process of applying statistical techniques in data analysis for taking proactive decisions depend requirements. The statistical modeling identifies relationship between variables, and it encompasses inferential statistics for model validation. The focus of the chapter is to analyze statistical modeling techniques in different contexts to understand the mathematical representation of data. The correlation and regression are used for analyzing association between key factors of companies' activities. Especially in business, correlation describes positive and negative correlation variables for analyzing the factors of business for supporting the decision-making process. The key factors are related with independent variables and dependent variables, which create cause and effect models to predict the future outcomes.

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