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Predictive analysis refers to the use of historical data and analyzing it using statistics to predict future events.
It takes place in seven steps, and these are: defining the project, data collection, data analysis, statistics, modeling, and model monitoring.
Many businesses rely on predictive analysis to determine the relationship between historical data and predict a future pattern.
These patterns help businesses with risk analysis, financial modeling, and customer relationship management.
Predictive analysis can be used in almost all sectors, for instance, healthcare, telecommunications, oil and gas, insurance, travel, retail, financial services, and pharmaceuticals.
Several programming languages can be used in predictive analysis, such as R, MATLAB, Python, and Golang.
What Is R, And Why Is It Used For SEO?
R is a package of free software and programming language developed by Robert Gentleman and Ross Ihaka in 1993.
It is widely used by statisticians, bioinformaticians, and data miners to develop statistical software and data analysis.
R consists of an extensive graphical and statistical catalog supported by the R Foundation and the R Core Team.
It was originally built for statisticians but has grown into a powerhouse for data analysis, machine learning, and...
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