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 ...

I 'm a big fan of Python for data analysis, but even I get curious about what else is available. R has long been the go-to ...

Data clustering is the process of programmatically grouping items that are made of numeric components. For example, suppose you have a dataset where each item represents a person's age, annual income ...

In studies on HSCT Kaplan–Meier (KM) estimates of survival curves and Cox proportional hazard models are widely used to describe survival trends and identify significant prognostic factors. All these ...

The adjusted r-squared is helpful for multiple regression and corrects for erroneous regression, giving you a more accurate ...

See how to join two data sets by one or more common columns using base R’s merge function, dplyr join functions, and the speedy data.table package. R has a number of quick, elegant ways to join data ...

We describe how to conduct a regression analysis for competing risks data. The use of an add-on package for the R statistical software is described, which allows for the estimation of the ...

Tax codes and incentive frameworks are no longer technical details of fiscal policy but, rather, front-line instruments of ...