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RStudio IDE (or RStudio) is an integrated development environment for R, a programming language for statistical computing and graphics. It is available in two formats: RStudio Desktop is a regular desktop application while RStudio Server runs on a remote server and allows accessing RStudio using a web browser .
Comma-separated values (CSV) is a text file format that uses commas to separate values, and newlines to separate records. A CSV file stores tabular data (numbers and text) in plain text, where each line of the file typically represents one data record. Each record consists of the same number of fields, and these are separated by commas in the ...
R is a programming language for statistical computing and data visualization.It has been adopted in the fields of data mining, bioinformatics and data analysis. [9]The core R language is augmented by a large number of extension packages, containing reusable code, documentation, and sample data.
There is a Log Code tab, which replicates the R code for any activity undertaken in the GUI, which can be copied and pasted. Rattle can be used for statistical analysis, or model generation. Rattle allows for the dataset to be partitioned into training, validation and testing. The dataset can be viewed and edited.
R Tools for Visual Studio (RTVS) is a plug-in for the Microsoft Visual Studio integrated development environment (IDE), used to provide support for programming in the language R.
Free software portal; Shiny is a web framework for developing web applications (apps), originally in R and since 2022 in python.It is free and open source. [2] It was announced by Joe Cheng, CTO of Posit, formerly RStudio, in 2012. [3]
In statistics, Mallows's, [1] [2] named for Colin Lingwood Mallows, is used to assess the fit of a regression model that has been estimated using ordinary least squares.It is applied in the context of model selection, where a number of predictor variables are available for predicting some outcome, and the goal is to find the best model involving a subset of these predictors.
Tukey defined data analysis in 1961 as: "Procedures for analyzing data, techniques for interpreting the results of such procedures, ways of planning the gathering of data to make its analysis easier, more precise or more accurate, and all the machinery and results of (mathematical) statistics which apply to analyzing data."