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R Programming for Researchers

The series covers various topics such as data types, data manipulation, data import, and export. It also includes descriptive statistics, correlation analysis, MLR, and data visualization.

Articles in this series

1- Data types in R

Jul 15, 2021 2 min read 475 views

We recommend installing and using the latest versions of R and RStudio IDE. The common R data types for research are numeric, factor, and...

1- Data types in R

2- Functions in R Programming

Jul 15, 2021 2 min read 192 views

A function is a collection of statements combined to perform a specific task. The basic syntax of an R function is: function_name <- function(arg_1,...

2- Functions in R Programming

3- Packages in R Programming

Jul 16, 2021 2 min read 140 views

R packages are combinations of functions and datasets created as extensions to R. The library function in R is used to indicate the location where the...

3- Packages in R Programming

4- Importing data to R Programming

Jul 16, 2021 2 min read 251 views

Mainly, researchers use .csv, .txt, .sav, and .xlsx format files. R has several base functions for importing data, including read.table(),...

4- Importing data to R Programming

5- Exporting data from R programming

Jul 16, 2021 1 min read 119 views

Create data: data <- c(1977, 1979, 2013, 2014,'', 2015) Save data as comma-separated CSV format: write.csv(data, 'created_data.csv') Save as...

5- Exporting data from R programming

6- Working directories and paths in R programming

Jul 17, 2021 2 min read 132 views

Set a default working directory in RStudio Go to Tools > Global Options > General > Default working directory (when not in a project) > Browse >...

6- Working directories and paths in R programming