Azad Rasul
SmartRS

SmartRS

Series

R Programming for Researchers

This series includes types, manipulation, import, and export of data. In addition to secretive statistics, relationship, multi correlation, ANOVA, and t-test. It also familiarizes you with graphs.

Articles in this series

1- Data types in R

Jul 15, 20212 min read 283 views

We recommend to you install and use the latest version of R and RStudio IDE. The common R data types for research are numeric, factor, and...

2- Functions in R Programming

Jul 15, 20212 min read 117 views

A function is a collection of statements combined to do a specific task. Basic syntax of an R function: function_name <- function(arg_1, arg_2, ...)...

3- Packages in R Programming

Jul 16, 20211 min read 78 views

R packages are combinations of functions and data sets created as extensions to R. While, library in R indicates the place where the package is...

4- Importing data to R Programming

Jul 16, 20211 min read 130 views

Mainly researchers use .csv, .txt, .sav, and .xlxs format files. R base functions for importing data: read.table(), read.delim(), read.csv(),...

5- Exporting data from R programming

Jul 16, 20211 min read 66 views

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

6- Working directories and paths in R programming

Jul 17, 20212 min read 70 views

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