R Programming- A new view of Biostatistics ....

R programming is a way of presenting any science, such as statistics or information related to any subject in biology, to your liking. By this, any mathematical reasoning can be structured in any new way according to the concept of mind. If you want to combine one type of graph with another kind of graph, new hybrid graphs can be created. Any changes to the graph can be made, a whole new graph that will be followed by researchers in the scientific community once they are in place .... All of which, for so long Microsoft Microsoft, SPSS, Past, Primer, MatLab or other statistically different ones. The software could do it differently with all of this R programming. Once learned, will stay forever ....

So first to get an idea about R in Bangla, the following two links will have to come back. Namely:

1.     R Programming - (Click Here)

2.     Some general signals of R programming - (click here)

To know more in depth please visit the link below:

1.     R Programming Bangla Tutorial - (Click Here)

2.     R Programming in Oceanography - (Click here)

3.     List of Video Tutorials in English - (Click here)

But for those who want to deepen their knowledge, start in English from the links below:

Start:

·       for R basics  - (Click here)

·       for data manipulation

o  - (Click here.)

o  - (Click here 2)

·       Interactive Introduction to R programming language  - (Click here)

·       Application focused R tutorial  - (Click here)

·       In-browser learning for R  - (Click here)

Economic data format:

·       lecture notes with R code  - (click here)

·       A brief guide to R and Economics  - (click here)

Plots, maps, graphs, etc.

·       tutorial with info on plots  - (click here)

·       A graph gallery of R plots and charts with supporting code  - (click here)

·       A tutorial for Lattice  - (Click here)

·       Ggplot R graphics  - (Click here)

·       Ggplot Vs Lattice  - (Click Here)

·       Multiple tutorials for using ggplot2 and Lattice  - (Click here)

·       Google Charts with R  - (Click here)

·       Introduction to using Google Maps  - (click here)

·       Thematic Maps with R  - (Click here)

·       geographic maps in R  - (Click here)

Some graphical user interfaces (GUIs):

·       Poor Man GUI for R  - (Click here)

·       R Commander is a robust GUI for R  - (Click here)

·       JGR is a Java-based GUI for R  - (click here)

Some R coding with time series or duration

·       a good beginner's tutorial for time series  - (click here)

·       Interesting time series packages in R  - (Click here)

·       Advanced time series in R  - (Click here)

·       Analysis and visualization framework for quantitative trading  - (click here)

·       Guide to Credit Scoring using R  - (Click here)

·       An Open Source Framework for Financial Analysis  - (Click Here)

Data / text mining:

·       A Data Mining Tool in R  - (Click here)

·       An online e-book for Data Mining with R  - (Click here)

·       Introduction to the Text Mining Package in R  - (Click here)

Other calculation formatting methods

·       Quick-R - (Click here)

·       annotated guides for a variety of models  - (click here)

·       Social Network Analysis  - (click here)

Some  R programming  editors:

·       Komodo Edit R editor  - (Click here)

·       Tinn-R makes for a good R editor  - (click here)

·       An Eclipse plugin for R   - (Click here)

·       Instructions to install StatET in Eclipse  - (Click here)

·       R Studio  - (click here)

·       Emacs Speaks Statistics, a statistical language package for Emacs  - (click here)

R's connectivity with other programming languages:

·       to embed R data frames in Excel via multiple approaches  - (click here)

·       provides a tool to make R usable from Excel  - (click here)

·       Connect to MySQL from R  - (Click here)

·       info about pulling data from SAS, STATA, SPSS, etc.  - (Click here)

·       Latex  - (Click here)

·       R2HTML  - (click here)

Some blogs and articles on R:

·       A very informative blog  - (click here)

·       A blog aggregator for posts about R  - (Click here)

·       R mailing lists  - (click here)

·       R newsletter (old)  - (Click here)

·       R journal (current)  - (Click here)

Additional R programming:

·       Web Scraping in R  - (Click here)

·       A very interesting list of packages that is seriously worth a look  - (click here)

·       Commercial versions of R  - (Click here)

·       Red R for R tasks  - (click here)

·       KNIME for R (worth a serious look)  - (Click here)

·       R Tutorial for Titanic  - (Click here)

There are also official links to this, which are as follows:

R Programming:

·       Introduction

·       Sample Session

·       Manage your workspace

·       Settings and Installation

·       Documentation

·       Control Structures

·       Working with functions

·       Debugging

·       Using C or Fortran

·       Utilities

·       Estimation utilities

·       Packages

Data Management:

·       Data types

·       Working with data frames

·       Importing and exporting data

·       Text Processing

·       Times and Dates

·       Graphics

·       Grammar of graphics

·       Publication quality output

·       Descriptive Statistics

·       Mathematics

·       Optimization

·       Probability Distributions

·       Random Number Generation

Theoretical main method of statistics:

·       Maximum Likelihood

·       Method of Moments

·       Bayesian Methods

·       Bootstrap

·       Multiple Imputation

·       Nonparametric Methods

Regression Model:

·       Linear Models

·       Quantile Regression

·       Binomial Models

·       Multinomial Models

·       Tobit And Selection Models

·       Count Data Models

·       Duration Analysis

·Time Series

·       Factor Analysis

Sort:

·       Ordination

·       Clustering

·       Network Analysis

Large calculation method:

·       Profiling R code

·       Parallel computing with R

Other:

·       Sources

·       Index