Outline and History

Good statistical understanding can be easy to learn and should be accessible to everyone. It is invaluable for informed decision making across disciplines and education levels. The software development has been led by Africa talent and is intended for a broad-multilingual audience.

R-Instat provides a front-end to R, designed to broaden the users of the software, particularly in Africa. "R is an open-source programming language and software environment for statistical computing and graphics that is supported by the R Foundation for Statistical Computing. The R language is widely used among statisticians and data miners for developing statistical software and data analysis."

R’s reputation has grown incredibly in recent years. General information about R is here and it’s early history is given here. The original Instat was an easy-to-use statistics package, produced at the University of Reading, UK. It was designed to support good statistical practice and included a special menu for the analysis of historical climatic data. The ideas behind Instat have motivated the structure of the R-Instat menus and dialogues, though no line of the original code remains.

R-Instat got its start thanks to a crowd-sourcing campaign in 2015. This 3 minute video from the original campaign outlines the need for this software.

Download R-Instat

In response to the recent review of R-Instat by Bob Muenchen we continue to develop new versions of R-Instat. Many thanks to Bob for reviewing R-Instat.

Latest stable release 0.7.6

Release version Release date Click to download Click for more
R-Instat 0.7.6 (64-bit) July 6, 2022 Download Release Notes
R-Instat 0.7.6 (32-bit) July 6, 2022 Download Release Notes

Looking for a specific release?

R-Instat releases by version number for 64-bit: +
Release version Release date Click to download Click for more
R-Instat 0.7.16 July 16, 2023 Download Release Notes
R-Instat 0.7.15 July 16, 2023 Download Release Notes
R-Instat 0.7.12 May 25, 2023 Download Release Notes
R-Instat 0.7.10 March 3, 2023 Download Release Notes
R-Instat 0.7.9 March 3, 2023 Download Release Notes
R-Instat 0.7.8 Jan. 31, 2023 Download Release Notes
R-Instat releases by version number for 32-bit: +
Release version Release date Click to download Click for more
R-Instat 0.7.16 July 16, 2023 Download Release Notes
R-Instat 0.7.15 July 16, 2023 Download Release Notes
R-Instat 0.7.12 May 25, 2023 Download Release Notes
R-Instat 0.7.10 March 3, 2023 Download Release Notes
R-Instat 0.7.9 March 3, 2023 Download Release Notes
R-Instat 0.7.8 Jan. 31, 2023 Download Release Notes

R-Instat is currently a Windows only application. However, it can be accessed on Mac or Linux through use of a Virtual Windows Machine.

Prerequisite Software

.NET Framework : R-Instat is a .NET software and requires an up to date version of the .NET (at least 4.6.1) to be installed before it can run. Most new Windows version already have this. The installation process will tell you if your .NET needs to be updated. If you need to download it, you can download .NET Framework here.

Rtools: R-Instat requires Rtools to export data to Excel files. If you do not intend to use this feature, you do not need to download Rtools. If you would like to you can download Rtools here.

R

R: R-Instat includes a built in copy of R, which performs all data processing in R-Instat. You do not need to download R separately to use R-Instat. If you would like to know more about R click here.

Documentation

R-Instat's documentation, tutorials, and guides are constantly evolving.

Installation Guide

We strongly recommend following the installation guide the first time you install R-Instat.

Installation guide: PDF version or Online version.

Introductory Tutorials

If you are new to R-Instat, these tutorials are a good way to begin to familiarise yourself with how it works using real and interesting data sets.

Part 1: Describing Data PDF version

Part 2: A Second Data Set PDF version

Part 3: Working with Labelled Data PDF version

Climatic Guide

R-Instat includes a special climatic menu for the analysis for historical climatic data. The Climatic Guide is a comprehensive guide to R-Instat's climatic functionalities.

R-Instat Climatic Guide PDF version (48MB)

Tutorial Videos

We have a growing collection of tutorial videos for R-Instat. Go to our YouTube Channel to see the current collection.

Built in Help

Comprehensive help for each R-Instat dialog will be implemented soon. This will be accessible through the Help button on each dialog, or the Help menu. As well as help on using the dialog, there will also be information about the R code and packages behind them, including direct links to R's documentation where appropriate.

Our Team

We have a team of experienced statisticians and software developers dedicated to providing high-quality statistical software.

Antoine Ntalumeso

Antoine Ntalumeso

Software Developer

Antoine has a passion for both logic and creativity, bringing a unique blend of computer science to the team.

Patrick Munyoki

Patrick Munyoki

Software Developer

Patrick has broad experience in software development, gained over several years working as a consultant for small and medium-sized companies.

Lily Clements

Lily Clements

Data Scientist

Lily is a statistician who has recently completed her PhD. She is involved in a number of exciting projects across IDEMS, with work concentrated mainly in using the statistical software, R.

Vitalis Kwambai

Vitalis Kwambai

Software Developer

Vitalis Kwambai is a degree holder in B.Sc. Applied Statistics from Maseno University. Vitalis is doing master degree in Applied Statistics from the same University and currently he is doing research work in climatology.

Beryl Waswa

Beryl Waswa

Documentation Specialist

Beryl Waswa has a background in Actuarial Science and is currently working as a Documentation Specialist and Office Manager at INNODEMS. Beryl documents how to use R-Instat for end users.

Sophie Malla

Sophie Malla

Software Developer

Sophie is passionate about applied science. She is always enthusiastic about learning new things and sharing her knowledge. She has a master's degree in applied physics and mathematics applied to climate modelling.

Derrick Agorhom

Derrick Agorhom

Software Developer

Derrick is passionate about software development. He has a background in Computer Science and Mathematics. His primary focus revolves around crafting innovative systems and applications that tackle real-world challenges through technology.

Fidel Lumbasi

Fidel Lumbasi

Software Developer

Fidel's expertise lies in computer science, and he currently serves as a software developer at INNODEMS, contributing to the testing and development of various projects.

Roger Stern

Roger Stern

SENIOR STATISTICIAN

Roger’s main interests include improving the teaching of statistics at all levels. He also works closely with Meteorological Services in many countries to support more use of their historical climatic data.

David Stern

David Stern

SENIOR STATISTICIAN

David's interests in mathematics are very broad, including statistics and computing. He previously worked as a computer programmer in the UK, in software development.

Danny Parsons

Danny Parsons

SENIOR STATISTICIAN

Danny completed his Masters in Mathematics at the University of Warwick, UK. During his undergraduate degree, Danny also had a keen interest in Mathematics education and spent two summers teaching in Primary and High Schools in the Kibera slums of Nairobi, Kenya.

Chris Marsh

Chris Marsh

Software Developer

Chris is an experienced software developer who has worked in a variety of sectors over his 20 year career. He has managed teams of software developers and coordinated large development projects.

Stephen Lloyd

Stephen Lloyd

SENIOR SOFTWARE ENGINEER

Stephen has worked on many international software projects. He is especially interested in software development using distributed teams. He is providing analysis, implementation, coordination and mentoring support to IDEMS’ software projects.

Contact

To report issues or bugs with the software, please post an issue on our Github Issues page.

We are more than happy to welcome any developer to take on the task of making R-Instat better.

We welcome you to get a copy of source code in our Github page.