Topic outline

  • Welcome to R-Instat's Learning Resources

    Most of the materials on this site include videos to watch and practice documents to follow along the activities. We suggest you do both. 

    Start by choosing which of the following categories is closest to your situation. 


    Once you have started, use the links below or scroll through the topics on the left to choose resources that are useful to you. 

    We are always adding to our resources, next up we will be adding more learning materials about descriptive statistics in R-Instat. Including tables and more on graphs. 

  • Getting Started

    In this section you will find exercises which introduce how to use R-Instat, alongside statistical ideas using real data. There are 4 ways to start depending on your computing experience and goals.


  • Starting with Data Entry

  • Easy Access to Amazing Data

  • Lists and Numbers

    • Explore lists of information on a wide range of topics and learn how to manipulate them to extract information. 
    • With a column calculator it becomes easy to play with numbers. Let R-Instat's Calculator dialog do the work so that you are free to become a data  detective and search out interesting patterns. 

    • Generate and explore sequences like abundant and super abundant numbers. 

    • Explore the real meaning of large numbers like a googol. 
  • Getting Data Tidy

  • Describing Data Well

    • In this exercise we will mostly produce the graphs from ggplot2’s Connect Observations script in tidyverse.


  • Use Scripts

    Adding this scripting capabilities to R-Instat was important. It bridges the gap between GUIs and R. With this scripting feature users can:

      • easily apply pre-written scripts and then continue to explore and work on their data using GUI front end.  
    AND 

      • take on repetitive tasks without the risks inherent with manual repetition.

    Those who are critical of GUIs argue that they are pitiful compared to the flexibility of R. This feature makes room for this flexibility within the easy to use frontend, which often contains all that is needed; thus bridging the gap. 

    The following presentations, you gain exposure to and familiarity with using R scripts without needing to learn the R language first. But only if, and when you are ready and interested; the point and click system is sufficient for many people and projects.


    • We are excited to introduce the new (as from 2024) scripting facilities in R-Instat. This is special for a point and click system and it reflects our goal of supporting users working efficiently in statistics and data science. Whether in R-Instat, in R, or both! 

    • R-Instat has a script window so users can run R scripts easily. Here we show how simple it is to run a script from an R package, or one that has been written for you.

    • This presentation illustrates how to produce line plots in R and R-Instat following the R script in R-Instat?

    • Explore the Calculator's Summary Keyboard within the narrative of how a script writer or a software developer would produce items. 

  • Climatic Data

  • General Information

    This site houses R-Instat's learning materials. 

    These videos and written exercises blend learning R-Instat with learning statistics through the continual use of data. 

    R-Instat is a free, open source statistical software that is easy to use. 

    It encourages good statistical practices and learning, by making it easy to emphasise concepts rather than theory. This software is designed to support improved statistical and data science literacy everywhere, through work undertaken primarily within Africa.

    R-Instat provides a front-end to R.

    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 very widely used.

    R, and so also R-Instat, provides a wide range of data sets.

    This enables users to practice using interesting, large, and varied data, which is instrumental to learning good statistics practices.


    • Though out our years of teaching statistics courses and service course, government, for profit, non-profit and academic organizations we have come across a wide array to people; with a range of relationships with data and statistics.


    • To follow along with the exercises on this website you need to have R-Instat installed on your computer. This page provides links and instructions for downloading and installing  R-Instat. 

      Joining Moodle will allow you to track your progress through these materials.

    • Questions about R-Instat? Find your answer here. Includes sections: 
      • General
      • Is R-Instat for me
      • Data Science
      • Climatic
      • Satellite and reanalysis data (NetCDF files)
    • The background to R-Instat.  How did it start and grow, and how was it transformed from Instat into R-Instat.  We also try to answer some questions you may have on R-Instat