1. Introductory Tutorials
The tutorials are a gentle introduction to R-Instat and get you working with example data right away. The example data is included in R-Instat, so you don't need to download anything else to get started.
The tutorials are available in both document and video format and are designed to be easy to follow for a beginner. Whatever format you choose, you will only learn by doing, so make sure you practice what you watch/read!
The videos are in two parts. Part 1 is the "How" showing you how to use the software, and Part 2 is the "why" discussing why we did these steps and how we interpret the results.
Tutorial 1 - Describing Data
Tutorial 1 does not use climatic data, but an example dataset called diamonds. If you want to get straight into climatic data, go to Tutorial 2, but we think there are useful things to learn here, even if your interest is climatic data.
| Tutorial 1 Video Part 2
Tutorial 1 Document
Tutorial 2 - A Climatic Dataset
Tutorial 2 uses a climatic data set of daily data from a station in Dodoma, Tanzania. We appreciate Tanzania Meteorological Agency for kindly providing this data freely for use in R-Instat.
Tutorial 2 Video Part 1 | Tutorial 2 Video Part 2
Tutorial 2 Document
2. Climatic Guide
The R-Instat Climatic Guide is a comprehensive guide to R-Instat's climatic functionalities. We do not suggest reading the whole guide in one go, but reading the relevant sections as you need them.
For this course, we suggest looking particularly at Chapter 2.4 and parts of Chapter 9 on gridded data.
R-Instat Climatic Guide
3. Example data & exercises
The link below is a guide to the demonstration done in the live session with further details and steps.
Comparing satellite and station data in R-Instat tutorial
The folder below contains the data used in the presentation. In the link above to Dropbox, click Download in the top right corner to download all the files to a zip folder, or click on a file and then the ↓ arrow to download individually. The data are provided in various formats which enable you to practice different elements of the analysis.
Download example Data
There are three types of exercises you may want to carry out:
1. Prepare and analyse the example data from Germany
Use the original data files as shown in the presentation to get practice in both data preparation and analyses. This simulates a process of working with real data where time is often needed for organising the preparing the data before
it can be analysed, as you saw in the presentation.
2. Analyse the pre-prepared example data from Germany
If you prefer to focus on the statistical analyses and comparisons in more detail, we have provided the pre-prepared data in the file sunh_merged.RData in the example data folder, ready to begin analyses straight away. This is less realistic than the normal situation when working with data,
but has the advantage of allowing you to focus on doing more analysis and comparisons.
3. Prepare and Analyse your own data
Some of you may have access to your own station data and we hope you may be adventurous and want to try out what you've learned for your own analysis. If you do, you will also need to download the corresponding satellite data for comparison, which you can get from CM SAF. You will likely need to do some preparing and formatting of your data to get it into shape for analysis, which may be slightly different to what you saw in the presentation. Use the climatic guide above, and ask questions on Slido if
you need help with this.
How to download data from CM SAF
4. More on R-Instat
We have a growing set of tutorial videos on various aspects of R-Instat's climatic features. View the playlist on YouTube to see the full set.
We love to hear from our users. If you would like to report a bug or request a new feature, post a message on our GitHub site. If you have a general query or feedback write to use at: r-instat (at) africanmathsinitiative.net