Statistical Guides: Moving on from MSTAT
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Dated: March 2000
Author: Statistical Services Centre
From the introduction:"This guide has been written as part of our work for DFID to encourage good statistical practice. It is to assist research teams in planning their computing strategy. MSTAT has been effective in many developing countries, in introducing statistical computing to staff who have had no previous experience. It remains a useful package for the design of trials and for some of its specialist facilities, in particular for breeding programs. However, MSTAT is limited in its facilities for the analysis of experimental data and relatively cumbersome to use for the Analysis of Variance, compared to the ease of use of modern statistical software under Windows. A recent development is that at least one modern statistics package can read MSTAT files directly. This increases the flexibility of analyses both for staff who have historical data in MSTAT files and for those who would like to combine their use of MSTAT with the transfer to more powerful software when the need arises. This guide illustrates some advantages in using a more powerful package than MSTAT for the design and analysis of experimental data. We use Genstat for this purpose for two reasons. Firstly, Genstat is an excellent package for the analysis of data from agricultural experiments and secondly Genstat has provided the facility for the transfer of MSTAT files. We believe that it is now much easier to learn a new Windows package, compared to a few years ago and that full exploitation of experimental data needs access to a modern statistical package, such as Genstat" Part of a series of statistical guides by The University of Reading Statistical Services Centre, which were originally written as part of a contract with DFID to give guidance to research and support staff working on DFID Natural Resources projects. They provide guidelines for staff involved in the development and presentation of research projects. The guidelines are intended to help researchers to identify their biometric or statistical needs.
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Moving_On_From_MSTAT.pdf
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