Modern agricultural research began at Rothamsted in 1843, when Sir John Bennet Lawes started the Broadbalk wheat experiment which is now the world’s longest-running field experiment. Rothamsted also pioneered the application of statistics in biological research when Sir Ronald Fisher was appointed in 1919 to study the accumulated results of Broadbalk and its many subsequent experiments. Fisher soon realised the need for improved statistical techniques over the whole range of agricultural and biological research, and the groundwork for modern applied statistics was laid by him and his colleagues during the 1920s and 1930s.
Statistical computing began at Rothamsted when Fisher’s successor Frank Yates obtained an Elliot 401 computer – one of the first computers to be used away from its manufacturing base, and one of the first to be used for statistical work. This extended the tradition, started by Fisher, of conducting statistical research to solve real problems arising from biological research. The resulting new methods could now be implemented in the Rothamsted statistical programs to enable them to be used more effectively in practice. The development of GenStat at Rothamsted began in 1968, when John Nelder took over from Yates as Head of Statistics. Roger Payne took over leadership of the GenStat activity when Nelder retired in 1985.
GenStat began to be distributed outside Rothamsted during the 1970’s and, in 1979, its distribution was taken over by the Numerical Algorithms Group (NAG), one of the world’s oldest technical computing companies. More recently GenStat has been developed and marketed by VSN International (VSNi). VSNi was formed in 2000 as a spin-off company from Rothamsted and NAG. This brought together the GenStat development group from Rothamsted with the statistical commercialization group from NAG to provide a stronger collaboration of research and development with sales and marketing. However, the development group retain their close links with the research community through the continuing links between VSNi and Rothamsted. So users benefit from the rigorous quality control required in a commercial setting, while still retaining the underlying excitement from the research environment.
An important feature of GenStat is that it has been developed in (and now in collaboration with) a Statistics Department whose members have been responsible for many of the most widely-used methods in applied statistics. Examples include analysis of variance, design of experiments, maximum likelihood, generalized linear models, canonical variates analysis and recent developments in the analysis of mixed models by REML. GenStat has thus been designed not only to be a system to provide easy access to existing methods, but also one in which new methods can conveniently be implemented and studied. Another important characteristic is that our GenStat developers are themselves involved in statistical consulting and research. So we believe that this gives us a unique insight into the statistical requirements of biologists, and makes GenStat the ideal system for your statistical work.