(Photograph by Denise Till)

The Fisher Memorial Trust was set up to promote interest in the life and work of the great statistician, evolutionary biologist and geneticist, Sir Ronald Aylmer Fisher (1890-1962) and to maintain his scientific legacy by encouraging discussion of the scientific fields in which he was active.

Charity Commission charity number 313536

Society | Representative | Position |

Biometric Society | Prof Rosemary Bailey | |

Biometric Society | Prof Vern Farewell** | |

Biometric Society | Mr Andrew Mead * | |

Genetics Society | Prof Brian Charlesworth, FRS | |

Genetics Society | Prof Adam Eyre-Walker | Treasurer |

Royal Society | Sir Walter Bodmer, FRS | Chairman |

Royal Statistical Society | Dr Andrew Sutherland *** | |

Royal Statistical Society | Prof Stephen Senn | Secretary |

* Replaced Prof John Gower 1 February 2015

** Replaced Prof Mike Kenward 1 February 2016

*** Replaced Prof Peter Diggle 15 February 2019

Report for 2016

Report for 2017

I | Dr. F. Yates | 23.3.66 | Computers, the second revolution in statistics. |

II | Dr. R. R. Race | 6.3.68 | Blood groups in human genetics |

III | Prof. E. A. Cornish | 3.9.69 | Developments from the Fisher-Cornish expansions. |

IV | Prof. K. Mather | 18.12.70 | Biometrical genetics. |

V | Prof. G. A. Barnard | 19.9.72 | Statistical inference and its historical development |

VI | Prof. L. L. Cavalli-Sforza | 24.6.74 | Cultural versus biological evolution |

VII | Prof. R. Hide | 17.11.77 | Motions in planetry fluids |

VIII | Prof. D. J. Finney | 20.9.78 | Bioassay and the practice of statistical inference |

IX | Prof. J. Maynard Smith | 19.3.81 | The evolution of the sex ratio |

X | Prof. J. H. Bennett | 3.6.81 | R. A. Fisher and The Genetical Theory of Natural Selection |

XI | Prof. S. Karlin | 20.4.83 | Kin selection and altruism |

XII | Prof. D. R. Cox | 5.4.84 | Regression and the design of experiments |

XIII | Prof. S. M. Stigler | 22.9.86 | Francis Galton and the unravelling of the normal world |

XIV | Prof. G. E. Box | 23.3.88 | Quality improvement, an expanding domain for the application of scientific method |

XV | Sir Walter Bodmer | 23.3.90 | Genetic sequences |

XVI | Prof. D. Lindley | 17.9.92 | Statistics of the market place |

XVII | Prof. A. J. Jeffereys | 16.8.93 | Molecular sleuthing: the story of genetic fingerprinting |

XVIII | Dr. A. W. F. Edwards | 20.10.94 | Fiducial inference and the fundamental theorem of natural selection |

XIX | Prof. M. J. R. Healy | 3.4.95 | The life and work of Frank Yates |

XX | Prof. J. A. Nelder | 5.9.96 | Computers and statistics: the continuing revolution. |

XXI | Sir John Kingman | 16.11.98 | Mathematics of genetic diversity: before and after DNA. |

XXII | Prof. B Efron | 12.9.00 | The essential Fisher |

XXIII | Sir Richard Doll | 29.10.01 | Proof of causality: Deductions from epidemiological evidence |

XXIV | Dr. Oliver Mayo | 26.06.02 | The realisation of Fisher's research programme |

XXV | Prof. Warren Ewens | 7.04.03 | Statistics and the transformation from genetics to genomics |

XXVI | Prof. Adrian Smith | 8.09.04 | Towards an Evidence-Based Society: the Role of Statistical Thinking |

XXVII | Prof. E.A.Thompson | 4.12.06 | 1953: an unrecognized summit in Human Genetic Linkage Analysis |

XXVIII | Prof. R.A. Bailey | 15.07.08 | Design of dose-escalation trials |

XXIX | Prof B Charlesworth and Prof D Charlesworth | 6.01.10 | Fisher and Modern Evolutionary Genetics |

XXX | Prof Philip Dawid | 10.11.11 | Causal inference from experimental data |

XXXI | Prof Peter Donnelly | 14.11.12 | Genetic Variation in Human Health and Disease |

XXXII | Prof David Spiegelhalter | 3.07.13 | Putting life into numbers: the highs and lows of communicating statistics to the public |

XXXIII | Prof Bill Hill | 8.01.14 | Applying quantitative genetic and genomic information to animal improvement |

XXXIV | Prof Peter McCullagh | 27.10.15 | Empirical phenomena and universal laws |

XXXV | Prof Nancy Reid | 27.10.16 | Statistical science and data science: where do we go from here? |

XXXVI | Prof Stephen Senn | 04.09.17 | And thereby hangs a tail: the strange history of P-values |

XXXVII | Prof Joe Felsenstein | 04.01.2018 | Is there a more fundamental theorem of natural selection? |

XXXVIII | Prof Michael Goddard | 9.10.2018 | The Genetic Architecture of Complex Traits |

Mike Goddard receiving the Fisher Memorial Lecture Award

from Walter Bodmer

Fisher grandson Richard Newsom with Walter Bodmer

Mike delivered a fine lecture as a fitting end to an excellent day in which Fisher's legacy and more modern developments were presented by a number of research veterans and some early career researchers. This was followed by a reception open to all attendees at which the Fisher Memorial Trust were delighted to have the presence of Fisher's grandson Richard Newsom. This was in turn followed by the usual Fisher Memorial Dinner for the lecturer and guests.

A simple but surprising result is that most quantitative genetic variation is due to very many polymorphisms, each with a tiny effect on the trait, and segregating in the population at moderate allele frequencies. For instance, there are approximately 10,000,000 sites in the genome where a mutation can affect a typical quantitative trait. Each generation, mutation generates new variation; some of the new mutant alleles have a large effect, but selection keeps them very rare. Most of the variation is caused by mutations of small effect that are almost neutral, and hence segregate at moderate allele frequencies. However, occasionally a mutation is favoured by selection and while it segregates generates a large variance. This is most common when the environment changes greatly so that the direction of selection on some mutations reverses. This new understanding explains many previously puzzling results, such as the linear response to artificial selection and the failure to find the genes causing variation in complex traits.

The ability to genotype thousands of SNPs at moderate cost has been utilised in methods of genomic selection or genomic prediction, which predict the genetic value of individuals for a trait based on SNP genotypes. This method is revolutionising animal and plant breeding and will be important in human medicine, for instance in personalised medicine.

We were fortunate enough to have trained and worked as young biometricians when analysis of variance (ANOVA) techniques were the primary method of analysis for comparative experiments.

Our tool of trade was the GENSTAT package, so that the elegant notation of Wilkinson and Rogers and the framework of Block and Treatment structures became ingrained in our statistical thinking. So, despite the complexity of the LMM we now use, we appreciate the importance of maintaining these fundamental concepts, in particular the link between the analysis and the experimental design. We are concerned that this view is shared by only a few, as is evidenced by what we regard as a widespread mis-use of LMM for comparative experiments. This may either be due to an unintentional lapse in transitioning from ANOVA to LMM or a complete lack of exposure to traditional methods of analysis for comparative experiments.

Over recent years, we have made it a priority to fill in this gap for our young statistical colleagues at the University of Wollongong.
In particular we have attempted to provide a link between ANOVA and LMM and to explain how to derive LMM that reflect the randomisation
employed in the design of the experiment, no matter how complex. We found this to be a non-trivial task and tried numerous educational
tools but without great success. A turning point was Brian's introduction of an Honours Statistics course on experimental design at the
University of Wollongong. He based this course on Rosemary Bailey's book and found words of wisdom that have inspired us to develop an
approach that we have termed *Design Tableau* (DT). The main aim of DT is to provide a simple, but general series of steps for specifying
the LMM for a comparative experiment. It is founded on the seminal work of Sir Ronald Fisher, John Nelder, Rosemary Bailey and Robin Thompson.
The motivation and concepts underlying Design Tableau will form the basis of our presentation. We will discuss the formal link between ANOVA
and LMM, describe the steps that constitute DT, illustrate DT for simple cases in which the LMM may be used to re-produce an ANOVA and finally
demonstrate how DT can be applied in a wide range of complex comparative experiments.

The RA Fisher Digital Archive University of Adelaide

Figures from the history of statistics Site maintained by John Aldrich

A Guide to R.A. Fisher Specific Fisher guide maintained by John Aldrich

Sir Ronald Aylmer Fisher MacTutor History of Mathematics Biography

Ronald Aylmer Fisher Monash University Fisher pages

COPSS Awards Fisher Lecture of the Committee of Presidents of Statistical Societies (Wikipedia page)

Chance, risk and healthOpen University series of 4 podcasts on RA Fisher and his legacy

Page of quotations from the works of Fisher collected by Anthony Edwards

This page last updated 27 February 2019

Page maintained by Stephen Senn stephen@senns.demon.co.uk