In the early years of Mendelism, 1900-1910, William Bateson established a productive research group consisting of women and men studying biology at Cambridge. The empirical evidence they provided through investigating the patterns of hereditary in many different species helped confirm the validity of the Mendelian laws of heredity. What has not previously been well recognized is that owing to the lack of sufficient institutional support, the group primarily relied on domestic resources to carry out their work. Members of the group (...) formed a kind of extended family unit, centered on the Batesons' home in Grantchester and the grounds of Newnham College. This case illustrates the continuing role that domestic environments played in supporting scientific research in the early 20th century. (shrink)

The requirement of randomization in experimental design was first stated by R. A. Fisher, statistician and geneticist, in 1925 in his book Statistical Methods for Research Workers. Earlier designs were systematic and involved the judgment of the experimenter; this led to possible bias and inaccurate interpretation of the data. Fisher's dictum was that randomization eliminates bias and permits a valid test of significance. Randomization in experimenting had been used by Charles Sanders Peirce in 1885 but the practice was not continued. (...) Fisher developed his concepts of randomizing as he considered the mathematics of small samples, in discussions with "Student," William Sealy Gosset. Fisher published extensively. His principles of experimental design were spread worldwide by the many "voluntary workers" who came from other institutions to Rothamsted Agricultural Station in England to learn Fisher's methods. (shrink)

In the early years of Mendelism, 1900-1910, William Bateson established a productive research group consisting of women and men studying biology at Cambridge. The empirical evidence they provided through investigating the patterns of hereditary in many different species helped confirm the validity of the Mendelian laws of heredity. What has not previously been well recognized is that owing to the lack of sufficient institutional support, the group primarily relied on domestic resources to carry out their work. Members of the group (...) formed a kind of extended family unit, centered on the Batesons' home in Grantchester and the grounds of Newnham College. This case illustrates the continuing role that domestic environments played in supporting scientific research in the early 20th century. (shrink)

The ArgumentMost lay users of statistics think in terms of means (averages), variances or the square of the standard deviation, and Gaussians or bell-shaped curves. Such conventions are entrenched by statistical practice, by deep mathematical theorems from probability, and by theorizing in the various natural and social sciences. I am not claiming that the particular conventions (here, the statistics) we adopt are arbitrary. Entrenchment can be rational without its being as well categorical (excluding all other alternatives), even if that entrenchment (...) claims also to provide for categoricity. 1 provide a detailed description of how a science is “normal” and conventionalized. A characteristic feature of this entrenchment of conventions by practice, theorems, and theorizing, is its highly technical form, the canonizing work enabled by apparently formal and esoteric mathematical means. (shrink)

Urbach (1985) has concluded that the use of randomization in the design of clinical and agricultural trials is both inappropriate and ineffective. It is argued here that it is appropriate, as it eliminates the dependence of inference on the unknown precise physical model that underlies a set of observations, and effective, in that it is relatively simple to apply in practice compared with any competing method. Furthermore, it has been proven in practice.

The most conspicuous form of agricultural experiment is the field trial, and within the history of such trials, the arrival of the randomised control trial is considered revolutionary. Originating with R.A. Fisher within British agricultural science in the 1920s and 30s, the RCT has since become one of the most prodigiously used experimental techniques throughout the natural and social sciences. Philosophers of science have already scrutinised the epistemological uniqueness of RCTs, undermining their status as the ‘gold standard’ in experimental design. (...) The present paper introduces a historical case study from the origins of the RCT, uncovering the initially cool reception given to this method by agricultural scientists at the University of Cambridge and the National Institute of Agricultural Botany. Rather than giving further attention to the RCT, the paper focuses instead on a competitor method – the half-drill strip – which both predated the RCT and remained in wide use for at least a decade beyond the latter’s arrival. In telling this history, John Pickstone’s Ways of Knowing is adopted, as the most flexible, and productive way to write the history of science, particularly when sciences and scientists have to work across a number of different kinds of place. It is shown that those who resisted the RCT did so in order to preserve epistemic and social goals that randomisation would have otherwise run a tractor through. (shrink)

This paper analyzes the interaction between science, philosophy and politics (including ideology) in the early work of J. B. S. Haldane (from 1922 to 1937). This period is particularly important, not only because it is the period of Haldane's most significant biological work (both in biochemistry and genetics), but also because it is during this period that his philosophical and political views underwent their most significant transformation. His philosophical stance first changed from a radical organicism to a position far more (...) compatible with mechanical materialism. The primary intellectual influence that was responsible for this shift was that of F. G. Hopkins. Later, Haldane came to accept Marxism and its official metaphysics, dialectical materialism, a move that let him accept the materialist conception of the world while still maintaining a resolute distance from mechanism. Throughout all these changes, what is most obvious is the influence of science on Haldane's philosophical views. An influence in the opposite direction is far less apparent. (shrink)

This essay examines the origin of genotype-environment interaction, or G×E. "Origin" and not "the origin" because the thesis is that there were actually two distinct concepts of G×E at this beginning: a biometric concept, or \[G \times E_B\], and a developmental concept, or \[G \times E_D \]. R. A. Fisher, one of the founders of population genetics and the creator of the statistical analysis of variance, introduced the biometric concept as he attempted to resolve one of the main problems in (...) the biometric tradition of biology - partitioning the relative contributions of nature and nurture responsible for variation in a population. Lancelot Hogben, an experimental embryologist and also a statistician, introduced the developmental concept as he attempted to resolve one of the main problems in the developmental tradition of biology - determining the role that developmental relationships between genotype and environment played in the generation of variation. To argue for this thesis, I outline Fisher and Hogben's separate routes to their respective concepts of G × E; then these separate interpretations of G × E are drawn on to explicate a debate between Fisher and Hogben over the importance of G × E, the first installment of a persistent controversy. Finally, Fisher's \[G \times E_B\] and Hogben's \[G \times E_D \] are traced beyond their own work into mid-2Oth century population and developmental genetics, and then into the infamous IQ Controversy of the 1970s. (shrink)

Subramanian has produced a new biography of Haldane taking into account archival material that has only become public during the last decade. He has been able to provide a more complete picture of Haldane’s personal life than earlier biographers, such as his difficult schooldays at Eton and the deterioration of his first marriage. He has also highlighted the extent to which Haldane was kept under constant secret surveillance by British intelligence services because of his politics. However, the book is less (...) successful in its account of Haldane’s scientific work including what he contributed to modern evolutionary theory, the Fisher–Haldane relationship, Haldane’s role in the Lysenko controversy, and what he achieved after emigration to India in 1957. (shrink)

The paper discusses the scope and influence of eugenics in defining the scientific programme of statistics and the impact of the evolution of biology on social scientists. It argues that eugenics was instrumental in providing a bridge between sciences, and therefore created both the impulse and the institutions necessary for the birth of modern statistics in its applications first to biology and then to the social sciences. Looking at the question from the point of view of the history of statistics (...) and the social sciences, and mostly concentrating on evidence from the British debates, the paper discusses how these disciplines became emancipated from eugenics precisely because of the inspiration of biology. It also relates how social scientists were fascinated and perplexed by the innovations taking place in statistical theory and practice. (shrink)

Why do classic biostatistical studies, alleged to provide causal explanations of effects, often fail? This article argues that in statistics-relevant areas of biology—such as epidemiology, population biology, toxicology, and vector ecology—scientists often misunderstand epistemic constraints on use of the statistical-significance rule (SSR). As a result, biologists often make faulty causal inferences. The paper (1) provides several examples of faulty causal inferences that rely on tests of statistical significance; (2) uncovers the flawed theoretical assumptions, especially those related to randomization, that likely (...) contribute to flawed biostatistics; (3) re-assesses the three classic (SSR-warrant, avoiding-selection-bias, and avoiding-confounders) arguments for using SSR only with randomization; and (4) offers five new reasons for biologists to use SSR only with randomized experiments. (shrink)

Since the beginning of the twentieth century statistics has reshaped the experimental cultures of agricultural research taking part in the subtle dialectic between the epistemic and the material that is proper to experimental systems. This transformation has become especially relevant in field trials and the paper will examine the British agricultural institution, Rothamsted Experimental Station, where statistical methods nowadays popular in the planning and analysis of field experiments were developed in the 1920s. At Rothamsted statistics promoted randomisation over systematic arrangements, (...) factorisation over one-question trials, and emphasised the importance of the experimental error in assessing field trials. These changes in methodology transformed also the material culture of agricultural science, and a new body, the Field Plots Committee, was created to manage the field research of the agricultural institution. Although successful, the vision of field experimentation proposed by the Rothamsted statisticians was not unproblematic. Experimental scientists closely linked to the farming community questioned it in favour of a field research that could be more easily understood by farmers. The clash between the two agendas reveals how the role attributed to statistics in field experimentation defined different pursuits of agricultural research, alternately conceived of as a scientists’ science or as a farmers’ science. (shrink)

Anyone reading the literature on the history of graphs will soon realize that the use of graphie displays of any type was really quite unusual until the mid-ninetenth century and that those scientists who did make use of them are often familiar to us as creative thinkers in their own fields of endeavour. Aternary diagram(also known as atriangular diagram) is a particular type of graph which consists of an equilateral triangle in which a given plotted point represents the relative proportions (...) (a, b, c) of three end-members (A, B and C), generally expressed as percentages and constrained bya + b + c= 100%. It has long been used to portray sample composition in terms of three constituents, or an observed colour in terms of three primary colours, because it is a convenient means of representing a three-component System in a planar projection, rather than as an isometric, or similar, view of a three-dimensional space. Recent papers suggest that its use is not as familiar to some statisticians as are other commonly used forms of graph. For example, although it was cited by Peddle in 1910 and more recently by Dickinson, it is not discussed in modern texts on statistical graphies nor in the key papers on the history of graphs. However, beginning with studies of colour-mixing in the eighteenth century, it has subsequently become widely used, particularly in geology, physical chemistry and metallurgy. In this paper, I attempt to document its gradual uptake as a standard method of data display and some of the scientific advances which its use has facilitated. (shrink)

The group theorist William Burnside devoted much of the last decade of his life to probability and statistics. The work led to contact with Ronald Fisher who was on his way to becoming the leading statistician of the age and with Karl Pearson, the man Fisher supplanted. Burnside corresponded with Fisher for nearly three years until their correspondence ended abruptly. This paper examines Burnside’s interactions with the statisticians and looks more generally at his work in probability and statistics.