Interest in statistical computing began not with the invention of the personal
computer in the 1980s or even with the rise of the large mainframe computer during
the 1960s. Statistical computing became a popular field for study during the
1920s and 1930s, as universities and research labs began to acquire the early
IBM mechanical punched card tabulators. They used these machines not only for
tabulating and computing summary statistics but also for fitting more complicated
statistical models such as analyses of variance and linear regressions.
These labs proved to be important places for advancing statistical methodology.
They helped make Galton’s and Pearson’s ideas on correlation practical
tools that could be used for scientific research. They encouraged researchers
to think in terms of large problems with extensive datasets. Without them,
modern statistical methodology could easily have languished as an interesting
useful for small problems but otherwise impracticable.
In addition to advancing statistical methodologies, these labs helped to advance
scientific computing in general. Many of these labs offered their services
to physicists and astronomers as well as to biologists and social scientists.
created tables of higher mathematical functions. Others solved complicated
differential equations. A few of these labs, most notably those at Iowa State
Columbia University, became test beds for early computer scientists, who experimented
with new ideas for computing machines and for numerical algorithms.
Most of these labs were small ad hoc organizations. Many were nothing more
than a creative professor who had arranged to use the tabulating machines of
business office during a second or third shift. The largest of these labs were
substantial institutions funded by donations from private individuals or small
foundations. In the 1920s, such gifts were almost the only funds a researcher
could expect to find. There was no National Science Foundation, no National
Institutes of Health. There were no instrumentation grants for the mathematical
The scientific infrastructure developed by Vanevar Bush during and after World
War II simply did not exist. The only source of government money for scientific
research was the Department of Agriculture, an organization that proved to
be very supportive of empirical research and that helped to establish the largest
and most sophisticated of the statistical laboratories, the Statistics Lab
Iowa State University.
The names associated with these early labs are familiar to very few — James
Glover, H. T. Davis, A. E. Brandt, Howard Tolley. They published little and
made only marginal contributions to the theory of statistics or the development
computers. Yet these researchers held a deep faith that the combination of
computing technology and mathematical statistics would radically change science.
tools remain linked today, but during the 1920s and 1930s the combination not
only helped establish the field of statistics on the American continent, it
also promoted computing as an important tool for scientific research.
Statistical Labs: Before the Tabulator
Most of the earliest statistical laboratories were founded to study economic
phenomena, though they quickly began to apply their tools and techniques to
problems in the social, biological, and behavioral sciences. Economic applications
the bills, leased the equipment, and provided the salaries for laboratory workers.
One of the first of these laboratories was founded at the University of Michigan
by James Glover, a professor of mathematics. Glover was a pioneer actuary and
student of financial risk. He began teaching advanced statistics courses in
1904, though they included little of the mathematical statistics that was being
in England by Karl Pearson and R. A. Fisher. The University of Michigan was
one of the founts of -statistical knowledge in the United States. The University
trained many of the early pioneers of American statistics, including George
founder of the Iowa State University laboratory.
Glover had a small lab operating by about 1910. It was staffed by his students
and followed the model of the computing labs found in observatories and astronomy
departments. At these labs, junior personnel acted as computing assistants
to the astronomers. These computing assistants would transform observations
stellar coordinates and would use the least squares methods of Gauss and Laplace
to estimate the orbits of comets and planets. In Glover’s lab, they reduced
data to summary statistics, created actuarial tables, cross-tabulated data,
and made projections from simple statistical models.
Glover rarely had more than two computing assistants. Most were his students
and many were women. Even in the early 1900s, the University of Michigan was
a coeducational institution, and Glover felt that statistical study was especially
appropriate for young women. At times, nearly half of his students were women.
A few of these women had surprisingly long and prosperous careers in industry,
in the U.S. Census, or in actuarial firms. For the most part, the largest cohort
of these women became human computers, the clerical workers who did mathematical
calculations before the advent of electronic computers.
Though Glover ultimately
had a distinguished career as an actuary and as the head of Teachers Insurance
and Annuity Association, he is a marginal figure
in the history of statistics. Glover’s lab, however, seems to have inspired
one of the founders of the field, Henry Reitz, to organize a computing lab
at the University of Illinois, where he worked until 1918. Like Glover, Reitz
interested in actuarial work and did projects for insurance companies in Chicago
and Springfield. Glover also taught the statistical courses at the University
of Michigan when George Snedecor attended the university between 1910 and 1913.
The First Card Tabulators
The earliest statistical laboratories used mechanical adding machines
or calculators, such as those made by Monroe, Marchant, or Sunstrand.
They began using punched card tabulators in the early 1920s. These devices
had been invented by Herman Hollerith for the 1890 U.S. Census. Hollerith
formed the Hollerith Tabulating Machine Company to manufacture and market
these devices. This company was merged with two other firms in 1911 to
form the Computing Tabulating and Recording Company or C.T.R. In 1924,
C.T.R. was renamed International Business Machines.
Although least squares was an important application for the early statistical
labs, Tolley and the others at the Bureau of Agriculture were initially more
interested in the statistical methods of Frederick Winslow Taylor than they
were in the methods of Galton, Pearson, and Fisher. Taylor was an engineer
whose writings on scientific management were highly influential in the first
decades of this century. He proposed a means of studying the methods of workers
and developed some crude statistical techniques for gathering and analyzing
data. These techniques were filled with heuristic and ad hoc methods and were
criticized by Taylor’s detractors. They were relatively effective at
the time, however, and were studied by many managers who wished to improve
at their plant or in their office.
Tolley was interested in applying Taylor’s ideas to fruit markets in New
York and cold-storage warehouses along rail lines. Yet, he clearly understood
the limits of Taylor’s methods and knew that these statistical methods
were unable to help him in situations with large amounts of variability, such
as estimating crop production and weather damage. His training at the Coastal
Survey helped him to understand the relationship between correlation analysis
and least squares. During his early years in the Department of Agriculture,
he worked to promote least squares analysis. Although researchers were generally
interested in this method, they occasionally found it difficult to apply because
the punched card tabulators of the early 1920s were unable to multiply. Tolley
apparently found a practical method to compute correlations that required both
a punched-card tabulator and a desk-top calculator.
The lab in the Department of Agriculture inspired two Iowans, George Snedecor
and Henry A. Wallace, to experiment with punched-card statistical computations.
Henry Wallace eventually rose to prominence as the Vice President of the United
States, but during the 1920s, he was the publisher of his family’s farm
journal, Wallaces’ Practical Farmer. He was also a self-taught statistician
and was interested in the interplay of biology and economics in farm management.
During the 1910s, he learned the methods of correlation studies and least squares
regression by reading Yule’s book, An Introduction to the Theory of Statistics
(London: Griffin, 1911). Finding in that book no easy method for solving the
normal equations for regression, Wallace devised his own, using an idea that
Gauss had applied to an astronomical problem.
In 1923, Henry A. Wallace learned of the new statistics lab at the Department
of Agriculture while he was visiting his father, Harry Wallace, who was then
the Secretary of Agriculture. Intrigued with the machines, he borrowed a tabulator
at a Des Moines insurance firm and taught himself how to use the device to
calculate correlations.. He would punch data cards and would then take them
to the offices
of the insurance company for tabulating. During the first years of the 1920s,
he published ever more sophisticated statistical studies in the pages of Wallaces’ Farmer,
studies that must have baffled many of his loyal readers, who tended to be
modestly educated farmers. The last, published in January 1923, was a detailed
land values in the state.
The study of Iowa land values marked the maturity of Wallace’s statistical
ability. By the time he published it, Wallace had become a friend of George Snedecor,
who taught the statistics courses at Wallace’s alma mater, then named Iowa
State College. Impressed with Wallace’s knowledge of least squares, Snedecor
invited him to teach an advanced course on those methods to college faculty.
This class, which met for 10 consecutive Saturdays over the fall and winter
of 1924, ended with a demonstration of punched-card calculation. After the
Snedecor helped Wallace prepare a manuscript on his algorithm for solving normal
equations. They jointly published the manuscript in 1925 with the title Correlation
and Machine Calculation.
The title of Wallace’s and Snedecor’s pamphlet tends to mislead modern
readers. For the most part, the machines to which it refers are desk calculators,
not tabulating machinery. Part of Wallace’s methods were easily adapted
to tabulating machines. By computing sums of squares and sums of cross-products,
a mechanical tabulator could quickly produce a set of normal equations. The
same tabulator, however, could not be easily used to solve these equations.
extremely awkward, if not impossible, to use a 1920s vintage tabulator to solve
matrix arithmetic problems. Such problems were solved by human computers who
used desk calculators.
Inspired by Wallace, Snedecor devoted much effort to acquiring tabulating machines
for his university. He was able to secure them in the Fall of 1927 and established
a statistical computing lab within the Department of Mathematics. (See Fig.
2) This first lab seems to have been a cooperative effort by several college
and may have been partly supported by local IBM officials, who were interested
in placing their equipment at universities. IBM helped many schools establish
computing labs at that time. The first was at Cornell, which leased tabulating
machines to form a lab in 1926. Next came Iowa State College, Columbia University,
and the University of Michigan, who acquired these machines in 1927. Shortly
thereafter came the University of Texas, Harvard University, Stanford University,
and the University of Tennessee.
The Statistics Lab
At Iowa State College
During 1927, Snedecor exhibited the same kind of exuberance
that we now attribute to someone who has just acquired a fancy new personal
computer. He used the
tabulating equipment for every possible application that he could find and
a detailed report to his chair. He tabulated basic agricultural statistics,
tracked the results of agricultural county fairs, and started a punched-card
breed book. A colleague used the tabulator to evaluate higher mathematical
functions. Another interpolated a function with polynomials.
After a year of
operation, after his ardor cooled somewhat, Snedecor turned the lab equipment
over to the management of A. E. Brandt. Brandt was a student
Snedecor’s and had been a professor of farm mechanics at Oregon State
University. He enjoyed the subtleties of the tabulators and liked to find new
ways of doing
calculations. From the Economics Department, he recruited human computers to
help operate the machines and to solve normal equations for regression problems.
One of these clerks, Mary Clem, would remain with the Statistics Lab for the
next 50 years and would ultimately be identified as the lead human computer
of the group.
The computing facility was an important part of a lab that was
quickly building statistical expertise. Through the Department of Agriculture,
it acquired funds
to host summer institutes in statistical theory. The first of these was held
in 1927 with British statistician R. A. Fisher. Fisher met with about 50 researchers
who were eager to learn his methods. (See Fig. 3.) One of these researchers
was Henry A. Wallace, who would shortly thereafter leave Iowa and become Secretary
of Agriculture, following in his father’s footsteps. By then, Wallace
had become fascinated with the problems of weather prediction and had begun
large study in which he attempted correlating heat, humidity, and wind direction
with the position of the planets. He discussed the study at length with Fisher,
who was little interested in such poorly grounded research. The work eventually
became an embarrassment to Wallace when his political enemies branded it as “weather
Even though Wallace may not have made the best use of his
contact with Fisher, he did become a champion of statistical studies as means
of planning programs
to address social and economic ills. As Secretary of Agriculture, he devised
and prepared the Agricultural Adjustment Act, a radical proposal to support
farm prices and to alleviate the effect of the Great Depression on American
This program was the first major piece of legislation in Franklin Roosevelt’s
New Deal, written and implemented within his first 100 days in office, and
it became a model for subsequent programs. It required the Department of Agriculture
to undertake large statistical studies of major farm products, including cotton,
corn, tobacco, and pork.
The Agricultural Adjustment Act proved to be a boon
for land grant colleges and state experimental farms because they were asked
to do much of the local
work. It was especially helpful to the Iowa State College Statistical Laboratory.
The lab, now independent of the Mathematics Department, acquired several government
contracts in the early days of the New Deal. As the demand for statistical
work increased, the lab undertook increasingly larger and more important jobs.
1936, it was negotiating with the Department of Agriculture to undertake major
research projects, including a large master sample of the nation’s farms.
These projects increased the size of the lab. Over a short period of five years,
its budget grew by a factor of 16.
John Atanasoff and
an Early Electronic Computer
The rapid expansion of the lab allowed one Iowa State College faculty member
to undertake some experiments in computation, experiments that would provide
the basis for the modern electronic computer. That professor, John Atanasoff,
held appointments in both the mathematics and physics departments. During the
early 1930s, Atanasoff had been studying approximate solutions to differential
equations. The last step of his approach required him to solve a large system
of linear equations. Knowing that the Statistics Lab routinely solved such
problems when it computed regression models, Atanasoff began to consider how
might be solved by using the lab’s punched-card equipment.
and 1937, he and A.E. Brandt experimented with lab equipment. In the first
experiment, Brandt and Atanasoff modified an IBM tabulator to
an atomic spectrum. To do this, they constructed a special circuit that allowed
a tabulator to compute all possible differences from a list of numbers. Once
they had completed this experiment, they began to work directly on the problem
of solving linear systems. Atanasoff sketched a design for the necessary
circuits but never completed the task. Before they made much progress on the
Brandt left the lab to join the Bureau of Soil Conservation. With Brandt
gone, Atanasoff probably lost his access to the punched card machines, for
no further experiments. He ultimately decided that his design was too difficult
to complete and abandoned it.
Even though Atanasoff lost interest in the punched-card machines, he did not
forget about the problem of solving systems of linear equations. In what is
a well-known story among computer historians, Atanasoff set off on a long drive
across Iowa to think about this problem sometime during the winter of 1937–1938.
Several hundred miles later, at a roadside bar in Illinois, he conceived the
basic elements for a machine to solve systems of linear equations. The proposed
machine had a lot of similarities with modern computers. It was electronic
and had a memory unit, a central processor, and binary arithmetic. He built
prototype of this machine in 1939 and prepared a proposal in 1940 for a full
working model, a proposal he used to solicit funds for the machine.
The Iowa State Statistical Lab clearly influenced Atanasoff as he wrote
this proposal. Atanasoff saw his machine within the context of a computing
much like the Statistics Lab, and that it would solve linear systems “at
low cost and for technical and research purposes.” Atanasoff then listed
nine possible applications for his machine. Of these nine, the first three
Atanasoff built his machine between 1940 and 1942. (See Fig.
4.) With the start of World War II, he abandoned his creation when he left
the college to join
the Naval Ordnance Laboratory in Washington, D.C. Atanasoff’s machine
would have remained in obscurity were it not for John Mauchly, one of the inventors
of the ENIAC computer. Mauchly met Atanasoff at a conference in May 1941 and
visited Atanasoff’s lab in Ames, where he studied Atanasoff’s machine.
During this visit, Mauchly learned a great deal about electronics and about
computing machines. Some of these ideas found their way into the ENIAC design
a point of contention between the two computer pioneers for the rest of their
The Statistics Lab of the Cowles Commission
Although the statistical lab at Iowa State University became one of the major
centers of statistical research, a similar lab at Indiana University grew
to be a center of econometric research. This lab was founded by H. T. Davis
was championed by Colorado financier Alfred Cowles. Davis was a new member
of the mathematics faculty when the dean asked him to form a statistical
1927. A small local foundation had agreed to finance such a group so that
they might better understand the fluctuations in the economy.
Like Snedecor, Davis was quick to use the lab to explore a diverse range
of computational problems, most of which had little to do with the statistical
study of the economy.
One of the first was an optical interference computation for a physicist
When he realized that his computers had used the wrong values in making the
computation, Davis convinced his colleague to perform the experiment a second
the values that his computers had mistakenly employed. Although he did statistical
calculations for business and economics professors, Davis took little interest
in statistical research. Instead, he studied numerical analysis and used
the lab to create tables of higher mathematical functions.
Alfred Cowles helped
revive Davis’s interest in statistics. Cowles, an
amateur statistician much like Wallace, was interested in large regression
studies of the economy. He envisioned studies that would collect thousands
and would fit regression models to 20 or 30 independent variables. In 1931,
he approached Davis and asked him for help in undertaking such computations.
immediately realized that his small computing lab, staffed by human computers,
would be unable to do the necessary computing. He urged Cowles to lease punched
-card equipment and helped him to establish a statistical lab near Cowles’s
offices in Boulder, Colorado. Davis spent the next several summers with Cowles,
helping him develop the necessary mathematical techniques. It seems likely
that Davis used the methods of Snedecor and Wallace because their pamphlet
of the few works on the computations needed for regression models.
this organization, which was then known as the Cowles Commission for Economic
Research, moved to the University of Chicago. It reestablished its
computing lab at the university even though the University of Chicago supported
the oldest organized computing groups in the nation. This group did calculations
for the Physics and Astronomy Departments. It was run by Ardis Monk, the
wife of a physics professor. She oversaw a dozen or so graduate students. These
human computers worked with the traditional tools of the day, slide rules
tables. Their computations were analogue approximations, not the digital
calculations of the Cowles Commission Laboratory. Over the next 14 years, during
the Cowles Commission moved to Yale University, the lab did an increasingly
important series of econometric computations, which supported the work of
people like Kenneth
Arrow and T. J. Koopmans.
The Last Days
World War II marked the glory days of the statistical lab and the start of
its slow decline. The Office of Scientific Research and Development financed
of statistical projects and organized computing labs to find concrete numerical
answers. At Columbia University, Abraham Wald operated a lab of 20 human
computers to develop a theory of sequential testing. University of California
Jerzy Neyman worked with a New York computing group to help the Air Corps
clear the Normandy beaches of mines in preparation for the D-Day landings.
used a geometric model to estimate the number of mines that would survive
by the Air Corps. The New York group, which had began operation as a W.P.A.
project, calculated the actual estimates.
At the war’s end, the statistical labs were deeply interested in the
new electronic computers. At an International Statistical Institute Conference
in the early summer of 1946, the Cowles Commission sponsored a session on electronic
computers. At the session were representatives of many of the statistical labs,
as well as some senior statisticians like Harold Hotelling. The featured speaker
was John Mauchly, who had unveiled the ENIAC computer only a few months prior.
Mauchly told the attentive group how the ENIAC could summarize data, compute
correlations, and solve linear regressions.
Yet, in some ways, the I.S.I. Conference in 1946 marked the start of the decline
of the old statistical labs. As universities and corporations built centralized
computing services, the statistical labs faded away. Their old calculators
were shelved, and the punched-card equipment returned to IBM as statisticians
computer time from a computing center. This trend was reversed in the early
1970s, when inexpensive minicomputers first appeared on the market. The popularity
the personal computer and the widespread availability of statistical software
ensured that not only every department would have a computing facility but
that every statistician could do more computing in an hour than the old Department
of Agriculture statistical lab could have done during the entire year of 1924.
Though modern computers are more powerful than the antiquated technology
of punch-card tabulators, the old statistical labs were probably more important
and technology. In the 1920s, the computing labs helped establish statistics
on the American continent. Without them, even a modest study was beyond the
ability of an individual statistician. At the same time, statistics labs
often had the
most powerful computing machines within their larger institution. They showed
how organized computing could benefit science and provided a place for the
earliest of computer scientists to test their ideas.