TheStatistical Research Group (SRG) was a research group at Columbia University focused on military problems during World War II. Abraham Wald, Allen Wallis, Herbert Solomon, [1] Frederick Mosteller, George Stigler, Leonard Jimmie Savage and Milton Friedman were all part of the group in which 18 researchers participated. [2]
Wallis, Stigler and Friedman met as graduate students at the University of Chicago. Despite their shared alma mater there is no evidence that Stigler and Friedman had grown close before serving on the SRG staff together in New York City. [3]
The SRG was disbanded at the end of World War II.
Statistical analysis was widely used by Federal agencies after the New Deal. The statistical publications of the United States became more sophisticated between 1930 and 1940. During the mobilization to war (1940-1941) and continuing on during the war, statistics continued to gain in importance with applications in operations research and management information systems (MIS). The Statistical Control System in the Air Force developed under Colonel C.B. Thornton, was an example of a wartime MIS. Its mission was to provide "a continuous flow of detailed information on the status of many parts of the Air Force, including personnel, supply, operations, and basic data upon which to base attrition rates, sortie rates, crew rotation rates, maintenance needs, supply rates, etc." [4]
The Statistical Research Group (SRG) at Columbia University was supported by the Applied Mathematics Panel (AMP) or the National Defense Research Committee (NDRC), part of the Office of Scientific Research and Development (OSRD). [5]
While teaching at Stanford during the war years, Allen Wallis wrote to a friend at the Census Bureau: [5]
Those of us teaching statistics in various departments here are trying to work out a curriculum adapted to the immediate statistical requirements of the war. It seems probably that a good many students with research training might by training in statistics become more useful for war than in their present work, or might increase their usefulness within their present fields."
Friedman wrote an appendix called "A Cautionary Tale about Multiple Regressions" that was published in Alternative Approaches to Analyzing Economic Data in which he says that, as a researcher at SRG, he constructed two new alloys to be used in aircraft engines. His work was based on a regression model that made use of data on existing alloys. Using this model he predicted that it would take several hundred hours for the new alloys to rupture at high temperatures. [6]
Analysis of variance (ANOVA) is a collection of statistical models and their associated estimation procedures used to analyze the differences among means. ANOVA was developed by the statistician Ronald Fisher. ANOVA is based on the law of total variance, where the observed variance in a particular variable is partitioned into components attributable to different sources of variation. In its simplest form, ANOVA provides a statistical test of whether two or more population means are equal, and therefore generalizes the t-test beyond two means. In other words, the ANOVA is used to test the difference between two or more means.
Milton Friedman was an American economist and statistician who received the 1976 Nobel Memorial Prize in Economic Sciences for his research on consumption analysis, monetary history and theory and the complexity of stabilization policy. With George Stigler, Friedman was among the intellectual leaders of the Chicago school of economics, a neoclassical school of economic thought associated with the work of the faculty at the University of Chicago that rejected Keynesianism in favor of monetarism until the mid-1970s, when it turned to new classical macroeconomics heavily based on the concept of rational expectations. Several students, young professors and academics who were recruited or mentored by Friedman at Chicago went on to become leading economists, including Gary Becker, Robert Fogel, and Robert Lucas Jr.
Statistics is the discipline that concerns the collection, organization, analysis, interpretation, and presentation of data. In applying statistics to a scientific, industrial, or social problem, it is conventional to begin with a statistical population or a statistical model to be studied. Populations can be diverse groups of people or objects such as "all people living in a country" or "every atom composing a crystal". Statistics deals with every aspect of data, including the planning of data collection in terms of the design of surveys and experiments.
In statistics, regression toward the mean is the phenomenon where if one sample of a random variable is extreme, the next sampling of the same random variable is likely to be closer to its mean. Furthermore, when many random variables are sampled and the most extreme results are intentionally picked out, it refers to the fact that a second sampling of these picked-out variables will result in "less extreme" results, closer to the initial mean of all of the variables.
Nonparametric statistics is a type of statistical analysis that makes minimal assumptions about the underlying distribution of the data being studied. Often these models are infinite-dimensional, rather than finite dimensional, as is parametric statistics. Nonparametric statistics can be used for descriptive statistics or statistical inference. Nonparametric tests are often used when the assumptions of parametric tests are evidently violated.
The Chicago school of economics is a neoclassical school of economic thought associated with the work of the faculty at the University of Chicago, some of whom have constructed and popularized its principles. Milton Friedman and George Stigler are considered the leading scholars of the Chicago school.
Wilhelm Lexis, full name Wilhelm Hector Richard Albrecht Lexis, was a German statistician, economist, and social scientist. The Oxford Dictionary of Statistics cites him as a "pioneer of the analysis of demographic time series". Lexis is largely remembered for two items that bear his name—the Lexis ratio and the Lexis diagram.
George Joseph Stigler was an American economist. He was the 1982 laureate in Nobel Memorial Prize in Economic Sciences and is considered a key leader of the Chicago school of economics.
Leonard Jimmie Savage was an American mathematician and statistician. Economist Milton Friedman said Savage was "one of the few people I have met whom I would unhesitatingly call a genius."
Abraham Wald was a Jewish Hungarian mathematician who contributed to decision theory, geometry and econometrics, and founded the field of sequential analysis. One of his well-known statistical works was written during World War II on how to minimize the damage to bomber aircraft and took into account the survivorship bias in his calculations. He spent his research career at Columbia University. He was the grandson of Rabbi Moshe Shmuel Glasner.
Stephen Mack Stigler is the Ernest DeWitt Burton Distinguished Service Professor at the Department of Statistics of the University of Chicago. He has authored several books on the history of statistics; he is the son of the economist George Stigler.
Survivorship bias or survival bias is the logical error of concentrating on entities that passed a selection process while overlooking those that did not. This can lead to incorrect conclusions because of incomplete data.
Anna Jacobson Schwartz was an American economist who worked at the National Bureau of Economic Research in New York City and a writer for The New York Times. Paul Krugman has said that Schwartz is "one of the world's greatest monetary scholars."
The Friedman test is a non-parametric statistical test developed by Milton Friedman. Similar to the parametric repeated measures ANOVA, it is used to detect differences in treatments across multiple test attempts. The procedure involves ranking each row together, then considering the values of ranks by columns. Applicable to complete block designs, it is thus a special case of the Durbin test.
In statistics, sequential analysis or sequential hypothesis testing is statistical analysis where the sample size is not fixed in advance. Instead data is evaluated as it is collected, and further sampling is stopped in accordance with a pre-defined stopping rule as soon as significant results are observed. Thus a conclusion may sometimes be reached at a much earlier stage than would be possible with more classical hypothesis testing or estimation, at consequently lower financial and/or human cost.
William Henry Kruskal was an American mathematician and statistician. He is best known for having formulated the Kruskal–Wallis one-way analysis of variance, a widely used nonparametric statistical method.
Wilson Allen Wallis was an American economist and statistician who served as president of the University of Rochester. He is best known for the Kruskal–Wallis one-way analysis of variance, which is named after him and William Kruskal.
The following is a list of works by the prominent American economist Milton Friedman.
Statistics, in the modern sense of the word, began evolving in the 18th century in response to the novel needs of industrializing sovereign states.