Studies in the history of probability and statistics. XV. The historical velopment of the Gauss linear model.

SUMMARY The linear regression model owes so much to Gauss that we believe it should bear his name. Other authors who made substantial contributions are: Cauchy who introduced the idea of orthogonality; Chebyshev who applied it to polynomial models; Pizzetti who found the distribution of the sum of squares of the residuals on the Normal assumption; Karl Pearson who linked the model with the multivariate Normal thereby broadening the field of applications; and R. A. Fisher whose extension of orthogonality to qualitative comparisons laid the foundations of the modern theory of experimental design.

[1]  Eugène Catalan,et al.  Sur les fractions continues , 1845 .

[2]  J. Gram Ueber die Entwickelung reeller Functionen in Reihen mittelst der Methode der kleinsten Quadrate. , 1883 .

[3]  E. Czuber,et al.  Theorie der Beobachtungsfehler , 1891 .

[4]  F. Y. Edgeworth XXII. Correlated averages , 1892 .

[5]  K. Pearson Mathematical Contributions to the Theory of Evolution. III. Regression, Heredity, and Panmixia , 1896 .

[6]  G. Yule On the Theory of Correlation , 1897 .

[7]  Karl Pearson,et al.  Mathematical Contributions to the Theory of Evolution. V. On the Reconstruction of the Stature of Prehistoric Races , 1899 .

[8]  Karl Pearson F.R.S. LIII. On lines and planes of closest fit to systems of points in space , 1901 .

[9]  W. R. Macdonell ON CRIMINAL ANTHROPOMETRY AND THE IDENTIFICATION OF CRIMINALS , 1902 .

[10]  T. N. Thiele,et al.  Theory Of Observations , 1903 .

[11]  George H. Ling,et al.  Die Ausgleichungsrechnung nach der Methode der Kleinsten Quadrate , 1907 .

[12]  G. Yule On the Theory of Correlation for any Number of Variables, Treated by a New System of Notation , 1907 .

[13]  E. Schmidt Über die Auflösung linearer Gleichungen mit Unendlich vielen unbekannten , 1908 .

[14]  E. Slutsky,et al.  On the Criterion of Goodness of Fit of the Regression Lines and on the Best Method of Fitting them to the Data , 1913 .

[15]  K. Pearson ON THE APPLICATION OF “GOODNESS OF FIT” TABLES TO TEST REGRESSION CURVES AND THEORETICAL CURVES USED TO DESCRIBE OBSERVATIONAL OR EXPERIMENTAL DATA , 1916 .

[16]  K. Pearson NOTES ON THE HISTORY OF CORRELATION , 1920 .

[17]  I. On a General Method of determining the successive terms in a Skew Regreuion Line , 1921 .

[18]  R. Fisher 014: On the "Probable Error" of a Coefficient of Correlation Deduced from a Small Sample. , 1921 .

[19]  Ronald Aylmer Sir Fisher,et al.  020: The Goodness of Fit of Regression Formulae and the Distribution of Regression Coefficients. , 1922 .

[20]  M. Young,et al.  The Interrelationships of the Physical Measurements and the Vital Capacity , 1923 .

[21]  HYPERSPHERICAL GONIOMETRY; AND ITS APPLICATION TO CORRELATION THEORY FOR N VARIABLES , 1923 .

[22]  R. Fisher,et al.  STUDIES IN CROP VARIATION , 2009 .

[23]  Student,et al.  On Testing Varieties of Cereals , 1923 .

[24]  R. Fisher 036: On a Distribution Yielding the Error Functions of Several Well Known Statistics. , 1924 .

[25]  Edmund Taylor Whittaker,et al.  The Calculus of Observations. , 1924 .

[26]  K. Pearson Researches on the Mode of Distribution of the Constants of Samples Taken at Random from a Bivariate Normal Population , 1926 .

[27]  V. Romanovsky NOTES ON CERTAIN EXPANSIONS IN ORTHOGONAL AND SEMI-ORTHOGONAL FUNCTIONS: II Note on Orthogonalising Series of Functions and Interpolation , 1927 .

[28]  R. A. Fisher,et al.  Studies in crop variation: IV. The experimental determination of the value of top dressings with cereals , 1927, The Journal of Agricultural Science.

[29]  L. Isserlis NOTES ON CERTAIN EXPANSIONS IN ORTHOGONAL AND SEMI-ORTHOGONAL FUNCTIONS: I. Note on Chebysheff's Interpolation Formula , 1927 .

[30]  P. H. Stevenson ON RACIAL DIFFERENCES IN STATURE LONG BONE REGRESSION FORMULAE, WITH SPECIAL REFERENCE TO STATURE RECONSTRUCTION FORMULAE FOR THE CHINESE , 1929 .

[31]  A study in sampling technique: the effect of artificial fortilisers on the yield of potatoes , 1929, The Journal of Agricultural Science.

[32]  R. Fisher,et al.  Studies in crop variation: VI. Experiments on the response of the potato to potash and nitrogen , 1929, Journal of Agricultural Sciences.

[33]  J. Wishart,et al.  085: The Arrangement of Field Experiments and the Statistical Reduction of the Results. , 1930 .

[34]  H. G. Sanders A note on the value of uniformity trials for subsequent experiments , 1930, Journal of Agricultural Sciences.

[35]  H. M. Walker,et al.  Studies in the history of statistical method , 1930 .

[36]  Frank Yates,et al.  The principles of orthogonality and confounding in replicated experiments. (With Seven Text-figures.) , 1933, The Journal of Agricultural Science.

[37]  J. Irwin On the Independence of the Constituent Items in the Analysis of Variance , 1934 .

[38]  J. Wishart Statistics in Agricultural Research , 1934 .

[39]  J. Neyman On the Two Different Aspects of the Representative Method: the Method of Stratified Sampling and the Method of Purposive Selection , 1934 .

[40]  M. S. Bartlett,et al.  The vector representation of a sample , 1934, Mathematical Proceedings of the Cambridge Philosophical Society.

[41]  Stanisław Kołodziejczyk,et al.  ON AN IMPORTANT CLASS OF STATISTICAL HYPOTHESES , 1935 .

[42]  A. C. Aitken IV.—On Least Squares and Linear Combination of Observations , 1936 .

[43]  W. G. Cochran The Omission or Addition of an Independent Variate in Multiple Linear Regression , 1938 .

[44]  Karl Pearson,et al.  Karl Pearson : an appreciation of some aspects of his life and work , 1939 .

[45]  D. Van der Reyden,et al.  Curve fitting by the orthogonal polynomials of least squares , 1943 .

[46]  Karl Pearson,et al.  Karl Pearson's early statistical papers , 1948 .

[47]  H. Seal Mortality data and the binomial probability law , 1949 .

[48]  R. Plackett A historical note on the method of least squares. , 1949, Biometrika.

[49]  J. Wishart,et al.  ORTHOGONAL POLYNOMIAL FITTING , 1953 .

[50]  J. M. Tienstra Theory of the Adjustment of Normally Distributed Observations. , 1956 .

[51]  H. Scheffé Alternative Models for the Analysis of Variance , 1956 .

[52]  Survey Adjustments and Least Squares , 1958 .

[53]  W. M. Smart,et al.  Combination of Observations , 1958 .

[54]  H. Scheffé The Analysis of Variance , 1960 .

[55]  R. Plackett,et al.  Principles of regression analysis , 1961 .

[56]  F. Graybill An introduction to linear statistical models , 1961 .

[57]  William Kruskal,et al.  The Coordinate-free Approach to Gauss-Markov Estimation, and Its Application to Missing and Extra Observations , 1961 .

[58]  R. Savage Probability inequalities of the Tchebycheff type , 1961 .

[59]  M. Fisz Wahrscheinlichkeitsrechnung und mathematische Statistik , 1962 .

[60]  L. Fox An introduction to numerical linear algebra , 1964 .

[61]  David Lindley,et al.  Introduction to Probability and Statistics from a Bayesian Viewpoint , 1966 .

[62]  J. Ortega,et al.  An introduction to numerical linear algebra , 1965 .

[63]  David Lindley,et al.  Introduction to Probability and Statistics from a Bayesian Viewpoint , 1966 .

[64]  N. Draper,et al.  Applied Regression Analysis , 1966 .

[65]  C. R. Rao,et al.  Linear Statistical Inference and its Applications , 1968 .