Berkson, Joseph. 1944. “Application of the Logistic Function to Bio-Assay.” Journal of the American Statistical Association 39 (227): 357–65.
Bliss, Chester I. 1934. “The Method of Probits.” Science 79 (2037): 38–39.
Bowley, A. L. 1906. “Address to the Economic Science and Statistics Section of the British Association for the Advancement of Sciences.” Journal of the Statistical Royal Society 69 (3): 540–58.
Bowley, AL. 1926. “Measurement of the Precision Attained in Sampling.(annex a to the Report by Jensen.) Bulletin of the International Statistical Institute, 22.” Supplement to 54 (1): 1–62.
Chollet, Francois, and JJ Allaire. 2018. Deep Learning with r. Manning.
Fisher, Ronald A. 1936. “The Use of Multiple Measurements in Taxonomic Problems.” Annals of Eugenics 7 (2): 179–88.
Fritsch, Stefan, and Frauke Guenther. 2016. Neuralnet: Training of Neural Networks.
Galindo, Edwin. 2015. Estadı́stica, métodos y Aplicaciones. Prociencia Editores, Quito. 3rd ed. Prociencia Editores.
Galton, Francis. 1889. “I. Co-Relations and Their Measurement, Chiefly from Anthropometric Data.” Proceedings of the Royal Society of London 45 (273-279): 135–45.
Gauss, Carl Friedrich. 1823. Theoria Combinationis Observationum Erroribus Minimis Obnoxiae. Vol. 2. H. Dieterich.
Godambe, V. P. 1955. “A Unified Theory of Sampling for the Finite Populations.” Journal of the Royal Statistical Society 17 (B17): 73–96.
Godambe, VP, and ME Thompson. 1977. “Robust Near Optimal Estimation in Survey Practice.” IS% Bulletin 47: 129–46.
Gorroochurn, Prakash. 2016. Classic Topics on the History of Modern Mathematical Statistics: From Laplace to More Recent Times. John Wiley & Sons.
Graunt, John. 1665. Natural and Political Observations Made Upon the Bills of Mortality. 3rd ed. The Royal Society.
Gregoire, Timothy G. 1998. “Design-Based and Model-Based Inference in Survey Sampling: Appreciating the Difference.” Canadian Journal of Forest Research 28 (10): 1429–47.
Gujarati, Damodar, and Dawn Porter. 2010. Econometrı́a. 5th ed. México: McGRAW-HILL/INTERAMERICANA EDITORES, SS DE CV.
Gutierrez-Rojas, Hugo Andres. 2015. TeachingSampling: Selection of Samples and Parameter Estimation in Finite Population.
Horvitz, D. & Thompson. 1952. “A Generalization of Sampling Without Replacement from a Finite Universe.” Journal of the American Statistical Association 47 (47): 663–85.
Izenman, Alan Julian. 2008. Modern Multivariate Statistical Techniques. NY: Springer.
Kassambara, Alboukadel. 2017. Practical Guide to Cluster Analysis in r: Unsupervised Machine Learning. Vol. 1. Sthda.
Kiaer, A. N. 1901. “Sur Les Methodes Representatives Ou Typologiques.” Bulletin of the International Statistical Institute.
Kwartler, Ted. 2017. Text Mining in Practice with r. John Wiley & Sons.
Legendre, Adrien Marie. 1806. Nouvelles méthodes Pour La détermination Des Orbites Des Comètes; Par AM Legendre... chez Firmin Didot, libraire pour lew mathematiques, la marine.
Matérn, Bertil. 1960. “Spatial Variation.” Medd. Statens Skogsforskingsintitu 49 (5): 100–135.
Mingers, John. 1989. “An Empirical Comparison of Selection Measures for Decision-Tree Induction.” Machine Learning 3 (4): 319–42.
Morgan, James N, and John A Sonquist. 1963. “Problems in the Analysis of Survey Data, and a Proposal.” Journal of the American Statistical Association 58 (302): 415–34.
Nelder, John Ashworth, and Robert WM Wedderburn. 1972. “Generalized Linear Models.” Journal of the Royal Statistical Society: Series A (General) 135 (3): 370–84.
Neyman, Jerzy. 1934. “On the Two Different Aspects of the Representative Method: The Method of Stratified Sampling and the Method of Purposive Selection.” Journal of the Royal Statistical Society 97 (4): 558–625.
Rosenblatt, Frank. 1961. “Principles of Neurodynamics. Perceptrons and the Theory of Brain Mechanisms.” Cornell Aeronautical Lab Inc Buffalo NY.
Sarndal, B. & Wretman J., C. Swensson. 1992. Model Assited Survey Sampling. Springer.
Schumacker, Randall E. 2015. Using r with Multivariate Statistics. Sage Publications.
Tippett, LHC. 1927. “Random Number Tables.” Tracts for Computers, no. 15.
Vapnik, V, and A Chervonenkis. 1964. “On a Class of Algorithms of Learning Pattern Recognition.” Automation and Remote Control 25: 937–45.