Agresti, A. (1984), Analysis of Ordinal Categorical Data, New York: John Wiley and Sons, Inc.

Agresti, A. (1990), Categorical Data Analysis, New York: John Wiley and Sons, Inc.

Agresti, A., and Coull, B. (1998), “Approximate is Better Than ‘Exact’ for Interval Estimation of Binomial Proportions,” The American Statistician, 52, 119–126

Akaike, H. (1974), “Factor Analysis and AIC,” Pschychometrika, 52, 317–332.

Akaike, H. (1987), “A new Look at the Statistical Identification Model,” IEEE Transactions on Automatic Control, 19, 716–723.

American Society for Quality Statistics Division (2004), Glossary and Tables for Statistical Quality Control, Fourth Edition, Milwaukee: Quality Press. “The Statistical Analysis of Variance-Heterogeneity and the Logarithmic Transformation,” JRSS Suppl 8, 128–138.

Baglama, J. and Reichel, L. (2005), “Augmented Implicitly Restarted Lanczos Bidiagonalization Methods,” SIAM Journal on Scientific Computing 27, 19-42.

Bartlett, M.S. (1966), An Introduction to Stochastic Processes, Second Edition, Cambridge: Cambridge University Press.

Bissell, A. F. (1990), “How Reliable is Your Capability Index?”, Applied Statistics, 30, 331–340.

Brown, M.B. and Benedetti, J.K. (1977), “Sampling Behavior of Tests for Correlation in Two-Way Contingency Tables,” Journal of the American Statistical Association 72, 305–315.

Brown, M.B. and Forsythe, A.B. (1974), “The Small Sample Behavior of Some Statistics Which Test the Equality of Several Means,” Technometrics 16:1, 129–132.

Brown, M.B. and Forsythe, A.B. (1974), “Robust tests for the equality of variances,” Journal of the American Statistical Association, 69, 364–367.

Chen, Song Xi and Hall, Peter. (1993), “Empirical Likelihood Confidence Intervals for Quantiles,” The Annals of Statistics 21(3): 1166–1181.

Chou, Y.M., Owen, D.B., and Borrego, S.A. (1990), “Lower confidence limits on process capability indices,” Journal of Quality Technology, 22(3): 223–229.

Cleveland, W.S. (1979). “Robust Locally Weighted Regression and Smoothing Scatterplots.” Journal of the American Statistical Association 74 (368): 829–836.

Cleveland, W.S. (1994). Visualizing Data, Summit, N.J: Hobart Press.

Cohen, J. (1960), “A coefficient of agreement for nominal scales,” Education Psychological Measurement, 20: 37–46.

Cochran, W.G. and Cox, G.M. (1957). Experimental Designs, Second Edition, New York: John Wiley and Sons.

Conover, W. J. (1972). “A Kolmogorov Goodness-of-fit Test for Discontinuous Distributions”. Journal of the American Statistical Association 67: 591–596.

Conover, W.J. (1980), Practical Nonparametric Statistics, New York: John Wiley and Sons, Inc.

Conover, W.J. (1999), Practical Nonparametric Statistics, 3rd Edition, New York: John Wiley and Sons, Inc.

Cureton, E.E. (1967), “The Normal Approximation to the Signed-Rank Sampling Distribution when Zero Differences are Present,” Journal of the American Statistical Association, 62:319, 1068–1069.

DeLong, E., Delong, D, and Clarke-Pearson, D.L. (1988), “Comparing the Areas Under Two or more Correlated Receiver Operating Characteristic Curves: A Nonparametric Approach,” Biometrics 44, 837–845.

Devore, J. L. (1995), Probability and Statistics for Engineering and the Sciences, Duxbury Press, CA.

Dunn, O.J. (1964), “Multiple Comparisons Using Rank Sums,” Technometrics 6, 241–252.

Dunnett, C.W. (1955), “A multiple comparison procedure for comparing several treatments with a control” Journal of the American Statistical Association, 50, 1096–1121.

Dwass, M. (1955), “A Note on Simultaneous Confidence Intervals,” Annals of Mathematical Statistics 26: 146–147.

Efron, B. (1981), “Nonparametric Standard Errors and Confidence Intervals,” The Canadian Journal of Statistics 9:2, 139–158.

Eubank, R.L. (1999), Nonparametric Regression and Spline Smoothing, Second Edition, Boca Raton, Florida: CRC.

Fisher, L. and Van Ness, J.W. (1971), “Admissible Clustering Procedures,” Biometrika, 58, 91–104.

Fleiss, J.L., Cohen J., and Everitt, B.S. (1969), “Large-Sample Standard Errors of Kappa and Weighted Kappa,” Psychological Bulletin, 72: 323–327.

Friendly, M. (1991), “Mosaic Displays for Multiway Contingency Tables,” New York University Department of Psychology Reports: 195.

Golub, G.H. and van der Vorst, H.A., (2000), “Eigenvalue Computation in the 20th Century,” Journal of Computational and Applied Mathematics 123, 35-65.

Goodman, L.A. and Kruskal, W.H. (1979), Measures of Association for Cross Classification, New York: Springer-Verlag (reprint of JASA articles).

Gupta, S.S. (1965), On Some Multiple Decision (selection and ranking), Rules., Technometrics 7, 225–245.

Hahn, G. J. and Meeker, W. Q. (1991) Statistical Intervals: A Guide for Practitioners. New York: Wiley.

Hajek, J. (1969), A Course in Nonparametric Statistics, San Francisco: Holden–Day.

Hartigan, J.A. and Kleiner, B. (1981), “Mosaics for Contingency Tables,” Proceedings of the 13th Symposium on the Interface between Computer Science and Statistics, Ed. Eddy, W. F., New York: Springer–Verlag, 268–273.

Hayter, A.J. (1984), “A proof of the conjecture that the Tukey–Kramer multiple comparisons procedure is conservative,” Annals of Mathematical Statistics, 12 61–75.

Hosmer, D.W. and Lemeshow, S. (1989), Applied Logistic Regression, New York: John Wiley and Sons.

“Hot Dogs,” (1986), Consumer Reports (June), 364–367.

Hsu, J. (1981), “Simultaneous confidence intervals for all distances from the ‘best’,” Annals of Statistics, 9, 1026–1034.

Hsu, J. (1989), Tutorial Notes on Multiple Comparisons, American Statistical Association, Washington, DC.

Hsu, J.C. (1996), Multiple Comparisons: Theory and Methods, Chapman and Hall.

Huber, Peter J. (1973), “Robust Regression: Asymptotics, Conjecture, and Monte Carlo,” Annals of Statistics, Volume 1, Number 5, 799–821.

Huber, P.J. and Ronchetti, E.M. (2009), Robust Statistics, Second Edition, Wiley.

Iman, R.L. (1974), “Use of a t-statistic as an Approximation to the Exact Distribution of Wilcoxon Signed Ranks Test Statistic,” Communications in Statistics—Simulation and Computation, 795–806.

Kendall, M. and Stuart, A. (1979), The Advanced Theory of Statistics, Volume 2, New York: Macmillan Publishing Company, Inc.

Kramer, C.Y. (1956), “Extension of multiple range tests to group means with unequal numbers of replications,” Biometrics, 12, 309–310.

Levene, H. (1960), “Robust tests for the equality of variances” In I. Olkin (ed), Contributions to probability and statistics, Stanford Univ. Press.

Mason, R.L. and Young, J.C. (2002), Multivariate Statistical Process Control with Industrial Applications, Philadelphia: ASA-SIAM.

McCullagh, P. and Nelder, J.A. (1983), Generalized Linear Models, London: Chapman and Hall Ltd.

Meeker, W.Q. and Escobar, L.A. (1998), Statistical Methods for Reliability Data, pp. 60–62, New York: John Wiley and Sons.

Nagelkerke, N.J.D. (1991), “A Note on a General Definition of the Coefficient of Determination,” Biometrika, 78:3 691–692.

Nelson, P.R., Wludyka, P.S., and Copeland, K.A.F. (2005), The Analysis of Means: A Graphical Method for Comparing Means, Rates, and Proportions, Philadelphia: Society for Industrial and Applied Mathematics.

Neter, J., Wasserman, W. and Kutner, M.H. (1990), Applied Linear Statistical Models, Third Edition, Boston: Irwin, Inc.

O’Brien, R.G. (1979), “A general ANOVA method for robust tests of additive models for variances,” Journal of the American Statistical Association, 74, 877–880.

O'Brien, R., and Lohr, V. (1984), “Power Analysis For Linear Models: The Time Has Come,” Proceedings of the Ninth Annual SAS User's Group International Conference, 840–846.

Olejnik, S.F. and Algina, J. (1987), “Type I Error Rates and Power Estimates of Selected Parametric and Nonparametric Tests of Scale,” Journal of Educational Statistics 12, 45–61.

Reinsch, C.H. (1967), Smoothing by Spline Functions, Numerische Mathematik, 10, 177–183.

Rousseuw, P.J. and Leroy, A.M. (1987), Robust Regression and Outlier Detection, New York: John Wiley and Sons.

Rubin, D. (1981), “The Bayesian Bootstrap”, The Annals of Statistics, 9:1, 130–134.

SAS Institute (2008), SAS/STAT 9.2 User’s Guide Introduction to Nonparametric Analysis, Chapter 16, SAS Institute Inc., Cary NC. Retrieved May 27, 2016 from https://support.sas.com/documentation/cdl/en/statugnonparam/61764/PDF/default/statugnonparam.pdf.

Schafer, J. and Strimmer, K. (2005), “A Shrinkage Approach to Large-Scale Covariance Matrix Estimation and Implications for Functional Genomics,” Statistical Applications in Genetics and Molecular Biology, 4:1, 1–30.

Slifker, J. F. and Shapiro, S. S. (1980). Technometrics, 22, 239–246.

Snedecor, G.W. and Cochran, W.G. (1980), Statistical Methods, 7th edition, Ames, Iowa: Iowa State University Press.

Somers, R.H. (1962), “A New Asymmetric Measure of Association for Ordinal Variables,” American Sociological Review, 27, 799–811.

Tan, Charles Y., and Iglewicz, Boris (1999), “Measurement-methods Comparisons and Linear Statistical Relationship,” Technometrics, 41:3, 192–201.

Tamhane, A. C. and Dunlop, D. D. (2000) Statistics and Data Analysis, Prentice Hall.

Welch, B.L. (1951), “On the comparison of several mean values: an alternative approach,” Biometrika 38, 330–336.

Wheeler, D.J. (2003), Range Based Analysis of Means, SPC Press, Knoxville, TN.

Wilson, E. B. (1927), “Probable Inference, the Law of Succession, and Statistical Inference,” Journal of the American Statistical Association, 22, 209-212.

Wludyka, P.S. and Nelson, P.R. (1997), “An Analysis-of-Means-Type Test for Variances From Normal Populations”, Technometrics, 39:3, 274–285.

Wludyka, P.S. and Nelson, P.R. (1999), “Two Non-Parametric, Analysis-of-Means-Type Tests for Homogeneity of Variances,” Journal of Applied Statistics, 26:2, 243–256.