General Statistics Applied to Pharmaceutical Data:

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1. Bolton, S., Pharmaceutical Statistics: Practical and Clinical Applications, 3 ed., Marcel Dekker, New York, 1997.

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2. Bolton, S., ―Statistics,‖ Remington: The Science and Practice of Pharmacy, 20 ed., Gennaro, A.R., ed., Lippincott Williams and Wilkins, Baltimore, 2000, pp. 124–158.

3. Buncher, C.R., Tsay, J., Statistics in the Pharmaceutical Industry, Marcel Dekker, New York, 1981.

4. Natrella, M.G., Experimental Statistics Handbook 91, National Institute of Standards and Technology (NIST), Gaithersburg, MD, 1991 (reprinting of original August 1963 text).

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5. Zar, J., Biostatistical Analysis, 2 ed., Prentice Hall, Englewood Cliffs, NJ, 1984.

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6. De Muth, J.E., Basic Statistics and Pharmaceutical Statistical Applications, 3 ed., CRC Press, Boca Raton, FL, 2014.

General Statistics Applied to Analytical Laboratory Data:

1. Gardiner, W.P., Statistical Analysis Methods for Chemists, The Royal Society of Chemistry, London, England, 1997.

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2. Kateman, G., Buydens, L., Quality Control in Analytical Chemistry, 2 ed., John Wiley and Sons, New York, 1993.

3. Kenkel, J., A Primer on Quality in the Analytical Laboratory, Lewis Publishers, Boca Raton, FL, 2000. 4. Mandel, J., Evaluation and Control of Measurements, Marcell Dekker, New York, 1991.

5. Melveger, A.J., ―Statististics in the pharmaceutical analysis laboratory,‖ Analytical Chemistry in a GMP Environment, Miller J.M., Crowther J.B., eds., John Wiley and Sons, New York, 2000.

6. Taylor, J.K., Statistical Techniques for Data Analysis, Lewis Publishers, Boca Raton, FL, 1990. 7. Thode, H.C., Jr., Testing for Normality, Marcel Dekker, New York, NY, 2002.

8. Taylor, J.K., Quality Assurance of Chemical Measurements, Lewis Publishers, Boca Raton, FL, 1987.

9. Wernimont, G.T., Use of Statistics to Develop and Evaluate Analytical Methods, Association of Official Analytical Chemists (AOAC), Arlington, VA, 1985.

10. Youden, W.J., Steiner, E.H., Statistical Manual of the AOAC, AOAC, Arlington, VA, 1975.

Nonparametric Statistics:

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1. Conover, W.J., Practical Nonparametric Statistics, 3 ed., John Wiley and Sons, New York, 1999.

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2. Gibbons, J.D., Chakraborti, S., Nonparametric Statistical Inference, 3 ed., Marcel Dekker, New York, 1992.

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3. Hollander, M., Wolfe, D., Nonparametric Statistical Methods, 2 ed., John Wiley and Sons, NY, 1999.

Outlier Tests:

1. Barnett, V., Lewis, T., Outliers in Statistical Data, 3rd ed., John Wiley and Sons, New York, 1994. 2. B?hrer, A., ―One-sided and two-sided critical values for Dixon's Outlier Test for sample sizes up to n = 30,‖ Economic Quality Control, Vol. 23 (2008), No. 1, pp. 5–13.

3. Davies, L., Gather, U., ―The identification of multiple outliers,‖ Journal of the American Statistical Association (with comments), 1993; 88:782–801.

4. Dixon, W.J., ―Processing data for outliers,‖ Biometrics, 1953; 9(1):74–89.

5. Grubbs, F.E., ―Procedures for detecting outlying observations in samples,‖ Technometrics, 1969; 11:1–21. 6. Hampel, F.R., ―The breakdown points of the mean combined with some rejection rules,‖ Technometrics, 1985; 27:95–107.

7. Hoaglin, D.C., Mosteller, F., Tukey, J., eds., Understanding Robust and Exploratory Data Analysis, John Wiley and Sons, New York, 1983.

8. Iglewicz B., Hoaglin, D.C., How to Detect and Handle Outliers, American Society for Quality Control Quality Press, Milwaukee, WI, 1993.

9. Rosner, B., ―Percentage points for a generalized ESD many-outlier procedure,‖ Technometrics, 1983; 25:165–172. 10. Standard E-178-94: Standard Practice for Dealing with Outlying Observations, American Society for Testing and Materials (ASTM), West Conshohoken, PA, September 1994.

11. Rorabacher, D.B., ―Statistical treatment for rejections of deviant values: critical values of Dixon's ―Q‖ parameter and related subrange ratios at the 95% confidence level,‖ Analytical Chemistry, 1991; 63(2):139–146.

Precision and Components of Variability:

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1. Hicks, C.R., Turner, K.V., Fundamental Concepts in the Design of Experiments, 5 ed., Oxford University Press, 1999 (section on Repeatability and Reproducibility of a Measurement System).

2. Kirk, R.E., Experimental Design: Procedures for the Behavioral Sciences, Brooks/Cole, Belmont, CA, 1968, pp. 61–63.

3. Kirkwood, T.B.L., ―Geometric means and measures of dispersion,‖ Letter to the Editor, Biometrics, 1979; 35(4). 4. Milliken, G.A., Johnson, D.E., Analysis of Messy Data, Volume 1: Designed Experiments, Van Nostrand Reinhold Company, New York, NY, 1984, pp. 19–23.

5. Searle, S.R., Casella, G., McCulloch, C.E., Variance Components, John Wiley and Sons, New York, 1992. 6. Snedecor, G.W., Cochran, W.G., Statistical Methods, 8th ed., Iowa State University Press, Ames, IA, 1989.

7. Standard E-691-87: Practice for Conducting an Interlaboratory Study to Determine the Precision of a Test Method, ASTM, West Conshohoken, PA, 1994.

8. Hauck, W.W., Koch, W., Abernethy, D., Williams, R. ―Making sense of trueness, precision, accuracy, and uncertainty,‖ Pharmacopeial Forum, 2008; 34(3).

Tolerance Interval Determination:

1. Hahn, G.J., Meeker, W.Q., Statistical Intervals: A Guide for Practitioners, John Wiley and Sons, New York, 1991. 2. Odeh, R.E., ―Tables of two-sided tolerance factors for a normal distribution,‖ Communications in Statistics: Simulation and Computation, 1978; 7:183–201.