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References

Published online by Cambridge University Press:  13 December 2024

Steven E. Rigdon ,
Ronald D. Fricker, Jr  and
Douglas C. Montgomery
Steven E. Rigdon
Affiliation:
Saint Louis University, Missouri
Ronald D. Fricker, Jr
Affiliation:
Virginia Polytechnic Institute and State University
Douglas C. Montgomery
Affiliation:
Arizona State University
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Introduction to Probability and Statistics for Data Science
with R
 , pp. 805 - 808
Publisher: Cambridge University Press
Print publication year: 2024

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References

Anderson, E. 1928. The problem of species in the northern blue flags, Iris versicolor L. and Iris virginica L. Annals of the Missouri Botanical Garden, 15(3), 241–332.CrossRefGoogle Scholar
Anderson, E. 1936. The species problem in Iris. Annals of the Missouri Botanical Garden, 23(3), 457–509.CrossRefGoogle Scholar
Ayres-de Campos, D, Bernardes, J, Garrido, A, Marques-de Sa, J, & Pereira-Leite, L. 2000. SisPorto 2.0: a program for automated analysis of cardiotocograms. Journal of Maternal–Fetal Medicine, 9(5), 311–318.Google ScholarPubMed
Bain, L.J., & Engelhardt, M. 1992. Introduction to Probability and Mathematical Statistics. 2nd edn. Duxbury Press.Google Scholar
Bartholomew, D.J. 1957. A problem in life testing. Journal of the American Statistical Association, 52(279), 350–355.CrossRefGoogle Scholar
Bartholomew, D.J. 1995. What is statistics? Journal of the Royal Statistical Society, Series A (Statistics and Society), 158, 3.CrossRefGoogle Scholar
Benjamini, Y., & Hochberg, Y. 1995. Controlling the false discovery rate: a practical and powerful approach to multiple testing. Journal of the Royal Statistical Society: Series B (Methodological), 57(1), 289–300.CrossRefGoogle Scholar
Bickel, P.J., Hammel, E.A., & O'Connell, J.W. 1975. Sex bias in graduate admissions: data from Berkeley. Science, 187(4175), 398–404.CrossRefGoogle ScholarPubMed
Bondah, E.K., Gren, L.H., & Talboys, S.L. 2020. Prevalence, drinking patterns, and risk factors of alcohol use and early onset among Ghanaian senior high school students. American Journal of Preventive Medicine and Public Health, 6(1), 16–25.CrossRefGoogle Scholar
Boslaugh, S. 2007. Secondary Data Sources for Public Health. Cambridge University Press.CrossRefGoogle Scholar
Box, G.E.P., & Draper, N.R. 1987. Empirical Model-Building and Response Surfaces. Wiley.Google Scholar
Box, G.E.P., & Pierce, D.A. 1970. Distribution of residual autocorrelations in autoregressive-integrated moving average time series models. Journal of the American Statistical Association, 65(332), 1509–1526.CrossRefGoogle Scholar
Box, G.E.P., Jenkins, G.M., Reinsel, G.C., & Ljung, G.M. 2008. Time Series Analysis: Forecasting and Control. 4th edn. Wiley.CrossRefGoogle Scholar
Brown, R. 1963. Smoothing, Forecasting and Prediction of Discrete Time Series. Prentice Hall.Google Scholar
Cannon, A.R., Cobb, G.W., Hartlaub, B.A., Legler, J.M., Lock, R.H., Moore, T.L., Rossman, A.J., & Witmer, J. 2018. STAT2: Modeling with Regression and ANOVA. W.H. Freeman.Google Scholar
Caroni, C. 2002. The correct “ball bearings” data. Lifetime Data Analysis, 8, 395–399.CrossRefGoogle ScholarPubMed
Cobb, G.W. 1998. Introduction to Design and Analysis of Experiments. Key College.Google Scholar
Colosimo, B.M., & Del Castillo, E. (eds.) 2006. Bayesian Process Monitoring, Control and Optimization. CRC Press.CrossRefGoogle Scholar
Davis, T.P. 1995. Analysis of an experiment aimed at improving the reliability of transmission centre shafts. Lifetime Data Analysis, 1(3), 275–306.CrossRefGoogle ScholarPubMed
Dixon, W.J., & Massey, F.J. 1983. Introduction to Statistical Analysis. 4th edn. McGraw Hill.Google Scholar
Dua, D., & Graff, C. 2017. UCI Machine Learning Repository. UC Irvine.Google Scholar
Efron, B. 1982. The Jackknife, the Bootstrap and Other Resampling Plans. SIAM.CrossRefGoogle Scholar
Efron, B., & Hastie, T. 2016. Computer Age Statistical Inference: Algorithms, Evidence, and Data Science. Cambridge University Press.CrossRefGoogle Scholar
Efron, B., & Hinkley, D.V. 1978. Assessing the accuracy of the maximum likelihood estimator: observed versus expected Fisher information. Biometrika, 65(3), 457–483.CrossRefGoogle Scholar
Eustace, S., Tello, R., DeCarvalho, V., et al. 1997. A comparison of whole-body turboSTIR MR imaging and planar 99mTc-methylene diphosphonate scintigraphy in the examination of patients with suspected skeletal metastases. American Journal of Roentgenology, 169(6), 1655–1661.CrossRefGoogle ScholarPubMed
Fisher, R. A. 1935. The Design of Experiments. 9th edn. Macmillan.Google Scholar
Fisher, R. A. 1936. The use of multiple measurements in taxonomic problems. Annals of Eugenics, 7(2), 179–188.CrossRefGoogle Scholar
Fisher, R.A., & Balmukand, B. 1928. The estimation of linkage from the offspring of selfed heterozygotes. Journal of Genetics, 20(1), 79–92.CrossRefGoogle Scholar
Gelman, A., Carlin, J.B., Stern, H.S., Dunson, D.B, Vehtari, A., & Rubin, D.B. 2014. Bayesian Data Analysis. 3rd edn. Chapman and Hall/CRC.Google Scholar
Geman, S., & Geman, D. 1984. Stochastic relaxation, Gibbs distributions, and the Bayesian restoration of images. IEEE Transactions on Pattern Analysis and Machine Intelligence, 6(6), 721–741.CrossRefGoogle ScholarPubMed
Gilks, W.R., Thomas, A., & Spiegelhalter, D.J. 1994. A language and program for complex Bayesian modelling. Journal of the Royal Statistical Society: Series D (The Statistician), 43(1), 169–177.Google Scholar
Gillich, E., & Lohweg, V. 2010. Banknote authentication. In: Bildverarbeitung in der Automation. Springer.Google Scholar
Groves, R.M., & Lyberg, L. 2010. Total survey error: past, present, and future. Public Opinion Quarterly, 74(5), 849–879.CrossRefGoogle Scholar
Hare, L.B. 1988. In the soup: a case study to identify contributors to filling variability. Journal of Quality Technology, 20(1), 36–43.CrossRefGoogle Scholar
Hastings, W.K. 1970. Monte Carlo sampling methods using Markov chains and their applications. Biometrika, 57, 97–109.CrossRefGoogle Scholar
Hilbe, J.M. 2011. Negative Binomial Regression. Cambridge University Press.CrossRefGoogle Scholar
Holt, C.C. 1957. Forecasting Seasonals and Trends by Exponentially Weighted Moving Averages, Office of Naval Research Memorandum (Vol. 52). Carnegie Institute of Technology.Google Scholar
Hsiue, Lin-Tee, Ma, , Chen-Chi, M., & Tsai, Hong-Bing. 1995. Preparation and characterizations of thermotropic copolyesters of p-hydroxybenzoic acid, sebacic acid, and hydroquinone. Journal of Applied Polymer Science, 56(4), 471–476.CrossRefGoogle Scholar
Ioannidis, John P.A. 2005. Why most published research findings are false. PLoS Medicine, 2(8), e124.CrossRefGoogle ScholarPubMed
James, G., Witten, D., Hastie, T., & Tibshirani, R. 2021. An Introduction to Statistical Learning: With Applications in R. Springer.CrossRefGoogle Scholar
Johnson, S.K, & Johnson, R.E. 1972. Tonsillectomy history in Hodgkin's disease. New England Journal of Medicine, 287(22), 1122–1125.CrossRefGoogle ScholarPubMed
Jones, B., & Montgomery, D.C. 2019. Design of Experiments: A Modern Approach. Wiley.Google Scholar
Lambert, D. 1992. Zero-inflated Poisson regression, with an application to defects in manufacturing. Technometrics, 34(1), 1–14.CrossRefGoogle Scholar
Lamberton, J.G., Arbogast, B.L., Deinzer, M.L., & Norris, L.A. 1976. A rapid method for the determination of arsenic concentrations in urine at field locations. American Industrial Hygiene Association Journal, 37(7), 418–422.CrossRefGoogle ScholarPubMed
Larsen, R.J., & Marx, M.L. 2005. An Introduction to Mathematical Statistics. Prentice Hall.Google Scholar
Lieblein, J., & Zelen, M. 1956. Statistical investigation of the fatigue life of deep-groove ball bearings. Journal of Research of the National Bureau of Standards, 57(5), 273–316.CrossRefGoogle Scholar
Lindsay, B.G., Kettenring, J., & Siegmund, D.O. 2004. A report on the future of statistics. Statistical Science, 19(3), 387–413.CrossRefGoogle Scholar
Ljung, G.M., & Box, G.E.P. 1978. On a measure of lack of fit in time series models. Biometrika, 65, 197–303.CrossRefGoogle Scholar
Lohr, S.L. 2010. Sampling: Design and Analysis. 2nd edn. Cengage.Google Scholar
Metropolis, N., Rosenbluth, A.W., Rosenbluth, M.N., Teller, A.H., & Teller, E. 1953. Equation of state calculations by fast computing machines. The Journal of Chemical Physics, 21(6), 1087–1092.CrossRefGoogle Scholar
Montgomery, D.C. 2020a. Design and Analysis of Experiments. 10th edn. Wiley.Google Scholar
Montgomery, D.C. 2020b. Introduction to Statistical Quality Control. 8th edn. Wiley.Google Scholar
Montgomery, D.C., Jennings, C.L., & Kulahci, M. 2015. Introduction to Time Series Analysis and Forecasting. 2nd edn. Wiley.Google Scholar
Myers, R.H., Montgomery, D.C., Vining, G.G., & Robinson, T.J. 2010. Generalized Linear Models: With Applications in Engineering and the Sciences. Wiley.CrossRefGoogle Scholar
Nemati, A., Mahdavi, R., & Baghi, A.N. 2012. Case–control study of dietary pattern and other risk factors for gastric cancer. Health Promotion Perspectives, 2(1), 20.Google ScholarPubMed
NIMBLE Development Team. 2022. NIMBLE User Manual. https://r-nimble.org/manuals/NimbleUserManual.pdf.Google Scholar
NIST/SEMATECH. 2021. NIST/SEMATECH e-Handbook of Statistical Methods. www.itl.nist.gov/div898/handbook/.Google Scholar
Patton, G.L., Bravman, J.C., & Plummer, J.D. 1986. Physics, technology, and modeling of polysilicon emitter contacts for VLSI bipolar transistors. IEEE Transactions on Electron Devices, 33(11), 1754–1768.CrossRefGoogle Scholar
Pearl, J., & Mackenzie, D. 2018. The Book of Why: The New Science of Cause and Effect. Basic Books.Google Scholar
Plummer, M. 2012. JAGS Version 3.3. 0 User Manual. International Agency for Research on Cancer.Google Scholar
Quinlan, J.R. 1993. Combining instance-based and model-based learning. In: Proceedings of the Tenth International Conference on Machine Learning. ACM.Google Scholar
Radelet, M.L. 1981. Racial characteristics and the imposition of the death penalty. American Sociological Review, 46(6), 918–927.CrossRefGoogle Scholar
Reintjes, R., de Boer, A., van Pelt, W., & Mintjes-de Groot, J. 2000. Simpson’s paradox: an example from hospital epidemiology. Epidemiology, 11(1), 81–83.CrossRefGoogle ScholarPubMed
Ridgeway, G., & MacDonald, J.M. 2009. Doubly robust internal benchmarking and false discovery rates for detecting racial bias in police stops. Journal of the American Statistical Association, 104(486), 661–668.CrossRefGoogle Scholar
Rudin, W. 1976. Principles of Mathematical Analysis. McGraw Hill.Google Scholar
Salsburg, D. 2001. The Lady Tasting Tea: How Statistics Revolutionized Science in the Twentieth Century. Macmillan.Google Scholar
Scholes, D., Daling, J.R., & Stergachis, A.S. 1992. Current cigarette smoking and risk of acute pelvic inflammatory disease. American Journal of Public Health, 82(10), 1352–1355.CrossRefGoogle ScholarPubMed
Schweizer, E., Rickels, K., Case, W.G., & Greenblatt, D.J. 1991. Carbamazepine treatment in patients discontinuing long-term benzodiazepine therapy: effects on withdrawal severity and outcome. Archives of General Psychiatry, 48(5), 448–452.CrossRefGoogle ScholarPubMed
Serafini, M., Bugianesi, R., Maiani, G., Valtuena, S., De Santis, S., & Crozier, A. 2003. Plasma antioxidants from chocolate. Nature, 424(6952), 1013–1013.CrossRefGoogle ScholarPubMed
Shahar, D.R., Schultz, R., Shahar, A., & Wing, R.R. 2001. The effect of widowhood on weight change, dietary intake, and eating behavior in the elderly population. Journal of Aging and Health, 13(2), 186–199.CrossRefGoogle ScholarPubMed
Shmueli, G. 2010. To explain or to predict? Statistical Science, 25(3), 289–310.CrossRefGoogle Scholar
Soylak, M., Narin, I., de Almeida Bezerra, M., & Ferreira, S.L.C. 2005. Factorial design in the optimization of preconcentration procedure for lead determination by FAAS. Talanta, 65(4), 895–899.CrossRefGoogle ScholarPubMed
Spiegelhalter, D., Thomas, A., Best, N., & Lunn, D. 2003. WinBUGS User Manual.Google Scholar
Spiegelhalter, D., Thomas, A., Best, N., & Lunn, D. 2014. OpenBUGS User Manual. www.openbugs.net/Manuals/Manual.html.Google Scholar
Stokes, M.E., Davis, C.S., & Koch, G.G. 2012. Categorical Data Analysis using SAS. SAS Institute.Google Scholar
Symons, M.J., Grimson, R.C., & Yuan, Y.C. 1983. Clustering of rare events. Biometrics, 39(1), 193–205.CrossRefGoogle ScholarPubMed
Talalay, P., Fahey, J.W., Healy, Z.R., Wehage, S.L., Benedict, A.L., Min, C., & Dinkova-Kostova, A.T. 2007. Sulforaphane mobilizes cellular defenses that protect skin against damage by UV radiation. Proceedings of the National Academy of Sciences, 104(44), 17500–17505.CrossRefGoogle ScholarPubMed
Thall, P.F., & Vail, S.C. 1990. Some covariance models for longitudinal count data with overdispersion. Biometrics, 46(3) 657–671.CrossRefGoogle ScholarPubMed
Theobald, C. 1981. The effect of nozzle design on the stability and performance of turbulent water jets. Fire Safety Journal, 4(1), 1–13.CrossRefGoogle Scholar
Thomas, S., Patel, D., Bittel, B., et al. 2021. Effect of high-dose zinc and ascorbic acid supplementation vs usual care on symptom length and reduction among ambulatory patients with SARS-CoV-2 infection: the COVID A to Z randomized clinical trial. JAMA Network Open, 4(2), e210369–e210369.CrossRefGoogle Scholar
Van Nood, E., Vrieze, A., Nieuwdorp, M., et al. 2013. Duodenal infusion of donor feces for recurrent Clostridium difficile. New England Journal of Medicine, 368(5), 407–415.CrossRefGoogle ScholarPubMed
Varberg, D., Purcell, E.J., & Rigdon, S.E. 2007. Calculus Early Transcendentals. Pearson Higher Education.Google Scholar
Vermund, S.H., Kelley, K.F., Klein, R.S., et al. 1991. High risk of human papillomavirus infection and cervical squamous intraepithelial lesions among women with symptomatic human immunodeficiency virus infection. American Journal of Obstetrics and Gynecology, 165(2), 392–400.CrossRefGoogle ScholarPubMed
Wackerly, D., Mendenhall, W., & Scheaffer, R.L. 2014. Mathematical Statistics with Applications. 7th edn. Brooks/Cole.Google Scholar
Wang, F.K. 2000. A new model with bathtub-shaped failure rate using an additive Burr XII distribution. Reliability Engineering & System Safety, 70(3), 305–312.CrossRefGoogle Scholar
Wang, K., Wong, E.L.Y., Ho, K.F., et al. 2020. Intention of nurses to accept coronavirus disease 2019 vaccination and change of intention to accept seasonal influenza vaccination during the coronavirus disease 2019 pandemic: a cross-sectional survey. Vaccine, 38(45), 7049–7056.CrossRefGoogle ScholarPubMed
Weisberg, S. 1986. A linear model approach to backcalculation of fish length. Journal of the American Statistical Association, 81(396), 922–929.CrossRefGoogle Scholar
White, C. 1990. Research on smoking and lung cancer: a landmark in the history of chronic disease epidemiology. Yale Journal of Biology and Medicine, 63, 29–46.Google ScholarPubMed
Winters, P.R. 1960. Forecasting sales by exponentially weighted moving averages. Management Science, 6(3), 324–342.CrossRefGoogle Scholar
Wu, C.F.J., & Hamada, M. 2000. Experiments: Planning, Analysis, and Parameter Design Optimization. Wiley.Google Scholar
Yates, F. 1934. Contingency tables involving small numbers and the χ2 test. Supplement to the Journal of the Royal Statistical Society, 1(2), 217–235.Google Scholar
Yeh, I.-Cheng. 1998. Modeling of strength of high performance concrete using artificial neural networks. Cement and Concrete Research, 28(12), 1797–1808.CrossRefGoogle Scholar

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  • References
  • Steven E. Rigdon, Saint Louis University, Missouri, Ronald D. Fricker, Jr, Virginia Polytechnic Institute and State University, Douglas C. Montgomery, Arizona State University
  • Book: Introduction to Probability and Statistics for Data Science
  • Online publication: 13 December 2024
  • Chapter DOI: https://doi.org/10.1017/9781316286166.022
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  • References
  • Steven E. Rigdon, Saint Louis University, Missouri, Ronald D. Fricker, Jr, Virginia Polytechnic Institute and State University, Douglas C. Montgomery, Arizona State University
  • Book: Introduction to Probability and Statistics for Data Science
  • Online publication: 13 December 2024
  • Chapter DOI: https://doi.org/10.1017/9781316286166.022
Available formats
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Save book to Google Drive

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  • References
  • Steven E. Rigdon, Saint Louis University, Missouri, Ronald D. Fricker, Jr, Virginia Polytechnic Institute and State University, Douglas C. Montgomery, Arizona State University
  • Book: Introduction to Probability and Statistics for Data Science
  • Online publication: 13 December 2024
  • Chapter DOI: https://doi.org/10.1017/9781316286166.022
Available formats
×