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Statistics for Business and Economics: Excel/Minitab Enhanced
Heinz Kohler
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Recommended Readings

 

 

Chapter 1

American Statistical Association and Institute of Mathematical Statistics. Careers in Statistics. Washington, DC: 1974.

Stigler, S. M. The History of Statistics: The Measurement of Uncertainty Before 1900. Cambridge, MA: Harvard, 1986.

Tanur, Judith M., et al., eds. Statistics: A Guide to the Unknown. 2nd ed. San Francisco: Holden, 1978. A superb volume of 46 essays that describe important applications of statistics in many fields of endeavor. Prepared by a joint committee of the American Statistical Association and the National Council of Teachers of Mathematics.

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Chapter 2 EXCEL

Blattner, Patrick et al. Special Edition Using Microsoft Excel 2000. Indianapolis, IN: Que Corporation, 1999.

Dodge, Mark, and Craig Stinson. Running Microsoft Excel 2000. Redmond, WA: Microsoft P, 1999.

Gookin, Dan, and Sandy Gookin. How to Use Microsoft Excel 2000. Indianapolis, IN: Sams, 1999.

Harvey, Greg. EXCEL for Dummies, 2nd ed. Foster City, CA: IDG, 1994.

---. EXCEL 2000 for Windows for Dummies. Foster City, CA: IDG, 1999.

McCullough, B. D., and H. D. Vinod. "The Numerical Reliability of Econometric Software," Journal of Economic Literature (Jun 1999): 633-65. An important article about the puzzling failure of many statistical software packages to pass even rudimentary tests for numerical accuracy.

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Chapter 2 MINITAB

McCullough, B. D., and H. D. Vinod, "The Numerical Reliability of Econometric Software," Journal of Economic Literature (Jun 1999) 633-65. An important article about the puzzling failure of many statistical software packages to pass even rudimentary tests for numerical accuracy.

Minitab, Inc., Meet MINITAB. State College, PA: Minitab, Inc., Feb 2000.

---. User's Guide 1:Data, Graphics, and Macros. State College, PA: Minitab, Inc., Feb 2000.

---. User's Guide 2: Analysis and Quality Tools. State College, PA: Minitab, Inc., Feb 2000.

---. MINITAB Mini-Manual: A Beginner's Guide to MINITAB Statistical Software. State College, PA: Minitab, Inc., 1995.

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Chapter 3

American Economic Association. "Reviving the Federal Statistical System," Papers and Proceedings, May 1990, 329-44. Explains why official government statistics cannot be taken as unambiguous measures of the truth; shows how they are sensitive to crucial assumptions and the choice of estimating techniques.

Blattner, Patrick et al. Special Edition Using Microsoft Excel 2000. Indianapolis, IN: Que Corporation, 1999. Contains lots of information on retrieving data from the Web; in particular, see Chapter 26.

Coyle, Diane. The Weightless World: Strategies for Managing the Digital Economy. Cambridge, MA: MIT P, 1998. A book that has been called "one of the 10 best business books of 1998" and "one of those rare books that force your thoughts out of their usual grooves."

Dodge, Mark, and Craig Stinson. Running Microsoft Excel 2000. Redmond, WA: Microsoft P, 1999. Contains lots of information on working with external data; in particular, see Chapter 26.

Hill, Brad. Internet Searching for Dummies, 2nd ed. Foster City, CA: IDG, 1998.

Levine, John R., and Margaret Levine Young. More Internet for Dummies, 2nd ed. Foster City, CA: IDG, 1998.

McKnight, Lee W., and Joseph Bailey, eds. Internet Economics. Cambridge, MA: MIT P, 1997. Brings together research on Internet engineering and economics.

Minitab, Inc., User's Guide 1:Data, Graphics, and Macros. State College, PA: Minitab, Inc., 1999. Contains lots of information on retrieving data from the Web; in particular, see Chapter 4.

Moore, D. S. Statistics: Concepts and Controversy. San Francisco: Freeman, 1979. On how data are collected; the focus is on ideas and their impact on everyday life.

Web site http://www.learnthenet.com/english/index.html . Provides a comprehensive on-line Internet tutorial.

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Chapter 4

Cochran, William G. Sampling Techniques. 3rd ed. New York: Wiley, 1977. A lucid and clear account of sample survey techniques.

Deming, W. Edwards. Sample Design in Business Research. New York: Wiley, 1960. The master of quality control examines sampling.

Gallup, George H. The Sophisticated Poll-Watcher's Guide. Princeton, NJ: Princeton Opinion P, 1976. The world's premier sampling pioneer examines the operation of public opinion polls.

Levy, Paul S., and Stanley Lemeshow. Sampling of Populations: Methods and Applications. New York: Wiley, 1999. A highly readable practical treatment of the subject.

Morgenstern, Oskar. On the Accuracy of Economic Observations. 2nd ed. Princeton: Princeton UP, 1963. A classic book about error in economic statistics.

Scheaffer, Richard L., William Mendenhall, and Lyman Ott. Elementary Survey Sampling. Boston: Duxbury P, 1986.

Sielaff, Theodore J. Statistics in Action: Readings in Business and Economic Statistics. San Jose, CA: Lansford P, 1963. Parts II-IV contain a dozen case studies on the use of sampling techniques.

Wheeler, Michael. Lies, Damn Lies, and Statistics: The Manipulation of Public Opinion in America. Dell, 1977. On the use and abuse of public opinion polls.

Wilburn, A. J. Practical Sampling for Auditors. New York: Dekker, 1984.

U.S. Department of Commerce, Bureau of the Census. Statistical Abstract of the United States. Washington, DC: U.S. Government Printing Office, Published annually, Contains a wealth of statistical data, along with discussions on how they are collected and listings of additional data sources.

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Chapter 5

Anderson, V.L,. and R.A. McLean. Design of Experiments: A Realistic Approach. New York: Marcel Dekker, 1974.

Cochran, W.G,. and G.M. Cox. Experimental Designs, 2nd ed. New York: Wiley, 1957.

Davies, Owen L., ed. The Design and Analysis of Industrial Experiments, 2nd ed. New York: Hafner, 1956.

Fisher, Ronald A. Statistical Methods for Research Workers. 14th ed. New York: Hafner, 1970.

Gilbert, J. , R.J. Light, and F. Mosteller, "How Well Do Social Innovations Work?" in J.M. Tanur et al., eds., Statistics: A Guide to Political and Social Issues (San Francisco: Holden Day, 1977): 47-60. Lots of fascinating examples about experiments.

Montgomery, DC Design and Analysis of Experiments, 3rd ed. New York: Wiley, 1991.

Schmidt, S., and R. Launsby. Understanding Industrial Designed Experiments. 4th ed. Colorado Springs: Air Academy P, 1994.

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Chapter 6

Bamford, James. The Puzzle Palace. Boston: Houghton, 1982. A fascinating book critical of the NSA, noted in Application 6.1, Deciphering Secret Codes and in Biography 6.1, William Friedman and Elizebeth Friedman.

Brainerd, B. Weighing Evidence in Language and Literature: A Statistical Approach. Toronto: University of Toronto P, 1974. Very readable.

Hall, Ray O. Handbook of Tabular Presentation: How to Design and Edit Statistical Tables. New York: Ronald P, 1946. A classic style manual and casebook.

Huff, Darrell, and Irving Geis. How to Lie with Statistics. New York: W. W. Norton, 1954. A discussion of graphical fallacies.

Kahn, David. The Codebreakers: The Story of Secret Writing. New York: Macmillan, 1967.

Kjetsaa, Geir. "The Battle of the Quiet Don." Computers and the Humanities. Pergamon P, 1977, vol. 11, 341-46. A statistical study of disputed authorship of The Quiet Don. Was it written by Kryukov or Sholokhov (who received the 1965 Nobel Prize for Literature for it)?

Marks, Leo. Between Silk and Cyanide: A Codemaker's War, 1941-1945. New York: The Free P, 1998. A fascinating story of code making and breaking.

Mosteller, Frederick, and David L. Wallace. Inference and Disputed Authorship: The Federalist. Reading, MA.: Addison, 1964. A more extensive discussion, including historical details and a variety of alternative analyses, of Application 6.2, Deciding Authorship.

Pratt, Fletcher. Secret and Urgent. The Story of Codes and Ciphers. Indianapolis: Bobbs-Merrill, 1939. Contains a discussion of the Shakespeare-Bacon controversy noted in Application 6.2, Deciding Authorship.

Smith, Laurence Dwight. Cryptography: The Science of Secret Writing. New York: W. W. Norton, 1943. More about codes and ciphers, including word-frequency listings for English, French, German, Italian, and Spanish.

Tufte, Edward R. The Visual Display of Quantitative Information. Cheshire, Conn.: Graphics P, reprint 1992. A classic.

Wainer, Howard. "How to Display Data Badly," The American Statistician, May 1984.

---. Visual Revelations: Graphical Tales of Fate and Deception from Napoleon Bonaparte to Ross Perot. New York: Copernicus-Springer-Verlag, 1997.

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Chapter 7

Campbell, Stephen K. Flaws and Fallacies in Statistical Thinking. Englewood Cliffs, NJ: Prentice, 1974. An excellent and amusing discussion aimed at helping consumers of statistics recognize (intentional and unintentional) abuses of statistical tools and gain the ability to judge the quality of statistical evidence.

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Chapter 8

Bernstein, L. Against the Gods: The Remarkable Story of Risk. New York: John Wiley and Sons, 1996.

David, Florence N. Games, Gods, and Gambling. New York: Hafner, 1962. On the origin and history of probability from the earliest times to the Newtonian era.

Feller, William. An Introduction to Probability Theory and Its Applications. New York: Wiley, 1968-1971, 2 volumes. A classic text.

Good, I. J. "Kinds of Probability," Science (Feb. 20, 1959): 443-47. Argues that the theory of probability is older than the human species because the assessment of uncertainty includes learning from experience, which most creatures do.

Heron House Editors. The Odds on Virtually Everything. New York: Putnam's, 1980. A popular book that uses empirical data to determine probabilities for practically anything, anywhere, any time.

Huff, Darrell, How to Take a Chance. New York: W. W. Norton, 1959. An amusing, well-informed book on probability and its many applications.

Laplace, Pierre Simon, Marquis de. A Philosophical Essay on Probabilities. New York: Dover, 1951.

Mises, Richard von. Probability, Statistics and Truth. London: Allen and Unwin, 1961. A classic statement of the objectivist view of probability theory that defines probability as the relative frequency of the observed attribute that would be found if the observations were indefinitely continued.

Mumford, A. G. "A Note on the Uniformity Assumption in the Birthday Problem," The American Statistician (Aug 1977): 119. An extension of the matching birthday problem discussed in Application 8.5 that shows that the probability of at least one match is increased if all birthdays are not equally likely.

Nunnikhoven, Thomas S. "A Birthday Problem Solution for Nonuniform Birth Frequencies," The American Statistician, (Nov 1992): 270-74. An elaboration on this chapter's Application 8.5.

Ramsey, Frank. The Foundations of Mathematics and Other Logical Essays. London: Kegan Paul, 1931. One of the earliest works on subjective probability.

Savage, Leonard J. The Foundations of Statistics. New York: Dover, 1972. A classic statement arguing that subjective probability alone is essential to decision making and rejecting the von Mises view noted above.

Schlaifer, Robert. Probability and Statistics for Business Decisions. New York: McGraw, 1959. One of the first books emphasizing the Bayesian approach to decision making that blends subjective probabilities with objective ones.

Todhunter, Isaac. A History of the Mathematical Theory of Probability. New York: Chelsea, 1949. Deals with the development of the theory from the time of Pascal (Biography 9.2) to the time of Laplace (Biography 8.1).

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Chapter 9

Feller, William. An Introduction to Probability Theory and Its Applications, 2 vols. New York: Wiley, 1950-1966. By far the best textbook on the theory and application of discrete probability distributions.

Folks, J. Leroy. Ideas of Statistics. New York: Wiley, 1981. Pages 118-19 provide the derivation of the Poisson formula from the binomial formula.

Gridgeman, N. T. "Probability and Sex." The American Statistician, (Jun 1968): 29. Shows what the binomial distribution can tell us about the sexes of children in families, including the order of their appearance.

Mosteller, Frederick. Statistics By Example: Finding Models, vol. 4. Reading, MA.: Addison, 1973. Pages 71-3 provide the derivation of the Poisson formula from the binomial formula.

Mullet, Gary M. "Simæ on Poisson and the National Hockey League." The American Statistician (Feb 1977): 8-12. Shows that the Poisson distribution describes the number of goals scored for or against each of the teams that played in the National Hockey League during the 1973-1974 season.

Owen, Donald B. Handbook of Statistical Tables. Reading, MA.: Addison, 1962. One of the most complete and useful volumes of statistical tables.

Wallis, W. Allen. "The Poisson Distribution and the Supreme Court." Journal of the American Statistical Association (Jun 1936): 376-80. Shows that the Poisson distribution describes the number of vacancies on the U.S. Supreme Court.

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Chapter 10

Walker, Helen. Studies in the History of Statistical Method. Baltimore: Williams and Wilkins, 1929. Chapter 2 provides a superb discussion of the history of the normal curve.

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Chapter 11

Adams, William J. The Life and Times of the Central Limit Theorem. New York: Kaedmon, 1974.

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Chapter 12

Arthur Guinness Son & Co., eds. Letters from W. S. Gosset to R. A. Fisher: 1915-1936. Dublin: Guinness, 1967. A stimulating collection of nearly 200 letters that are of great interest for the history of statistical theory and practice.

Pearson, E. S., and John Wishart, eds. "Student's" Collected Papers. London: University College, 1943. A collection of Gosset's writings between 1907 and 1938.

"Student." "The Probable Error of a Mean." Biometrika . (1908): 1-25. The crucial article on the t distribution.

Wooldridge, Jeffrey M. Introductory Econometrics: A Modern Approach. Cincinnati, OH: South-Western, 2000. On estimation, see Appendix C.

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Chapter 13

Fisher, R. A. "On the Mathematical Foundations of Theoretical Statistics." Philosophical Transactions of the Royal Society, 1922, 309-68. An early landmark of the Fisherian revolution in statistics.

---. Statistical Methods for Research Workers, 14th ed. New York: Hafner P, 1970. A classic work on statistical estimation, hypothesis testing, analysis of variance, correlation, and more.

---. Statistical Methods and Scientific Inference, 3rd ed. New York: Hafner P, 1973.

McCloskey, Donald N. "The Loss Function Has Been Mislaid: The Rhetoric of Significance Tests," The American Economic Review (May 1985): 201-05. An important and delightfully written warning about the common misuse of significance tests.

Menges, G. "Inference and Decision." Selecta Statistica Canadiana, vol. 1. New York: Wiley, 1973. Contrasts the Fisher view of statistics with the Neyman-Pearson view.

Morrison, D., and R. E. Henkel. The Significance Test Controversy. Chicago: Aldine, 1970. Raises serious questions about the usefulness and sense of employing significance tests in social-science research.

Neyman, Jerzy, and E. S. Pearson. "On the Problem of the Most Efficient Tests of Statistical Hypotheses." Philosophical Transactions of the Royal Society, 1933, 289-337. This and the preceding entry are two crucial articles developing the modern theory of hypothesis testing.

---. "On the Use and Interpretation of Certain Test Criteria for Purposes of Statistical Inference." Biometrika, 1928, 175-240 and 263-94.

Popper, Karl R. The Logic of Scientific Discovery. New York: Harper, 1965. This book, first published in 1935, presents a detailed discussion of the formulation of hypotheses, their testing through observation, and their role in the development of scientific theories.

Savage, Leonard J. The Foundations of Statistics, rev. ed. New York: Dover, 1972. Contains a sharp attack on hypothesis testing.

Wooldridge, Jeffrey M. Introductory Econometrics: A Modern Approach. Cincinnati, OH: South-Western, 2000. On hypothesis testing, see Appendix C.

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Chapter 14

Bennett, J. H., ed. Experiments in Plant Hybridisation. Edinburgh: Oliver and Boyd, 1965. An interesting supplement to Application 14.2. Reprints Mendel's original article, along with commentary by Ronald A. Fisher.

Fienberg, S. E. The Analysis of Cross-Classified Categorical Data. Cambridge, MA: MIT P, 1987. All about contingency table tests.

Pearson, Karl. "On the Criterion That a Given System of Deviations From the Probable in the Case of a Correlated System of Variables is Such That It Can Be Reasonably Supposed to Have Arisen From Random Sampling." Philosophical Magazine. 5th series (1900): 157-75. Presents the chi-square test of goodness of fit.

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Chapter 15

Anderson, V. L., and R. A. McLean. Design of Experiments: A Realistic Approach. New York: Marcel Dekker, 1974.

Cochran, W. G., and G. M. Cox. Experimental Designs. 2nd ed. New York: Wiley, 1957.

Davies, Owen L., ed. The Design and Analysis of Industrial Experiments. 2nd ed. New York: Hafner, 1956.

Fisher, Ronald A. Statistical Methods for Research Workers, 14th ed. New York: Hafner, 1970.

Fisher, Ronald A., and W. A. Mackenzie. "Studies in Crop Variation, II. The Manurial Response of Different Potato Varieties." Journal of Agricultural Science (1923): 311-20. The seminal article that introduced the analysis of variance.

Snedecor, George W. Calculation and Interpretation of Analysis of Variance and Covariance. Ames, IA: Collegiate P, 1934. One of the earliest tabulations of F distributions, which also explains why the statistic is sometimes referred to as Snedecor's F.

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Chapter 16

Bibby, J. "The General Linear Model–A Cautionary Tale." In C. A. O'Muircheartaigh and Clive Payne, eds, The Analysis of Survey Data, vol. 2: Model Fitting. New York: Wiley, 1977, 35-79. Argues that regression analysis is fragile (that violations of assumptions make the results of such analysis useless).

Folks, J. Leroy. Ideas of Statistics. New York: Wiley, 1981. Chapters 20 and 21 provide fascinating insights into Galton's discovery of regression and correlation. Chapter 22 sheds light on Legendre's principle of least squares.

Frees, Edward W. Data Analysis Using Regression Models: The Business Perspective. Upper Saddle River, NJ: Prentice Hall, 1996. An excellent text.

Friedman, Milton. "Do Old Fallacies Ever Die?" Journal of Economic Literature (Dec 1992): 2129-32. A timely warning about the regression fallacy.

Galton, Francis. "Regression Towards Mediocrity in Hereditary Stature." Journal of the Anthropological Institute (1885): and "Typical Laws of Heredity," Proceedings of the Royal Institute, 8 (1877): 282-301. About the peas experiment featured in text Figure 16.2.

Goldberger, Arthur S. Introductory Econometrics. Cambridge, MA: Harvard UP, 1998. Chapters 6-8 and 13-14 elaborate on simple regression analysis.

Kerlinger, F. N., and E. J. Pedhazur. Multiple Regression in Behavioral Research. New York: Holt, 1973. Argues that regression analysis is robust (that violations of assumptions are not serious).

Manski, Charles F. "Regression." Journal of Economic Literature (Mar 1991): 34-50. A superb survey of the state of modern regression theory.

McCloskey, Deirdre N., and Stephen T. Ziliak. "The Standard Error of Regression," Journal of Economic Literature (Mar 1996): 97-114. A fascinating and important article on the difference between statistical and economic significance.

Stigler, Stephen M. "Gauss and the Invention of Least Squares." The Annals of Statistics, 9 (1981): 465-74. On the development of what is now the most important tool for econometric work.

Walker, Helen M. Studies in the History of Statistical Method. Baltimore: Williams, 1929. Contains (in Chapter 5) an excellent history of regression and correlation theory.

Wonnacott, Thomas H., and Ronald J. Wonnacott. Regression: A Second Course in Statistics. New York: Wiley, 1981. A superb text devoted to regression and correlation analysis at a more advanced level.

Wooldridge, Jeffrey M. Introductory Econometrics: A Modern Approach. Cincinnati, OH: South-Western, 2000. A superb text; on simple regression analysis, see chapters 1-2.

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Chapter 17

Allen, D. M., and R B. Cady. Analyzing Experimental Data by Regression. Belmont, CA: Wadsworth, 1982.

Anderson, Gary M., David M. Levy, and Robert D. Tollison. "The Half-Life of Dead Economists." Canadian Journal of Economics (Feb. 1989): 174-83. An amusing regression study on how fast an economist's work decays over time.

Draper, N., and H. Smith. Applied Regression Analysis. 2nd ed. New York: Wiley, 1981.

Durbin, J. R., and G. S. Watson. "Testing for Serial Correlation in Least Squares Regression," Parts 1-3. Biometrika (1950): 409-28; (1951): 159-78; (1971): 1-20.

Fair, Ray C. "The Economic Effect of Economic Events on Votes for President." The Review of Economics and Statistics, (May 1978): 159-73. A multiple regression model of voting behavior, based on the U.S. experience since 1892.

Franklin, LeRoy A. "Graphical Insight Into Multiple Regression Concepts." The American Statistician (Nov 1992): 284-88. Provides intuition for crucial concepts, including the meaning of R2, the significance of the overall regression model, the multicollinearity problem, and more.

Frees, Edward W. Data Analysis Using Regression Models: The Business Perspective. Upper Saddle River, NJ: Prentice Hall, 1996. An excellent text.

Goldberger, Arthur S. Introductory Econometrics. Cambridge, MA: Harvard UP, 1998. Chapters 9-12 and 15-17 elaborate on multiple regression analysis.

Katz, David A. Econometric Theory and Applications. Englewood Cliffs, NJ: Prentice, 1982. Chapter 4 discusses how to correct for serial correlation, heteroscedasticity, and multicollinearity.

Mendenhall, William, and James T. McClave. A Second Course in Business Statistics: Regression Analysis. San Francisco: Dellen, 1981. Chapter 5 discusses matrix algebra and its application to multiple regression (as, for example, in Formula Boxes 17.C and 17.D).

Wooldridge, Jeffrey M. Introductory Econometrics: A Modern Approach. Cincinnati, OH: South-Western, 2000. A superb text; on multiple-regression analysis, see chapters 3-9.

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Chapter 18

Anderson, T. W., and H. Rubin. "Estimation of the Parameters of a Single Equation in a Complete System of Stochastic Equations." Annals of Mathematical Statistics, March 1949. Introduces the limited-information maximum likelihood method, LIML, also known as the least variance ratio (LVR) method, for estimating a single equation in a simultaneous equations model.

Basmann, Robert L. "A Generalized Classical Method of Linear Estimation of Coefficients in a Structural Equation," Econometrica (Jan 1957): 77-83. A seminal work introducing two-stage least squares, developed independently of Henri Theil below.

Goldberger, Arthur S. Introductory Econometrics. Cambridge, MA: Harvard UP, 1998. Chapters 17-20 elaborate on the use of dummy variables and the construction of simultaneous equations models.

Heckman, James J. "Haavelmo and the Birth of Modern Econometrics: A Review of The History of Econometric Ideas by Mary Morgan." Journal of Economic Literature (Jun 1992): 876-86. A superb review of a superb book. Includes a discussion of the controversial Neyman-Pearson view of hypothesis testing (noted in Chapter 13) and of Bayesian alternatives.

Johnston, J. Econometric Methods. 3rd ed. New York: McGraw, 1994.

Klein, Lawrence R. The Economics of Supply and Demand. (Baltimore: The Johns Hopkins UP, 1983). A very readable econometric discussion of supply side economics by the 1980 Nobel laureate. Includes a discussion of project LINK, which seeks to coordinate econometric models of different countries. This permits forecasts of how political measures taken in one country might affect the economic performance of another. Also includes an extensive bibliography of Klein's works ( 149-61).

Kmenta J. Elements of Econometrics. 2nd ed. (New York: Macmillan, 1986).

Maddala, G. S. Introduction to Econometrics. 2nd ed. (New York: Macmillan, 1992).

Malinvaud, E. Statistical Methods of Econometrics. 3rd ed. (Amsterdam: North-Holland, 1976).

Popper, Karl F. The Logic of Scientific Discovery. (London: Hutchinson, 1959). A discussion of model building. Argues for choosing simplicity when trying to model complex real-world phenomena.

Theil, Henri. Repeated Least-Squares Applied to Complete Equation Systems. (The Hague; Netherlands: Central Planning Bureau, 1953). A seminal work introducing two-stage least squares, developed independently of R. L. Basmann above.

Wooldridge, Jeffrey M. Introductory Econometrics: A Modern Approach. Cincinnati, OH: South-Western, 2000. A superb text; on simultaneous equations models, see chapters 7, 9, 15, and 16.

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Chapter 19

American Economic Association. "Reviving the Federal Statistical System," Papers and Proceedings (May 1990): 329-44. Discusses why official government statistics, such as time-series data on unemployment, cannot be viewed as unambiguous, but are sensitive to numerous assumptions and estimation techniques.

Armstrong, J. Scott. Long-Range Forecasting: From Crystal Ball to Computer. New York: Wiley, 1978. An excellent, wide-ranging discussion with lots of examples.

Bloomfield, Peter. Fourier Analysis of Time Series: An Introduction. New York: Wiley, 1976. Focuses on frequency-domain methods, not discussed in text Chapter 19.

Box, George E. and Gwylim M. Jenkins. Time Series Analysis: Forecasting and Control, rev. ed. San Francisco: Holden, 1976. Focuses on ARIMA models, not discussed in text Chapter 19.

Brown, Robert G. Smoothing, Forecasting, and Prediction of Discrete Time Series. Englewood Cliffs, NJ: Prentice, 1963. Shows, among other things, certain desirable theoretical properties of exponential smoothing.

Farnum, N. and L. Stanton. Quantitative Forecasting Methods. Boston: PWS/Kent, 1989.

Frees, Edward W. Data Analysis Using Regression Models: The Business Perspective. Upper Saddle River, NJ: Prentice Hall, 1996. Chapters 10 and 11 provide more advanced material on time-series models and forecasting.

Jenkins, G. M., and Donald G. Watts. Spectral Analysis and Its Applications. San Francisco: Holden, 1968.

Johnston, J. Econometric Methods. New York: McGraw, 1972. A superb text.

Kendall, Maurice G. Time-series. 2nd ed. New York: Hafner, 1976. Focuses on time-domain methods.

Moore, Geoffrey H. and Julius Shiskin. "Early Warning Signals for the Economy." In Judith M. Tanur et al., eds., Statistics: A Guide to the Unknown. San Francisco: Holden, 1972, 310-20. A discussion of the history, nature, and reliability of leading, coincident, and lagging business-cycle indicators.

Morgenstern, Oskar. On the Accuracy of Economic Observations. 2nd ed. Princeton, N.J.: Princeton UP, 1963. Must reading for anyone working with business and economic statistics.

Newbold, and T. Bos. Introductory Business Forecasting. Cincinnati: South-Western, 1990.

Wonnacott, Thomas H. and Ronald J. Wonnacott. Regression: A Second Course in Statistics. New York: Wiley, 1981. Chapters 6 and 7 contain a more advanced discussion of time-series forecasting.

Wooldridge, Jeffrey M. Introductory Econometrics: A Modern Approach. Cincinnati, OH: South-Western, 2000. A superb text; on forecasting, see chapters 10-12 and 18.

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Chapter 20

Cagan, Phillip, and Geoffrey H. Moore. The Consumer Price Index: Issues and Alternatives. Washington, DC: American Enterprise Institute, 1981. Reviews the history and uses of the CPI, examines its limitations and deficiencies, and recommends feasible improvements.

Fisher, Irving. The Making of Index Numbers: A Study of Their Varieties, Tests, and Reliability. 3rd ed. rev. Boston: Houghton, 1927. A classic work that examines many alternative formulas for computing index numbers.

Maunder, W. F., ed. Bibliography of Index Numbers. London: Athlone P, 1970. An exhaustive listing from 1707 to 1968.

Theil, Henri. "Best Linear Index Numbers of Prices and Quantities." Econometrica (Apr 1960): 464-80. A more advanced development of the theory of chain indexes. (Additional discussion in T. Kloek and G. M. De Wit. "Best Linear and Best Linear Unbiased Index Numbers." Econometrica (Oct 1961): 602-16.

Ulmer, Melville J. The Economic Theory of Cost of Living Index Numbers. New York: Columbia UP, 1950. An imaginative approach to establishing the upper and lower limit of a constant-utility index.

United Nations, Human Development Report 1998 (New York: Oxford UP, 1998): Technical Note, 107. A detailed discussion about the construction of the human development index.

U.S. Department of Labor, Bureau of Labor Statistics. The Consumer Price Index: History and Techniques. Bulletin 1517. Washington, DC: U.S. Government Printing Office, no date. A detailed discussion of procedures from the 1890s to the mid-1960s.

U.S. Department of Labor, Bureau of Labor Statistics. The Consumer Price Index: Concepts and Content over the Years. Report 517, May 1978 (revised).

Wilkerson, Marvin. "Sampling Error in the Consumer Price Index." Journal of the American Statistical Association (Sep 1967): 899-914. A discussion of the inevitable errors contained in an index number produced by a highly complex network of samples.

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Chapter 21

Gibbons, J. Nonparametric Methods for Quantitative Analysis. New York: Holt, 1976.

Lehmann, E. L. Nonparametrics: Statistical Methods Based on Ranks. San Francisco: Holden, 1975.

Noether, Gottfried E. Introduction to Statistics: A Nonparametric Approach. 2nd ed. Boston: Houghton, 1976.

Savage, I. Richard. Bibliography of Nonparametric Statistics. Cambridge, MA.: Harvard UP, 1962.

Siegel, Sidney. Nonparametric Statistics for the Behavioral Sciences. New York: McGraw, 1956. Gives detailed information on applying many nonparametric procedures.

Solterer, J. "A Sequence of Historical Random Events: Do Jesuits Die in Three's?" Journal of the American Statistical Association (Dec 1941): 477-84. Examines the deaths of 597 Jesuit priests in the United States between 1900 and 1939 by means of a runs test to assess the folklore according to which accidents or tragedies occur in triplets. (They do.)

Spearman, Charles E. "The Proof and Measurement of Association Between Two Things." American Journal of Psychology, 15 (1904): 72-101. The original article on rank correlation.

Wilcoxon, Frank. "Individual Comparisons by Ranking Methods," Biometrics Bulletin 1, 6 (1945): 80-83. The pathbreaking article in which the two-sample rank-sum statistic as well as the paired-sample signed-rank statistic first appeared.

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Chapter 22

Deming, W. Edwards. Elementary Principles of the Statistical Control of Quality, Tokyo: Nippon Kagaku Gijutsu Remmei, 1951.

---. Out of the Crisis. Cambridge, MA: MIT Center for Advanced Engineering Study, 1986.

---. Quality, Productivity, and Competitive Position. Cambridge, MA: MIT Center for Advanced Engineering Study, 1983.

Gale, Bradley. Quality as a Strategic Weapon. Cambridge: The Strategic Planning Institute, 1985.

Gitlow, Howard, Shelly Gitlow, Alan Oppenheim, and Rosa Oppenheim. Tools and Methods for the Improvement of Quality. Homewood, IL: Irwin, 1989. Focuses on the Deming philosophy.

Grant, E. L., and R. S. Leavenworth. Statistical Quality Control. 6th ed. New York: McGraw, 1988.

Kane, V. E. Defect Prevention. New York: Marcel Dekker, 1989.

Military Standard Sampling Procedures and Tables for Inspection by Attributes. MIL-STD-105D, Washington, DC: U.S. Government Printing Office, 1963.

Montgomery, Douglas C, Introduction to Statistical Quality Control. 3rd ed, New York: Wiley, 1996.

Ouchi, William G. How American Business Can Meet the Japanese Challenge. Reading, MA: Addison, 1981. Propounds Theory Z, the adaptation of Japanese management practices.

Peters, Tom. Thriving on Chaos. New York: Alfred A. Knopf, 1987. More on total quality control.

Prahalad, C. K. and M. S. Krishnan, "The New Meaning of Quality in the Information Age," Harvard Business Review (Sept-Oct 1999): 109-18. Provides a framework for judging the quality of a company's software, which is becoming a critical source of competitive advantage.

Shewhart, Walter A, Economic Control of Quality of Manufactured Product. New York: D. Van Nostrand, 1931. The first book on control charts, which were introduced by its author in 1924.

The Ernst and Young Quality Improvement Consulting Group, eds. Total Quality: An Executive's Guide for the 1990s. Homewood, IL: Dow Jones, 1990.

Walton, Mary. The Deming Management Method. New York: Dodd, 1986. Chapter 4 tells the parable of the beads, which Deming used to convince factory workers that they should understand the concept of statistical control.

Wheeler, Donald J. Advanced Topics in Statistical Process Control: The Power of Shewhart Charts. SPC P, 1995.

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Chapter 23

Aitchison, John. Choice Against Chance: An Introduction to Statistical Decision Theory. Reading, MA.: Addison, 1970.

Bayes, Thomas, "An Essay Towards Solving a Problem in the Doctrine of Chances." Philosophical Transactions of the Royal Society, 53 (1763): 370-418. The posthumous publication containing Bayes' theorem. Now most easily available in Thomas Bayes. Facsimiles of Two Papers by Bayes. New York: Hafner, 1963.

Bell, David E., R. L. Keeney, and H. Raiffa. Conflicting Objectives in Decisions. New York: Wiley, 1977.

Berkson, Joseph. "My Encounter With Neo-Bayesianism." International Statistical Review, 45 (1977): 1-8. Presents arguments against the Bayesian approach.

Bernstein, L. Against the Gods: The Remarkable Story of Risk. New York: Wiley, 1996.

Box, George E. , and George C. Tiao. Bayesian Inference in Statistical Analysis. Reading, MA: Addison, 1973.

Clemen, R. Making Hard Decisions. Boston: PWS-Kent, 1991.

Dawes, R. M. Rational Choice in an Uncertain World. San Diego: Harcourt, 1988.

Efron, B. "Why Isn't Everyone a Bayesian?" The American Statistician (Feb 1986): 1-11. A discussion, with numerous comments by critics, of the Fisher vs. Neyman-Pearson-Wald controversy.

Fisher, Ronald A. Statistical Methods and Scientific Inference, 2nd ed. rev. New York: Hafner, 1959. In this, his last book, Fisher strongly rejects the Bayesian approach to statistics as well as the view of statistics as a decision-making science traceable to Wald.

Kohler, Heinz. Intermediate Microeconomics: Theory and Applications. 3rd ed. Glenview, IL: Scott, 1990. Includes presentations of basic utility theory (Chapter 2) and of the economics of uncertainty (Chapters 9 and 10).

Luce, Robert D., and Howard Raiffa. Games and Decisions. New York: Wiley, 1958.

Menges, G. "Inference and Decision." Selecta Statistica Canadiana, vol. I. New York: Wiley, 1973. On the Fisher-Wald controversy concerning the nature of statistical science.

Neumann, John von, and Oskar Morgenstern. The Theory of Games and Economic Behavior, rev. ed. Princeton: Princeton UP, 1953. The classic work on game theory that studies decision making under uncertainty that is complicated by a conscious conflict of wills so that the payoff to an action depends not only on the decision maker's choice and "nature," but also on the conscious choices made by other people.

Savage, Leonard J. "The Theory of Statistical Decision." Journal of the American Statistical Association (Mar 1951): 55-67. A classic article, including a stimulating exposition of Wald's work.

Smith, J. Q. Decision Analysis: A Bayesian Approach. London: Chapman and Hull, 1988.

Stigler, Stephen M. "Who Discovered Bayes' Theorem?" The American Statistician (Nov 1983): 290-96. A fascinating article that suggests that Bayes, perhaps, was not the first to discover the theorem bearing his name.

Tsokos, Chris , and I. N. Shimi, eds. The Theory and Applications of Reliability with Emphasis on Bayesian and Nonparametric Methods. New York: Academic Press, 1977.

Wald, Abraham. Sequential Analysis. New York: Wiley, 1947, and Statistical Decision Functions. New York: Wiley, 1950. These books are crucial landmarks in the development of statistics as a decision-making science.

Winkler, Robert L. Introduction to Bayesian Inference and Decision. New York: Holt, 1972.

Zellner, Arnold. An Introduction to Bayesian Inference in Econometrics. New York: Wiley, 1971.

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