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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