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Useful Books

On Propaganda & Related Topics

On Statistics

Note: some of these books may be out-of-print or out in a new edition. If you can find them, though, they´re worth having in your library

  • Belsey, David A.; Kuh, Edwin; Welsch, Roy E. Regression Diagnostics. New York: John Wiley & Sons. 1980. ISBN: 0-471-05856-4. [The definitive text on coping with collinearity. Explains various collinearity diagnostics clearly and succinctly. Also covers the determination of “influential data” and outliers and discusses methods for dealing with them. Highly recommended for anyone who works with Multiple Linear Regressions regularly.]
  • Draper, N.R.; Smith, H. Applied Regression Analysis. New York: John Wiley & Sons, Inc. 1981. ISBN: 0-471-02995-5. [The Bible of Multiple Regression–everything you ever wanted to know about Regression, including residual analysis, determination of the “best” regression equation, etc. Covers both linear and non-linear regression techniques. Highly recommended for anyone who works with regression regularly.]
  • Hollander, Myles; Wolfe, Douglas A. Nonparametric Statistical Methods, 2nd Edition. New York: John Wiley & Sons. 1999. ISBN: 0-4711-90454-4.[As comprehensive as the Siegel text below with more detail and examples. Recommended for those who regularly work with nonparametrics.]
  • Lehmann, E.I. Nonparametrics: Statistical Methods Based on Ranks. San Francisco: Holden-Day, Inc. 1975. ISBN: 0-8162-4996-6. [A comprehensive textbook on the subject. Useful, but harder for the practitioner to work with.]
  • Siegel, Sidney; Castellan, N. John. Nonparametric Statistics for the Behavioral Sciences. New York: McGraw-Hill Book Company. 1956. ISBN: 07-057348-4. [This is a non-parametric “cookbook” for nonparametric techniques. Explains the rationale and function of each test as well as the method for performing each test, its use with small samples and large, and its power-efficiency. A must for statistical practitioners who rely on nonparametrics, particularly those who do a lot of small sample analysis.]
Statistics books for the Less Mathematically Inclined–more readable, easier to understand for most people:
  • Bluman, Alan G. A Brief Version: Elementary Statistics, A Step by Step Approach. New York. NY: McGraw-Hill. 2008. ISBN: 1259755339. [An excellent book for those of you who have some adeptness with basic Algebra. The book covers core statistical techniques and stresses real world uses and problems. Lots of pictures, diagrams, and case studies. Very Highly Recommended]
  • Larson, Ron; Farber, Betsy. Elementary Statistics: Picturing the World, 3 ed.. Upper Saddlle River, NJ. 2006. ISBN: 0-13-148317-X [Another excellent book for those of you who have some adeptness with basic Algebra. This book covers a little more than the Bluman book; but the presentation isn’t as glossy. Has lots of good case studies and problems. Very Highly Recommended.]
Books on Statistics Done Wrong or Misused
  • Huff, Darrell. How to Lie with Statistics . W.W. Norton & Company, 201993. ISBN: 0393310728. [A classic, reissued. A wonderful book for the layman dealing with how to identify flawed statistical reporting in the media and elsewhere.]
  • Reinhart, Alex. Statistics Done Worng: The Woefully Complete Guide . San Francisco, No Starch Press, 2015. ISBN: 1-59327-620-6 [ This is an outstanding book for those who would otherwise think they’re up-to-date on their statistical techniques. It points out flaws in statistical techniques typically employed by mainstream statisticians. It calls for major changes in how statisticians do their analyses and how they report them. It specifically targets over-reliance on p-values, and shows how this can negatively impact the quality and efficacy of the research being done Very, very highly recommended for statistical practitioners. ]
  • Zaccaro, Edward. Scammed by Statistics . Hickory Grove Press, 2010. ISBN: 0967991579. [ An easy-to-read book with some interesting examples. ]

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Encyclopedia Brittanica Article on Propaganda [Discusses the various meanings and nuances of the term, its evolution, and its origins. A very good, informative, easy-to-read article.]