References

It is not expected that you look at any of these books (except for the one which is a required text for the course) while taking STAT 554. Primarily, I'm listing these here for your use after you have finished STAT 554, but desire more information on particular topics.

basic books

  1. Statistical Concepts and Methods. Bhattacharyya and Johnson. Wiley (1977).
  2. Biostatistical Analysis, 4th edition. J. H. Zar. Prentice Hall (1999).
  3. Statistics for the Social Sciences. R. R. Wilcox. Academic Press (1996).
  4. Applied Statistics for Engineers and Physical Scientists, 2nd edition. Hogg and Ledolter. Macmillan (1992).
  5. Applied Statistics: A Handbbok of Techniques, 2nd edition. L. Sachs. Springer-Verlag (1984).
  6. Introduction to the Theory of Statistics, 3rd edition. Mood, Graybill, and Boes. McGraw Hill (1974).
  7. Statistical Inference, 2nd edition. Casella and Berger. Duxbury (2001).
The first book is a required book for the course. It includes the prerequisite probability material, as well as material pertaining to some of the more common statistical techniques that we will consider. The second book is an optional selection for the course. It assumes a very low level of mathematical preparation; however, it's coverage of applied techniques is very broad, and the book contains important material that we won't have time to cover this semester. The third book is meant to be an introductory text, but it contains some fairly advanced material (but presented at a low level). I like that Wilcox is really into robustness, but I find fault with some of the material he presents. (But still the book is a treasure-trove of descriptions of good, but unfortunately rarely used, methods.) The fourth book is pretty good, except that it doesn't cover nonparametric statistics. The fifth book is a nice handbook, but not a good text. The last two book get into the theory underlying a lot of the statistical procedures that STAT 554 covers. The one by Casella and Berger will be the text for STAT 652 the next time I teach it.

nonparametrics

  1. Applied Nonparametric Statistics. W. W. Daniel. PWS-Kent (1990).
  2. Applied Nonparametric Statistical Methods. P. Sprent. Chapman and Hall (1989).
  3. Nonparametric Statistical Methods, 2nd edition. Hollander and Wolfe. Wiley (1999).
  4. Nonparametrics: Statistical Methods Based on Ranks. E. L. Lehmann. Holden-Day (1975).
  5. Nonparametric Statistical Inference, 4th edition, revised and expanded. J. D. Gibbons and S. Chakraborti. Marcel Dekker (2003).
The first two of these books are friendlier to the neophyte, although none of the books are terribly difficult. I used the last book as the text book for STAT 657 six times in the past. (But don't buy that edition, since a new edition is ecpected to appear in late 2002.) I'm using the third book as the text for STAT 657 this semester (but only because the new edition of Gibbons and Chakraborti isn't ready yet).

ANOVA

  1. Applied Statistics: Analysis of Variance and Regression. Dunn and Clark. Wiley (1974).
  2. Statistics for Experimenters, An introduction to design, data analysis, and model building. Box, Hunter, and Hunter. Wiley (1978).

categorical data analysis

Bhattacharyya and Johnson (listed above) contains a nice discussion of the analysis of categorized data.

regression

  1. Regression Analysis by Example. Chatterjee and Price. Wiley (1977).
  2. Introduction to Linear Regression Analysis, 2nd edition. Montgomery and Peck. Wiley (1992).
  3. Applied Regression Analysis, 3rd edition. Draper and Smith. Wiley (1998).
The first of these books is easy to read and understand. The Draper and Smith book is at a higher level. (It is used in STAT 656.)

robust statistics and EDA

  1. Fundamentals of Modern Statistical Methods: Substantially Improving Power and Accuracy. R. R. Wilcox. Springer (2001).
  2. Introduction to Robust Estimation and Hypothesis Testing. R. R. Wilcox. Academic Press (1997).
  3. Robust Estimation and Testing. Staudte and Sheather. Wiley (1990).
  4. Understanding Robust and Exploratory Data Analysis. Hoaglin, Mosteller, and Tukey. Wiley (1983).
  5. Graphical Exploratory Data Analysis. du Toit, Steyn, and Stumpf. Springer-Verlag (1986).
  6. Graphical Methods for Data Analysis. Chambers, Cleveland, Kleiner, and Tukey. Wadsworth & Brooks/Cole (1983).
The 2001 Wilcox book is at a much lower level than his 1997 book.

Minitab