Annotated Statistics Bibliography

Suggested Citation: Jung, B.C. (1999 - 2023). Annotated Statistics Bibliography.
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Abelson, R.P. (1995). Statistics as Principled Argument. NJ: Lawrence Erlbaum Associates. THE DEFINITIVE Text to answer the question, "But, what does it mean?" from a social science research standpoint. After you read this text, you will understand how statistics should be used in the context of research methodology to make acceptable numerical claims. His concept of "ticks, buts, and blobs" clarify the strengths and weaknesses of statistical claims. Some of the concepts covered may require a more than basic understanding of statistical analysis, unless you work in research. An excellent read.

American Psychological Association. (2009). Publication Manual of the American Psychological Association, Sixth Edition. DC: APA. This most recent edition of the perennial favorite style manual for the social sciences provides much more than the proper formatting of research articles for publication. It includes many useful chapters about how to present data as well as how to interpret statistical analyses for purposes of reporting. Additional information about how to cite Internet resources makes this a very current reference guide for those interested in scholarly publishing. All around useful textbook for the researcher in all of us.

Argyrous, G. (2000). Statistics for Social & Health Research. With a Guide to SPSS. London: Sage Publications. FOR DATA ANALYSIS - READ THIS BOOK FIRST. An excellent basic textbook about data analysis. What sets this book apart from others covering the same topic is explaining the process of data analysis organized by level of measurement. Thus, all the statistical procedures are presented within the context of the type of data one has to work with. Having read this textbook, I can truly say that this is THE textbook to study from if you want to develop a conceptual understanding of data analysis beyond the tasks of numbers crunching. Excellent step-by-step sections on using SPSS to perform the necessary statistical procedures. Except for a blatant error on pages 295-6 (I won't say what, you should be able to figure this one out), the book is well-written and worth having as part of your statistical library.

Brown, F.L., Amos, J.R., & Mink, O.G. (1995). Statistical Concepts-A Basic Program. NY: HarperCollins College Publishers. A self-teaching text using the concept of programmed learning before programming had anything to do with computers. Covers all the concepts in a sequential manner, with helpful sections on Measurement, and the use of such computer programs as Minitab, SAS and SPSS. An appendix is also devoted to the use of these software applications.

Baker, S. (2002). The Complete Idiot's Guide to Business Statistics IN: Alpha Books. Aside from various typos, this textbook does provide an understandable introduction to statistics as used in business settings. The consistent use of batteries as an example is helpful, as is the glossary of statistical terms.

Baker, Stephen. (2008). The Numerati NY: First Mariner Books. Here is a book that I consider with an air of prescience in which mathematical algorithms are being used to the make decisions in every area of human endeavor. Here is a Brief Summary of the material he covers in his book.

It is somewhat scary about where we are heading in a world where so much information about us can be found on a variety of storage facilities. Imagine what can be done if someone and/or some machine can pull all these bits of information (data in math-speak) and use it to predict human behavior! Well, it is happening now, and Baker does his best in showing how mathematicians are mining the data that are being relentlessly gathered by a variety of entities. From financial to health information, there are tons of data all over the place.

They are beginning to refer to mountains of electronic data as Big Data, all there for the picking by those who know how. Imagine Big Data managers and analysts? Imagine being manipulated by those who have more information on you than you care to disclose? This is partially driven by young people today who think nothing of sharing everything online, sharing information about themselves indiscriminately. Basically, ethical questions should be asked regarding ownership of these data. If the data are about us, shouldn't we have a say about how the data can and cannot be used? Worth reading.

Best, J. (2001). Damned Lies and Statistics. Untangling Numbers from the Media, Politicians, and Activists. CA: University of California Press. "Reality is complicated, and every statistic is someone's summary, a simplification of that complexity. Every statistic must be created, and the process of creation always involves choices that affect the resulting number and therefore affect the resulting number and therefore affect what we understand after the figures summarize and simplify the problem." (p. 161).

Here is a wonderfully readable book about social statistics and how such statistics are used by those not necessarily well-versed in their proper use, but opportunistically mine the numbers, to the detriment of the public's fascination and fear of numbers. Best does for social statistics what Babbie does for social research, and that's really something. Best patiently explains what social statistics should really do, and how they are perpetually misused by non-statisticians to advance hidden agendas through numerical persuasion. Other than mortality statistics, which do not lend themselves to extensive manipulation, social statistics are derived from research that lends itself to how such researchers can creatively define a problem to fit a solution. If you really want to understand how statistics are abused and misused, then this is a must-read. I loved the book.

Best, J. (2004). More Damned Lies and Statistics. How Numbers Confuse Public Issues. CA: University of California Press. What a great follow-up to his 2001 book! Fortunately, I bought both at the same time, so it was a pleasure to read these two sequentially. In this book, Best actually provides examples of the misuse of social statistics for advancing social causes. Because there are so many causes to choose from, activists feel they must emphasize the importance of their particular cause by using statistics. This has lead to a public mistrust of statistics, which, in a way, is a good thing, but unfortunately undermines what statistics can really do, and that is to provide a barometer of how things are going, and a tool for assessing the progress being made to addressing a social problem. Best asserts, "every piece of research contains limitations; researchers inevitably choose specific definitions, measures, designs, and analytic techniques. These choices are consequential; they shape every study's results" (p. 154).

Though I know most of his gems from my work experiences, it is good to see this in print. Best definitely knows what he is talking about, and his call for statistical literacy is important and worthy of adoption by society. Inevitably, we will continually be inundated with statistics because they can be so easily generated these days, at times by those who have no idea of what they are doing, nor do they understand the ethical aspects of being a good statistician. I recommend this book (and his previous book) to everyone who works with statistics because it lays the foundation for appreciating research methodology as a context for generating and interpreting statistics.

Carlan, A. (1998). Everyday Math for the Numerically Challenged NY: Barnes & Nobles. Why should this book be included in this statistics bibliography? Well, I have found that there is a great fear of statistics. And, much of this fear came from a fear of mathematics, which came from a fear of arithmetic. This great little book should help to alleviate a lot of the fear associated with simple math, which, perhaps, some of us never completely mastered, from fractions to decimals, etc. Carlan is a truly great teacher who goes out of the way to make this review painless. However, I must warn you, there are typos. And, you should know they are typos!

Craft, J.L. (1990). Statistics and Data Analysis for Social Workers. 2nd Edition. Itasca,IL: F.E. Peacock Publishers. A straightforward, concise text about analyzing data. Chapter 6's "Crosstabulation Analysis" is the best explanation I've seen on how to do this kind of analysis especially if you have a lot of categorical and ordinal variables you want to include in your overall data analysis. The chapters covering correlational methods and hypothesis testing are good in their simplicity. Good overview of other statistical procedures you may want to develop a basic understanding of.

Devlin, K. (2000). The Math Gene. How Mathematical Thinking Evolved and Why Numbers Are Like Gossip. Great Britain: Weidenfeld & Nicolson. The book has very little to do with the title. It took Devlin 252 page to get to his main point, which I won't disclose, and even then it wasn't suspenseful. A mathematician, he digresses (off-line thinking) into the world of language.

I don't necessarily agree with Devlin that there a math gene, nor are his explanations plausible, even though he does present his arguments in an interesting way (e.g., language was developed so people can talk about other people, or gossip). Be forewarned, if math is not your cup of tea, you will receive support from Chapter 4.

Though Devlin views mathematics as crystallized abstract thinking, justaposing language with mathematics does not jive with me. Just because those gifted in art and music are few in number (as mathematicians), we can still appreciate them for the esthetic pleasure they provide. But, mathematics is different, we may be in awe of their talent, and wish we could be an artist or musician, but not necessarily vie to be a mathematician. Well, at least there's job security for those good with numbers.

Dewdney, A.K. (1993). 200% of Nothing. NY: John Wiley & Sons, Inc. A mathematician takes on statistics and innumeracy. If you can get over his ranting about the continual deterioration of the educational system, of which innumeracy is a sentinel event, you may find this book informative. A more recent rendition of Huff's book. The final chapter provides a short overview of the basic math you should know so you won't be taken by those who don't but like to use numbers to impress an innumerate audience.

Diamond, I. & Jefferies, J. (2001). Beginning Statistics. An Introduction for Social Scientists. CA:Sage Publications. A good, easy-to-understand book about the basic principles of statistics. The authors really do try and make it as painless as possible by sparing the reader of all those (gasp!) formulas. Good relevant examples from the fields of health and social sciences. Authors take the time to work out principles with examples. An appendix of basic arithmetic and alegebraic principles. A nice review for me. However, watch for occasional typos.

Frey, B. (2006). Statistical Hacks. CA: O'Reilly. While I did try to read this for edification, I found it too all over the place. I really had to struggle through the 3 chapters on how to use statistics to win at gambling, which I wasn't really interested in doing, since we all know that nobody wins but the house. However, there were a few gems, like predicting the longevity of any type of phenomenon, and how to do some parlor tricks. You can tell Frey is a diehard statistician and is trying hard to make it "fun", but most people who are reading the book probably won't find it funny at all. Only for the statistical buff.

Foster, J.J. (2001). Data Analysis Using SPSS for Windows Versions 8 to 10. A Beginner's Guide. CA: Sage Publications. A great book for using SPSS. Best beginner's text. But you should have access to the software to make the most of this textbook.

Freed, M.N., Ryan, J.M., & Kess, R.K. (1991). Handbook of Statistical Procedures and Their Computer Applications to Education and the Behavioral Sciences. NY: American Council on Education, Macmillan Publishing Company. This excellent text integrates research theory with statistical techniques. Explains how research questions should be framed and how to answer them with statistical procedures. Provides summaries of research designs, statistical procedures, and sampling techniques. The second half of the text offers a resource listing of existing computer packages that can be used in analyzing data and then concentrates on how to compute the most common statistical procedures in social science research with SAS, SYSTAT, SPSS-X, and Minitab. This must-own reference book is a true handbook in every sense of the word.

Gardner, M.J., & Altman, D.G. (1989). Statistics with Confidence - Confidence Intervals and Statistical Guidelines. London:British Medical Journal. A good text on the use of confidence intervals with various statistical procedures, instead of just citing the p value in reporting research results. Two excellent chapters: "Statistical guidelines for contributors to medical journals" - what to look for in the reporting of medical research, and "Use of check lists in assessing the statistical content of medical studies" offers a peer-review approach to looking at what an excellent research paper would include, from design to statistical analysis.

Gigerenzer, G. (2002). Calculated Risks. How To Know When Numbers Deceive You NY: Simon & Shuster MacMillan Co. An excellent book that introduces you to a better way of understanding statistics. Yes, it is possible to present statistical information in an easy-to-understand format that can be used for decision-making. The author's premise that presenting risk in natural frequencies is the right way to talk about risk is well-supported by examples and explanation. I think this book would be more useful if he also presented a curriculum with which schools and universities can incorporate his ideas into teaching math and statistics from elementary all the way into professional schools (i.e., medicine, law, etc.). Great promise for improving Public Health risk communication, too. Nothing is worst than people trying to fog you with statistics when they themselves don't even understand what they are saying!!! A must read.

Gore, S.M. & Altman, D.G. (1992). Statistics in Practice. London: British Medical Association. A compilation of articles written by the authors dealing with the use of biostatistics in medical research published in the British Medical Journal. Altman manages to find the use of statistics in the medical literature to be as deplorable as the way I used grammar in my high school English compositions. You will learn what's "ludicrous" and "nonsense," as well as what he considers to be the unethical uses of statistics. Gore, a little more tolerant, takes a didactic approach. She shows the reader how to critically assess research design and statistical methods, and offers many useful pointers on how to conduct proper medical research. Excellent articles on confidence intervals, transforming data and data presentation.

Graham, A. (2003) Teach Yourself Statistics. McGrawHill Contemporary Books. ... not sure if you truly can in this update of the 1994 edition of the same name. Graham does do a great job laying out the "minimum" you need to know to understand the increasing reliance on statistics for everything. It does show how much more we need and are expected to learn to grasp the basic concepts. However, for the truly studious, this book will give you everything you need to know to be statistically literate. Graham does take the time to explain the rationale to many of the statistical concepts most numbers crunchers take for granted. Well worth the $12.95 price.

Graham, A. (1994) Teach Yourself Statistics. London:NTC Publishing Group. With this book you can. Good logical progression in presenting the basic statistical concepts, saving probability (the bane of commonfolk) for the end. Excellent basic text, provided you don't mind pounds and pences for dollars and cents, and motorways for highways.

Hinton, P.R. (1995). Statistics Explained. A Guide for Social Science Students. NY: Routledge. SIMPLY THE BEST STATISTICS TEXT. If you can only have one statistics book, or want only one statistics book for your reference library, THIS IS IT. If you still don't understand statistics after reading this book, then there is no hope for you.

Huff, D. (1954). How to Lie With Statistics. NY: W.W. Norton & Company. After 4 decades this classic is still relevant. Often quoted in discussions as THE reference work on the misuse of statistics for nefarious and other reasons, Huff minces no words about the need to exercise skepticism when reading anything statistical. References to income and current events may seem historical now but the reference to the Connecticut Tumor Registry still holds true as the statistical concepts Huff talks about.

Jackson, S.L. (2012). Research Methods and Statistics: A Critical Thinking Approach. 4th Edition. Wadsworth Cengage Publishing. A very good textbook that covers the various methods used by research today and has several chapters about the proper use of statistics in research.

Jaisingh.L. (2000). Statistics for the Utterly Confused. NY:McGraw Hill. It is obvious that statistics is an excellent subject for the continuous publications of books such as these. So whether you are terrified, numerically challenged, hate it, or just utterly confused, there is a book for you. This latest, in the vein of the "Dummies" series, is really very good in laying the foundation for de-confusing yourself. I always manage to learn something from these books, and this one is no exception.

Jones, G.E. (1995). How to Lie With Charts. San Francisco: Sybex. Not really as unethical as the title would "lead" you to believe the book to be. The author takes a back-handed approach to graphing data the right way, and does it splendidly. You really will learn how to be ethical about presenting data. A nice short overview of using a spreadsheet.

Kaplan M. & Kaplan, E. (2006). Chances Are... Adventures in Probability. NY: Penguin/Viking Group. An interesting historical and philosophical look at the contributions of probability and statistics to a variety of disciplines, such as Law, Medicine, Public Health, Science, etc. This book shows we really can learn from history! Vignettes such as how Edwin Chadwick in the 1830s standardized the reporting from local municipalities to help him to make a case about the effects of public hygiene on public health probably set the stage for the reporting of vital statistics today.

It was also interesting to read about the probably first recorded effectiveness study done in 1828 by Pierre Charles Alexandre Louis on the effects of bloodletting on pneumonia. His conclusion that it was totally useless spared numerous people from so-called treatments by leech and lancet. The Kaplans also raise important questions for those working the statistics about why ethical decisions should override scientific ones when in comes to designing studies, and that "the less perfect the study, the more likely a positive result." (p. 168).

Though the Kaplans do try to make a case for the role of probability in many facets of our lives, its misuse by those who do not understand its proper role is probably what hinders the appreciation of what probability can help us in the most, and that's to reduce uncertainty when it comes to decision-making. A worthwhile book to read by those with a "renaissance" frame of mind.

Kranzler, G. & Moursund, J. (1995). Statistics for the Terrified. NJ: Prentice Hall. A "Read-Me-First" book for anyone who HAVE TO take a statistics course. Authors try real hard to make statistical concepts as painless as possible. Actually has very good chapters on variance, how to interpret standard scores, what a Z score is, one-way analysis of variance, the Sheffe method of post hoc analysis, and hypothesis testing. Appendices include a review of the arithmetical concepts you should know, and tips on how to overcome math anxiety.

Lang, T.A., & Secic, M. (1997)How to Report Statistics in Medicine. Annotated Guidelines for Authors, Editors, and Reviewers. PA:American College of Physicians. FINALLY, a guide on how medical research should be reported in the literature!! With this text in print, now there really is no reason for poorly written research reports to be in print, nor for medical researchers not to know how to write up their research in an appropriate fashion. And for research consumers - this text will tell you what you should be looking for when you read the literature.

Langley, R. (1970). Practical Statistics. Dover books. Good basic text. Explains all the different significant tests, what data are required and how to interpret, with examples.

Levitt, Steven D. & Dubner, Stephen J. (2005). Freakonomics. A Rogue Economist Explores the Hidden Side of Everything. NY:HarperCollins Publishers. It is actually a statistical look at modern society that no one ever bothered to do up to this point. The authors do try to put social trends into a new perspective that is worth your time to explore, like how names betray the social class of the parents who pick them for their children, an explanation for lower crime rates, and what exactly is a perfect parent. Challenge your thinking and read this book!

Mlodinow, L. (2008). The Drunkard's Walk. How Randomneess Rules Our Lives NY: Vintage Books. The historical aspects of how many of the principles of probability and statistics were developed is told through biographical sketches of interesting personalities. But I found that the second part that dealt with statistics was more interesting than the first part on probability. While Mlodinow is a gifted storyteller, I am not sure that 190+ pages was needed to support the author's contention that our lives are affected more by chance than we care to admit, in the final chapter of the book.

I suppose if we accept Mlodinow's point that Chance/Luck exists, which I think is the reason why we rely so much on statistics to enhance predictability of phenomena around us, then we would have to agree with him that Luck plays a part in our lives in ways we may not be happy with (bad luck). Obviously, we would like to believe that good luck can befall on us, which is why so many people gamble on lottery tickets, etc. While Mlodinow contends throughout the book that if we understood the principles of probability and statistics, then we can make better decisions about our daily lives, he sort of blows it all by saying that some of us are lucky while others aren't. Maybe food for thought? I am not sure.

Moore, D.S. (1991). Statistics Concepts and Controversies. 3rd Edition. NY: WH Freeman & Co. Taking a very liberal arts approach, Moore talks about statistics in the most broadest sense about how it is used in a variety of disciplines. Very easy to understand if you want to understand why statistics is so important to know, from how it is used, misused, and the best ways to look at and present data, and appropriate ways to interpret statistics. A good section on probability concepts.

Morgan, S.E., Reichert, T., & Harrison, T.J. (2002). From Numbers to Words. Reporting Statistical Results for the Social Sciences. MA: Allyn & Bacon. A slim text of gentle reminders from three young academics on the proper way to report research statistics. As the authors put it, this is a supplemental text. It really does require a basic understanding of statistics. Perhaps, the saddest commentary is how poorly social science research is reported that the authors had to review some 5,000 research articles to come up with examples of the best that were STILL lacking in some way. Perhaps, the worst example can be found on pp. 24-25 in which I found 4 errors without much effort, in a three-sentence excerpt! And, these were just simple things like inconsistency between text and numbers and percentage totals! More comprehensive coverage for statistical reporting can be found in Lang & Sercic's 1997 excellent annotated guidelines.

Munro, B.H., & Page, E.B. (1993). Statistical Methods for Health Care Research. (2nd Edition). Philadelphia, PA: J.B. Lippincott Co. Includes a floppy disk of the statistical program MYSTAT, which is a simplified version of SYSTAT. (EXCELLENT EXPLANATIONS OF ALL THE STATISTICAL TECHNIQUES YOU WILL EVER WANT TO ATTEMPT) Plus - how to interpret computer-generated output from SPSS.

Myatt, M., & Ritter, S. (1997). Analysing Data. A Practical Primer Using Epi Info. Brixton Books. The best of Brixton Books series from Myatt. Does very well in explaining the statistical procedures that can be done with Epi Info, as well as explain how to report statistics in articles, and what the numbers actually mean. Good section on transforming data. Only Brixton Book worth buying.

Newton, R.R., & Rudestam,K.E. (1999). Your Statistical Consultant. Answers to Your Data Analysis Questions. CA:Sage Publications. THE DEFINITIVE STATISTICAL ANSWER BOOK!!! Yes! Finally, two professors put together a readable and informative textbook about all those questions you were too afraid to ask a statistician for fear you may sound stupid. Written for anyone who has a burning statistical question nobody could answer, or, at least to your satisfaction and understanding. Not only do they offer answers, but they do take the time to provide a conceptual basis to tie everything together into a cohesive whole. Also, covers the most current controversies surrounding statistical thinking (and there are plenty), and confirms my suspicion that the reason why a lot of what makes up hypothesis testing is counter-intuitive, really is.... I love these guys!!! Don't miss this one!

Niederman, D., & Boyum, D. (2003). What the Numbers Say. A Field Guide to Mastering our Numerical World. NY: Broadway Books. Two mathematicians try their hardest to put a light spin on the serious subject of critical mathematical thinking skills. Most of the book is quite entertaining and insightful, but be prepared for a serious discussion about math curriculum reform. I do agree with the authors that kids should know basic arithmetic before touching a calculator. I would take one step further and suggest that life math skills be mandatory for all high school graduates. If there is one thing every high school graduate will need to know is how to manage money, which is practical numbers that requires some common sense as well. Is it too much to ask that an 18 year-old know how to balance a checkbook, maintain a savings account, use a credit card judiciously and do an annual tax return? This is a great book about why it is so important to develop an intelligent appreciation of how to use math to enrich our lives.

Norman, G.R., & Streiner, D.L. (1986). PDQ Statistics. Philadelphia, PA: B.C. Decker, Inc. Cram text.

Paulos, J.A. (1995). A Mathematician Reads the Newspaper. NY: Basic Books. Lucky this mathematician only critiqued the abuse found in newspapers. An enjoyable journey through the daily newspapers' attempts to convince us they know what they're talking about - most of the time, they don't. More an essay about the role of math in our daily lives, Paulos still believes in the power of the pen, but wishes those who wield one would take the time to also learn how to count things. May be too math-oriented for some, believe it or not.

Phillips, Jr., J. L. (1992). How to Think About Statistics. NY: W. H. Freeman & Co. Applying statistical concepts to the social sciences. The initial attempts at the beginning of the book to hook the statistically-terrified gets entangled as the author falls back on what he knows best - statistics.

Ramsey, F.L. & Schafer, D.W. (1997). The Statistical Sleuth: A Course in Methods of Data Analysis. CA: Duxbury Press. A really good comprehensive text on how to analyze data. May be a little too heavy if you just want to understand the outcome of statistical procedures.

Rosenthal, J.S. (2006). Struck by Lightning. The Curious World of Probabilities WASH DC: John Henry Press. Incredibly, an enjoyably readable book about probability! Rosenthal applies probability to the real world to explain whether events are truly coincidences or surprises, why casino always wins (even though you may have a lucky streak - that won't last), measuring social trends, research studies, margins of error, and junk e-mail. The most interesting point I learned was that spammers can afford to send out one million junk e-mails for a possible 15 responses, simply because paying so little to stuff our E-mail boxes pays off for them in the long run. Lesson - don't respond to junk E-mail, or make the !@#$% pay! Probability is probably the most hardest mathematical concept to grasp for the average person, but necessary to understand how inferential statistics work. This book will help you understand probability.

Salkind, N.J.(2000). Statistics for People Who (Think They) Hate Statistics. CA: Sage Publications. Yes! Finally, a statistics book written for the truly terrified. Salkind does a great job with explaining statistics in the most simplest way. His love for the subject shows through. Many great extras like SPSS help, software listings, and Web site listings (which you will find on my Statistics Sites Page).

Salsburg, D. (2001). The Lady Tasting Tea. How Statistics Revolutionzed Science in the Twentieth Century. NY: WH Freeman. This humanities-approach look at how Statistics evolved into what it is today is quite insightful. A well-rounded interesting look at the personalities behind the named procedures we use as statisticians. However, I must say that it's incredible that the pettiness of such "great" minds did not undermine the genius each displayed in his own way. I think that increasing accessibility during the 1990s of statistical software programs for the broader audience of numbers crunchers has probably done more to demystify and lessen the anxiety of statistics in our lives, but not necessarily the mathematical theories that seem only to make sense within their own universes. It really wasn't necessary for Salzburg to apologize for not including "everyone" in his Afterword, but it would have been a great benefit if he did summarize all the issues and problems facing Statistics that he identified and mentioned throughout the book. A worthwhile book for those who work as statisticians to discover and appreciate how easy their lives are today as compared to the early 1900s when "computers" and "calculators" were women who spent months tediously doing and redoing the math....

SAS Institute. (1985).SAS Introductory Guide for Personal Computers, Version 6 Edition. NC: SAS Institute. Good intro to the use of a very popular statistical package.

Selvin, S. (1991). Statistical Analysis of Epidemiologic Data. NY: Oxford University Press. Definitely not for anyone who considers themselves biostatistically-challenged. A real technical text that is quite comprehensive in covering statistical measures only principal investigators would be, or should be interested in. A great reference for understanding life tables, censored and truncated data, proportional hazards analyses and logistic modeling. Surprisingly, the earlier chapters on measures of risk, variation and bias were the hardest to get through.

Shiffler, R.E., & Adams, A.J. (1996). Just the Basics, Please: A Quick Review of Math for Introductory Statistics. Belmont, CA: Duxbury Press. (BEST MATH REVIEW TEXT). If probability is an improbable topic, this book spends 3 chapters explaining its concepts in an easy-to-understand way. And, if 8!, permutations, combinations slip your mind in the short-term memory sector, this book is the best to bring it back, or teach you the basics you never learned (or have conveniently forgotten) that you will need to tackle biostatistics. A good section on using a scientific calculator.

Spence, J.T., Cotton, J.W., Underwood, B.J., & Duncan, C.P. (1990). Elementary Statistics. 5TH EDITION. NJ: Princeton Hall. [SIMPLY THE BEST ELEMENTARY STATISTICS TEXTBOOK AROUND]. I didn't know that such a textbook existed (and there are hundreds of elementary stats books to choose from) until I read this one. Everything is explained completely. If you must work with statistics then you must have this textbook.

SPSS. (1999). SPSS Base 10.0 Applications Guide IL: SPSS. Everything you want to know about what SPSS can do, mighty powerful, but too much for the average user. Okay, if you want to be an SPSS maven, memorize this book. I must warn you, new version of SPSS is out...

Sternstein, M. (1994). Barron's EZ-101 Statistics. NY: Barron's Educational Series, Inc. (THE BEST STATISTICS REVIEW TEXT). Covers what an introductory college-level statistics course would cover. There are at least 3 key examples for each major concept from every type of industry.

Stroup, D.F., & Teutsch, S.M. (1998). Statistics in Public Health: Quantitative Approaches to Public Health Problems. NY: Oxford University Press. THE BEST FOR USING STATISTICS IN PUBLIC HEALTH. An excellent textbook on the appropriate use of statistics in solving public health problems. An excellent chapter on the basic principles of statistics is worth buying the book for. Covers everything from conducting needs assessments to program planning and development and how to best use statistics in such tasks. A companion text for Teutsch's other great book, Principles of Public Health Surveillance.

Swinscow, T.D.V. (1990). Statistics At Square One. London: British Medical Association. A compilation of articles published in the British Medical Journal. Good for reviewing the salient points of statistics.

Tal, J. (2001). Reading Between the Numbers. Statistical Thinking in Everyday Life. NY: MacGraw Hill. GET THIS BOOK. If you are truly petrified of statistics, read this book. Tal's general public approach is not only refreshing in the world of statistics, but truly liberating. He grounds statistical thinking in the fabric of our daily lives. All the statistical concepts are explained in PLAIN English, and prefaced by some interesting anecdote, thus, destroying the myth that mathematicians have no life beyond numbers. Chapter 25 is probably the best example of what this man can do - a simple to understand explanation of analysis of variance.

Urden, T.C. (2001). Statistics in Plain English. NJ: Lawrence Erlbaum Association Publishers. GET THIS BOOK. THIS IS THE BEST STATISTICS BOOK AROUND. Yes, Urden knows his stuff, and is a great teacher at explaining the basic concepts of statistics that you will be able to understand. Chapter 11's Repeated-Measures Analysis of Variance is probably the best example of how he takes what is a tough concept and makes it simple to understand. Though his humility is nice to see, this can easily be the best basic textbook of statistics around, not just a review text.

U.S.H.H.S./U.S. Public Health Service/CDC. (1992). Using Chronic Disease Data. Handbook for Public Health Practitioners. Using available US government statistics for research: mortality data, hospital discharge data, behavioral risk factor data; age-adjustment techniques; categorizing diseases; legislative mandates regarding data.

van Belle, G. (2002). Statistical Rules of Thumb. MA: Wiley-Interscience. Very good text for statisticians who want to be a consultant. van Belle is well-versed in the ins and outs of statistical practice across a number of disciplines. There are excellent chapters on how Epidemiology and Environmental Studies are seen through the eyes of a statistician. I found his rules of thumb helpful for understanding a number of concepts, but it may be too much for the average person who just wants to understand the basic principles. There was one rule I did not agree with, and that is his dislike for pie charts. I find pie charts useful in conveying parts of wholes.

Voelker, D.H, & Orton, P.Z. (1993). Statistics. Lincoln, NE: Cliff Notes. Great overview of inferential statistics (everything you ever wanted to ask about statistics but couldn't find someone who could really explain it to your liking).

Wallgren, A., Wallgren, B., Persson, R., Jorner, U., Haaland, J-A. (1996). Graphing Statistics & Data: Creating Better Charts. The definitive book for those who can't stand numbers as numbers and looking for a proper way to present them without misleading the reader or listener. And, no, I didn't misspell the authors - they happen to be Swedish. This text was originally Swedish, but the need for this kind of reference work was so great that it has been translated for the English masses. I'm glad.

Weaver, J.H (2000). Conquering Statistics. Numbers Without the Crunch. MA: Perseus Publishing. Another for the "statistically scared" crowd. Useful for those who just want to understand statistics a little better without having to deal with formulas and tables, from a roll-your-eyes humor perspective. However, it does require you to read a lot of narrative, which could have been better presented with more tables and graphics. Most interesting (and useful) was a good explanation and examples of how to determine sample size - something that is not covered in the majority of statistics and research methods textbooks.

Weinbach, R.W., & Grinnell, R.M. (1991). Statistics for Social Workers. NY: Longman. (THE BEST FOR SIMPLICITY IN UNDERSTANDING HOW TO USE STATISTICS FOR PROGRAM EVALUATION). Good examples of how chi squares are used for this purpose.

Weiss, N.A., & Hassett, M.J. (1991). Introductory Statistics. NY: Addison-Wesley Publishing Co. Basic statistics. Meant to be read sequentially. This text gives you an idea of why a basic statistics course is such a terror to those mathematically challenged.

Yates, K. (2020). The Math of Life & Death. 7 Mathematical Principles that Shape Our Lives. NY: Scribner. In 7 chapters, Kit Yates provides an interesting overview of how mathematics is very much a part of our daily lives. And, it doesn't all have to do with calculations. Because of our numerophobia, we tend to gloss over when numbers become a part of the conversation, which is why mathematics is misused and abused in all walks of life.

Because of mathematical errors, like the misplacement of a decimal point, wrong medication dosages can lead to death, as well as a mix-up in different measurements (liters vs. gallons) can result in running out of plane fuel while a country is switching over to the metric system. Yates shows how the misuse of statistics in the courtroom to sway the jury can result in wrongful imprisonment, and how the mistiming of warning alarms resulted in a bombing that could have been prevented.

Throughout the book, Yates offers real-world and interesting examples of how we really can't do with numbers at the same time offering historical gems on how we ended up with clocks having 24 hours, each hour with 60 minutes, and each minute with 60 seconds. His final chapter "Susceptible, Infective, Removed: How to Stop an Epidemic" was my favorite since it covered Public Health. It was too bad this book came out before the pandemic. I am sure Yates would have offered an enlightened look that how bad our record-keeping has been from underreporting cases and deaths to the lack of testing that should have been done to assess the prevalence of COVID-19. Maybe his next book can be devoted entirely to the topic.

Finally, Chapter 6 on the use of algorithms for everything offers a warning of overdependence on its use for everything. Sure, we want things automated, and we want it done in as orderly fashion as possible. Nevertheless, we should not forget that those who write the algorithms are humans, and humans make mistakes.

I have written enough computer programs to know that you really can tell a computer what to do. And, it will do it exactly the way your coding tells it to do. But, the interpretation still has to be done by humans, and they can always misinterpret the numbers. And, the programmer can introduce a bias in what data are to be included or excluded, which, of course, would result in possibly inaccurate data that could be misinterpreted, adding insult to injury.

It's like people today can plug in a set of numbers into a spreadsheet, and wah-la, a beautiful graph will show up that could be totally meaningless. And, "Even if some of the most complex mental tasks can be farmed out to an algorithm, matters of the heart can never be broken down into a simple set of rules. No code or equation will ever imitate the true complexities of the human condition." (p. 242).

I truly enjoyed this book that sought to explain mathematical concepts in a very understandable way. Yates does provide tables with numbers to illustrate his points, but no formulas that you would need to memorize like when you took it in school to understand what he is trying to say. You will come out with an appreciation of why we need numbers in our lives. After all, what would a birthday be without a number?

Zeisel, H. (1985). Say it With Figures. (6th Edition). NY: Harper & Row. A true classic in how to present data in tabular form. If you plan to present any data, this is a must read.

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Published on the Web: January 24, 2000; February 23, 2001
Updated: 12/27/2022 R228
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