

Alpha Center. (1995) Working with Large Insurance Databases: Avoiding and Overcoming the Pitfalls. Robert Wood Johnson Foundation. A good guide to analyzing secondary data found in large insurance databases. Not that you would have access to such data unless you work for an insurance company, or a research group  this guide does show that such data are not such a goldmine of usable data. If you are willing to clean it up you may be able to use it for research, but remember  secondary data are still inferior to the data you collect solely for your research.
Cleveland, W.S. (1993). Visualizing Data. NJ: Hobart Press. A good basic text about the new data analytical tool known as data visualization. Unless you are an engineer and into quality control, skip the text. The graphics may be tempting, but Cleveland is too much a salesman to see the limitations this tool has in the context of good research methodology.
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.
Davidson, F. (1996). Principles of Statistical Data Handling. NY: Sage Publications. Ever wonder what data managers do all day? Well, you can find out with this book that sets out to delineate the handson practice of data management. While basic in its approach, and many principles seem almost common sense to data managers who've been doing this type of work for years (like myself), it's a good review text for data managers of all stripes and sizes. It may be somewhat dry for those who entertain only a passing curiosity of professionals who are fast becoming the 21st century's growing breed of techie grunts. SAS and SPSS applications make this very useful for those who use these software programs, but limits the book's generalizability to those who don't.
FitzGibbon, C.T. & Morris, L.L. (1987). How to Analyze Data. #8 of the "Program Evaluation Kit" 2nd Edition series. An excellent howto book on the analysis of data. Covers descriptive statistics, differences between groups, relationships between variables, analyzing questionnaires, choosing the right statistical procedure, and gives an overview of meta analysis.
Institute of Medicine. (1994) Health Data in the Information Age. Uses, Disclosure, and Privacy. WASH, DC: National Academy Press. As usual, IOM takes on another issue with health policy ramifications that will continue to plague us into the next century. A good scholarly book on what health data are, the problems with storing such data in national databases, and some ideas on what can be done to safeguard such data for the sake of privacy. Read my review in Data Quality.
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 any medical researcher 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.
Selvin, S. (1991). Statistical Analysis of Epidemiologic Data. NY: Oxford University Press. Definitely not for anyone who considers themselves biostatisticallychallenged. 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.
Shenk, D. (1997). Data Smog. NY: HarperCollins Publishers. Basically, an eloquent journalist obsesses over the possible implications of a highly technical society on his trade. More seriously, an entertaining book about the curses rather than the blessings of Technology, more specifically, the doubleedged sword of Internet access. What Shenk refers to information is really data, and data are only as useful as our interpretation of them. It will make you think twice about what we take for granted as a wealth of information that is really impoverishing our quality of life.
Spilker, B. (1986). Interpretation of Clinical Data. NY:Raven Press. What to do with the data you've collected from clinical studies. Hundreds of "Howto" tables. Working with efficacy/safety data.
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.
US General Accounting Office. (April 9, 1997). Statistical Agencies. Consolidation and Quality Issues. GAO (GA/TGGD9778). Is it possible to integrate federal agencies handling data without compromising data quality?? The musings may be theoretical at this point, but if it is at all possible, government can be more efficient if such integration can occur.
US General Accounting Office/Accounting Information and Management Division. (February, 1997). Year 2000 Computing Crisis: An Assessment Guide. Exposure Draft. GAO/AIM10.1.14. A good planning document for any program manager who has at least one computer in the program. This major problem is looming right when the millennium takes off into a new century, and don't say you have never been warned....
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; ageadjustment techniques; categorizing diseases; legislative mandates regarding data.
Wallgren, A., Wallgren, B., Persson, R., Jorner, U., Haaland, JA. (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.
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 mixup 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 realworld 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 recordkeeping has been from underreporting cases and deaths to the lack of testing that should have been done to assess the prevalence of COVID19. 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 wahla, 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?
Marangraphics. (2001). Teach Yourself Visually Microsoft Office 2000. NY: Wiley Publishing. I love this company. Smart graphics will leave nothing to your imagination, which is good for selftaught books. Provides a great intro to what makes MS Office the handsdown favorite suite. Covers Word, Excel, Access, Publisher and Outlook.
Wang, W. & Parker, R.C. (1999). Microsoft Office 2000 for Windows for Dummies CA: IDG Books. Yes, I needed a basic overview of still another version of Microsoft Office. Nothing beat humor and this one has it. Take an informative and humorous tour through Word, Excel, Access, Outlook, Publisher and Smartdraw. Picked up some useful pointers. Let not humor deter you from treating the authors as dummies, they really know their stuff.
Dinwiddie, R. (2000). Charts & Graphics Using Excel 2000 Windows 98. NY: Dorling Kindersley Book. Basic howto manual for using Excel to create charts and graphics.
Dinwiddie, R. (2002). Excel: Formulas & Functions Using Excel 2000 Windows 98. NY: Dorling Kindersley Book. Excellent introduction to the use of formulas in Excel.
MaranGraphics (1999). Teach Yourself Visually  Excel 2000. NY: Wiley Publishing. First off, I love this whole series of visual textbooks from Marangraphics. They know how to make the subject visually interesting and textually understandable. The graphics are cute but add to understanding the software. If you can't stand the thought of a software manual, this may be the text for you. Picked up some pointers here and there.
Brown, F.L., Amos, J.R., & Mink, O.G. (1995). Statistical ConceptsA Basic Program. NY: HarperCollins College Publishers. A selfteaching 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.
Elliot, R.J. (1995). Learning SAS in the Computer Lab. Belmont, CA:Wadsworth Publishing Co. This text is very basic in covering the statistical procedures of SAS. Use only if you have access to SAS in a computer lab WITH a SAS expert nearby.
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 used in analyzing data and then concentrates on how to compute the most common statistical procedures in social science research with SAS, SYSTAT, SPSSX, and Minitab. This is a mustown reference book is a true handbook in every sense of the word.
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.
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 stepbystep sections on using SPSS to perform the necessary statistical procedures. Except for a blatant error on pages 2956 (I won't say what, you should be able to figure this one out), the book is wellwritten and worth having as part of your statistical library.
Brown, F.L., Amos, J.R., & Mink, O.G. (1995). Statistical ConceptsA Basic Program. NY: HarperCollins College Publishers. A selfteaching 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.
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 used in analyzing data and then concentrates on how to compute the most common statistical procedures in social science research with SAS, SYSTAT, SPSSX, and Minitab. This is a mustown reference book is a true handbook in every sense of the word.
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 computergenerated output from SPSS.
Norusis, M. J. (2000). SPSS 10.0 Guide to Data Analysis NJ: Prentice Hall. Probably THE book to have if you are going to use SPSS. Author is wellversed in not only the program, but the basics of data analysis.
Puri, B.K. (2002). SPSS in Practice. An Illustrated Guide. 2nd Edition. NY: Oxford University Press. An excellent beginner's textbook to using SPSS. Provides a good handson overview to conducting data analysis in SPSS. I hope he writes a more detailed book in the future that covers SPSS syntax.
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...
SPSS Inc (1999) SPSS Training. The Basics: SPSS for Windows 10.0 IL: SPSS. Nothing beats the basics. SPSS has put together a really great training manual that is easy to use and does comprehensively cover all the basic procedures that can perform from their navigational and tool bars.
MaranGraphics (1999). Teach Yourself Microsoft Access 2000 Visually. CA: IDG Books. The best series to learn any software program. In color. The more complex the program, the more I'm beginning to appreciate visual books.
Microsoft (1999). Microsoft Access 2000. Step by Step WA: Catapult/Microsoft Press. A good company book to get you started on using the powerful database management software package.
Ray, D.S. & Ray, E.J. (1999). Visual Quickstart Guide Access for Windows 2000 CA:Peachpit Press. A very detailed textbook that will provide you with all the basics you need, plus a little more. Good sections on using Access with the Web.
Rutledge, PA. (1999). Microsoft Access 2000 Fast & Easy. CA: Prima Publishing. Learn with pictures of all the screens.
Siegel, C. (2000) Teach Your Microsoft Access 2000. NY:IDG Books WW. Good, easy to use book, generously illustrated.
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