 | | | | Interpreting Basic Statistics: A Guide and Workbook Based on Excerpts from Journal Articles |  | Author: Zealure C. Holcomb
Publisher: Pyrczak Publishing
Category: Book
List Price: $42.50
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Avg. Customer Rating:  (9 reviews)
Sales Rank: 142653
Languages: English (Original Language), English (Unknown), English (Published)
Media: Paperback
Edition: 5
Number Of Items: 1
Pages: 192
Shipping Weight (lbs): 1.2
Dimensions (in): 10.7 x 8.4 x 0.6
ISBN: 188458571X
Dewey Decimal Number: 519
EAN: 9781884585715
ASIN: 188458571X
Publication Date: January 2007
Availability: Usually ships in 1-2 business days
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| Customer Reviews: Read 4 more reviews...
 good Stat book July 5, 2008
expensive for a paperback but I guess it is in high demand. Book was in very good shape. Shipping was average in speed.
 Pragmatically difficult to use January 17, 2008
2 out of 2 found this review helpful
This is a case of a publisher who puts out different editions without thinking. It difficult (and very expensive)to get all of my students to purchase the same Edition. In fact the latest edition is almost impossible to locate. Yet, the workbook pages are so varied from edition to edition, that it is nearly impossible to coordinate among students in a class. While I applaud Holcomb for wishing to keep the examples fresh and updated, this is a case of simply not thinking about how the book would be used. I would suggest staying away ... its more trouble than its worth.
A little knowledge is a dangerous thing October 28, 2007
8 out of 9 found this review helpful
This book is primarily designed for psychology and other social sciences students, so that they can understand the statistical information in reports, etc., that they may read. It is based on two premises: (1) that a little knowledge is a good thing, and therefore the smaller the knowledge, the better the results; (2) that the best and more significant learning takes place without any 'doing' component; simply reading the text is enough.
Unfortunately, the book calms the unknowning reader into a false sense of security. A very common phrase in the book is "this is beyond the scope of this book," and this is used to dismiss even simple extensions and all calculation. The examples used are trivial and simplified, because anything more might require a calculator and some understanding. The reader is led through some interesting areas of descriptive and inferential statistics, but unless they go somewhere else, they won't learn anything of any significant value. Some terms are used that in proper statistics are now either outdated or given alternative names, but nothing seems to back them up. For example, Gosset and the t test are mentioned, but the common statistical appelation of "Student's t test" is not. ANOVA is introduced, but not how to get the results, nor (really) how to interpret them.
The second premise is perhaps the worst. Unless a student actually crunches some numbers, they will never appreciate how these things work, and in particular the risk of errors by the user. Too much statistical analysis today seems to depend on stuffing all the data into a package, such as SPSS, and looking at the print-out, and only applying some thinking at that point, rather than at the experiemental design, data collection and data entry stages. This book supports this approach in the reader.
If people today are scared of numbers, especially quantities of numbers, surely giving them the tools to deal with those numbers and make sense of them through understanding them is the preferred solution, not the analgesia of non-thinking that characterizes this book. If they were in the engineering or physical sciences, tools and understanding would be the solution adopted. Why is this not the case in the social sciences? Is EVERYONE in these fields both ignorant and terrified of statistics, and numbers in general?
The entire design and philosophy of this book is back-to-front and ultimately counter-productive to the education of people who can actually make sense of statistics. It smooths the pillow of the dying intellect and promises a better life in the next world. It breeds a group of people who drive statistics packages without understanding statistics, while feeling that, somehow, they actually do. It makes the statistical impoverishment of researchers in the social sciences more certain, rather than less.
Because there is no significant level of mathematics involved, readers must learn terminology, rather than what's happening with the data. Instead of an understanding of the fundamentals, the reader learns to identify different statistics and their symbols, different sampling methods by name, etc., but there are no logical connections made, no sense of what statistics is really about in this field. To add to the student's difficulties with a terminology/definitions-based learning strategy, there is no index in this book!
The ideal book for meeting the need for basic statistical understanding is Darrel Huff's "How to Lie with Statistics", which is basic, comprehensive, sceptical and almost devoid of calculation. It actually serves to increase statistical literacy at a basic level, and does not try to extend itself beyond dealing with basic descriptive and inferential statistical problems.
While Huff's book is great for a sceptical analysis at a general level, such as a technical report or paper's conclusions, unfortunately it is of little use in trying to analyze the details of the statistics spewed out in those reports and papers in the social sciences. Pryczak's book attempts to deal with this, but fails miserably on all counts. Readers have no overview, despite the title, of the bigger issues or the need for scepticism and common sense. The explanations are too comfortable and comforting to suggest scepticism of statistical analysis. Readers have no means of accessing the meaning of the statistics, because there is no attempt to deal with real data. Readers never have to DO anything, beyond read the text and look at trivial, doctored examples. The book presents no help whatsoever to a student in a course where even basic statistics have to be derived from some data, e.g., using Excel and its Data Analysis add-in package.
While Huff spends some time on a rigorous interpretation of 'average,' Pyrczak cannot even manage this without waffling, and fails to explain how to calculate a mean, median or mode ("it will be all right, don't be frightened, the horrid statistics won't hurt you, be calm, trust the software package or the other person to get it right, it will be all right"). A formula for the standard deviation is tucked in an appendix. Pyrczak gets into a tangle over standard deviations and standard errors, not being clear about either, really. And from here things go downhill, but the comfortable, comforting tone remains ("In know, statistics is SO hard, but this will allow you to forget all that and feel OK again. You won't be challenged by it if you don't want to be (and who would ever WANT to try to actually understand statistics?).").
In summary, this book is a waste of ANY student's time and money. It is unfortunate that it is a required text in some courses, but that fact probably explains more about the statistical weaknesses in the social sciences than anything else (r^2 > 0.9). This book is actually counter-productive to education in statistics.
Recommendations: (1) If it's a required text in a course you are taking, I pity you. Get a proper statistics text so that you can actually learn something useful.
(2) If you are thinking about using this as a text in a course you are offering, actually look at the book. If you think it's good and useful, get someone else to run your course--your course will not help anyone's statistical understanding (including yours); in fact it will do quite the opposite, without anyone realizing it.
(3) If you are simply interested in learning about statistics, don't even consider this book.
(4) Amazon needs negative star ratings, as this would be about -3 (90% CI of 0.1).
 At too a simple a level to be widely used February 18, 2007
6 out of 8 found this review helpful
While this book does conform to the title segment "A Conceptual Overview", I am not sure that it satisfies an existing market niche. I have been teaching basic statistics at the college level for decades and am used to equations and formulas in a statistics book. Therefore, I will admit that my background may be causing some bias in my outlook.
There is only one formula in this book, the expression for standard deviation and it is in an appendix. And unfortunately, it is not well presented; the sigma notation is used without being well explained. The coverage is thorough; all of the topics that I cover in my basic statistics class are in this book. But covered in such a superficial manner that I find it difficult to believe that the reader will really be learning anything about what statistics really is. I don't see how it is possible to really learn what a mean is without seeing it in formula form.
The only people that I could possibly recommend this book to would be those who have no idea at all what statistics is and what it is used for. Other than that, there seems no other place where it can be used.
 Guide? No! - Workbook? Yes! - Value? So-so / it depends ... February 15, 2007
2 out of 2 found this review helpful
Clearly, this is an introductory book. As the title implies, the book's contents are very basic - most appropriate for undergraduate (or maybe even high school) statistics; probably not for graduate students unless they need something for a 'super quick' review. (But even then, there are references other than this book better suited for that purpose.)
The author says the book might be used to demonstrate "that the interpretation of data is not always straigthforward" (p. vii). But I think using "excerpts" of studies makes it more difficult to understand how and why approaches to data interpretation vary. An appropriately chosen article may serve the purpose as adequately as the book (if not more).
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