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Statistical Methods for the Social Sciences (Englisch) Taschenbuch – 5. Januar 2008

5.0 von 5 Sternen 1 Kundenrezension

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Taschenbuch, 5. Januar 2008
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"This text is readable, understandable, and well-organized. It provides good examples with SPSS output." (Robert Wilson, University of Delaware). "Overall, [Agresti/ Finlay] is a good book for introductory statistics that targets general audiences...it covers most topics you want to cover and allows the instructor to choose which topics to include." (Youqin Huang, State University of New York, Albany) "I originally started using the Agresti/ Finlay book based on its reputation as "the class of the market", in terms of being unfailingly statistically correct and having a "modern" perspective. By "modern", I mean that it is model rather than test oriented, that it gives heavy emphasis to confidence intervals and p-values rather than using arbitrary levels of significance, and that it eschews computational formulae. It has met those expectations..." (Michael Lacey, Colorado State University) "..the book has been a good and helpful resource for me in preparing the class notes and assigning homework qustions. The main concepts to be understood by students are sampling distribution, confidence interval, p-value, linear regression. The book helps in this..." (Arne Bathke, University of Kentucky)


The book presents an introduction to statistical methods for students majoring in social science disciplines. No previous knowledge of statistics is assumed, and mathematical background is assumed to be minimal (lowest-level high-school algebra). The book contains sufficient material for a two-semester sequence of courses. Such sequences are commonly required of social science graduate students in sociology, political science, and psychology. Students in geography, anthropology, journalism, and speech also are sometimes required to take at least one statistics course. Datasets and other resources (where applicable) for this book are available here.

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Format: Taschenbuch
If you follow courses on statistics, even on a more advanced level, then this is the right choice to help you through the hell of statistics. At the end, when you finally understand the key concepts of statistics and the logic behind several fundamental research methods, you will encounter no problems understanding the results of any quantitative research studies.
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Die hilfreichsten Kundenrezensionen auf Amazon.com (beta)

Amazon.com: 3.7 von 5 Sternen 48 Rezensionen
29 von 29 Kunden fanden die folgende Rezension hilfreich
5.0 von 5 Sternen clear presentation, covers a lot of ground 2. April 2000
Von Ein Kunde - Veröffentlicht auf Amazon.com
Format: Gebundene Ausgabe
Your typical undergraduate student who is not a fan of mathematics education will find this book intimidating. But that's not really saying much.
A student who's not math-phobic will enjoy it. It's not one of those statistics texts that tries to give just the concepts and not the underlying math. This one goes for the math -- which is the foundation of the concepts. (Conceptual explanations in plain English are here too! The book is not pure math. Anyway, statistics is equal parts numbers and reasoning.)
The illustrations and diagrams are generally excellent. Each chapter ends with a large selection of questions and exercises (answers to some of these are provided at the back of the book) and a bibliography for further reading. Yes, really useful further reading -- not just academic texts, but popular science magazine articles, biographies of mathematicians, etc.
Notation and terms are boxed off within the text, to be clearly noticeable upon review of the chapter. Helpful for studying.
Sample computer output is given frequently, which is a nice bonus. Sometimes the output of popular statistics software can seem cryptic to the uninitiated. This initiates people. An appendix covers SAS and SPSS usage for each topic in the textbook.
Of course it's up to the reader (or instructor) to choose how much material to cover; you could easily just ignore the last few chapters if you don't need the advanced material. But it's here, which makes this a nice book. (You might want the advanced material SOMEday...)
There are 17 chapters running from "Sampling and Measurement", "Descriptive Statistics" and "Probability Distributions" through regression and correlation, *multiple* regression and correlation, ANOVA, and on to ANCOVA, "Model Building with Multpile Regression", "Logistic Regression", and then a single chapter at the end which briefly talks about the existence of factor analysis, structural equations, and other "Advanced Topics".
It's a well written and quite in-depth textbook. A good choice for learning about statistics; a good choice for keeping on your bookshelf.
14 von 14 Kunden fanden die folgende Rezension hilfreich
5.0 von 5 Sternen As a student and a teacher, I've loved it! 16. September 2003
Von Ellis Godard - Veröffentlicht auf Amazon.com
Format: Gebundene Ausgabe
I was subjected to an earlier edition when I took statistics as an undergraduate, and I've used the 2nd and 3rd editions as a lecturer and professor, and I believe there is no preferable alternative.
Agresti and Finlay are, above all, clear and accurate. Over the last decade, I've looked at several dozen alternatives, hoping to find one that's strong in the areas where this text is weak. I've been enticed by different layouts, writing styles, even overall motifs, but am always reminded of why I (and others) have relied on this text for so long.
Some alternatives are just sloppy - poor editing, excessive typographic errors, incorrect answers in the answer keys. Some others border on incompetent, confusing basic issues and not clarifying the disputes on border issues. And some, while achieving rapport through comics, comedy, or simply light humor, lose some of the subtle finesse that statistics entails.
Now, this one ain't perfect. The subtleties and disputes are side-stepped rather than highlighted. The text and layout are a bit wordy and eye-hard. And the examples are more practical than pedagogical. The data examples could be a bit sexier.
But the meat is all there, and correct, and clear. And that's what you want in a statistics textbook. You don't need something that pretends stats is inherently fun or exciting. The lecturer should convey the power of p, the coolness of coefficients, and the holy grail of "r-squared". The text book should cover the material accurately and in detail, and this one does.
13 von 13 Kunden fanden die folgende Rezension hilfreich
4.0 von 5 Sternen A good choice for learning Quantitative Research Methodologies 14. Juni 2008
Von Jonathan D. Bostic - Veröffentlicht auf Amazon.com
Format: Gebundene Ausgabe Verifizierter Kauf
As a doctoral student with an interest in quantitative research and evaluation methodologies, I am currently using this book for a course in regression analyses. It is a fairly easy read for those who are familiar with statistics and I would recommend it to those wanting to learn more about quantitative analyses. The examples are up-to-date compared to previous editions. There appear to be no substatial content differences between this edition and the previous editions (in my experience having read both).
14 von 15 Kunden fanden die folgende Rezension hilfreich
2.0 von 5 Sternen Poorly edited... 26. Februar 2011
Von PoliSciGrad - Veröffentlicht auf Amazon.com
Format: Gebundene Ausgabe Verifizierter Kauf
This book has solid formulae, but
Some of the exercises weren't checked for validity.
I wasted an hour when a prediction equation contained a negative coefficient,
when it in fact should have been positive. I hate when this happens, because students often
Assume that these things are adequately proofread and mathematically sound.
For the amount students are charged for academic texts such as these, this is simply unacceptable.
Also, some of the terminology in the exercises deviates from that covered in the chapters.
Eg; strength in association suddenly becomes magnitude. You eventually infer these relationships, but
When you're in the middle of trying to complete your homework and your constantly cycling back to the chapter in order to
Verify the correct processes needed to complete the problem, the last thing you need is to have an author suddenly
Deviate from the standard (pardon the pun) terminology. I understand that these books take a lot of time and energy to produce, hence the significant cost, but my time is valuable as well and given this, the overall cost is not worth it for this book.
10 von 10 Kunden fanden die folgende Rezension hilfreich
5.0 von 5 Sternen Solid Text on Introductory Applied Statistics. A Keeper. 29. März 2010
Von A. Luque - Veröffentlicht auf Amazon.com
Format: Gebundene Ausgabe Verifizierter Kauf
Well... the text is pretty straightforward. It markets itself particularly to the social sciences, but in reality it is nothing more than an introductory statistics text. Nonetheless, it is very clearly written and covers most of the basics you need to do any kind of research (multiple regressions, ANOVA, basic t,z, and F-tests, etc.). This is by no means a theoretical textbook: if you want to learn about distribution theory and the proofs behind the tests look elsewhere. If you want a quick introduction and reference to the different methods and tests with all the assumptions and potential pitfalls then this text is perfect.
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