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Allyn & Bacon / Prentice Hall

Psychology

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Statistics for Psychology, 4/E
Arthur Aron, Ph.D.State University of New York at Stony Brook
Elaine N. Aron, Ph.D.State University of New York at Stony Brook
Elliot Coups, Ph.D.Memorial Sloan-Kettering Cancer Center

ISBN-10: 0131931679
ISBN-13:  9780131931671

Publisher:  Prentice Hall
Copyright:  2006
Format:  Cloth; 768 pp
Published:  09/01/2005
We're sorry, this product is no longer available and has been replaced with Exam Copy for Statistics for Psychology, 5/E.

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The fourth edition of this popular text uses definitional formulas to emphasize concepts of statistics, rather than rote memorization. This approach constantly reminds students of the logic behind what they are learning, and each procedure is taught both verbally and numerically, which helps to emphasize the concepts. Thoroughly revised, with new content and many new practice examples, this text takes the reader from basic procedures through analysis of variance (ANOVA). Students cover statistics and also learn to read and inderstand research articles.


This product accompanies:
Aron, Aron & Coups,  Statistics for Psychology, 5/E

Q: How important is accessibility in a textbook?  How do you help your students who are intimidated by math and statistics?
A: Aron uses both verbal and numerical explanations—definitional formulas are emphasized over computational so students can understand the logic behind the procedure

  • SHOW: Inside of the cover which lists all the formulas & verbal explanations.
  •  SHOW: boxed verbal explanations next to each numerical formula within the text
  • “Worked-out” practice problems

 Q: How do you use SPSS in your classes? 
A: Many professors use SPSS in the lab and class to help students work out the calculations.

SHOW: new SPSS screen shots within the text

 

 

NEW—SPSS examples–Include with each procedure.

~Shows how to compute procedures in SPSS, including a worked out example with screen prints.

 

NEW—Extensively updated throughout– Updated dozens of examples (especially the in-the-research-literature ones), updated controversies and boxes, updated the psychology topics (e.g., more neuroscience); and further streamlined the exposition.

~Students value material that is fresh and current.

 

NEW–Reorganization–The self-contained chapters on correlation and regression have been moved after t-test and analysis of variance.

~Maintains flexibility, allowing those who want to teach correlation and regression right after chapter 2 can still do so with no problems.

 

NEW—Chapter–Combined the two chapters on one-way analysis of variance into one chapter.

~Makes the whole topic more straightforward.

 

NEW–Writing revisions–The authors have thoroughly reviewed every sentence, simplifying constructions and terminology wherever possible and sometimes rewriting from scratch entire paragraphs or sections.

~Let’s students focus on learning statistics by keeping the reading as simple and straightforward as possible.

 

Emphasis on definitional formulas—As opposed to “computational” formulas.

~Lays bare the underlying logic used for all explanations, worked out examples, and problems.

 Practical, up-to-date excerpts—For each procedure, the text explains how results are described in research articles.

~Makes sure students can use what they have learned to read the statistics sections of psychology research articles.

Verbal and numerical (and usually visual) presentation—With the same example being described in each way.

~Appeals to students with different learning styles—On exercises and test problems students not only write out in words what they are doing, but also make sketches.

Interesting examples throughout—Often include studies of or by researchers of diverse ethnicities.

~Emphasize topics or populations that students find especially appealing.

Attention-grabbing boxes—Each chapter includes one or more boxes about famous statisticians or interesting sidelights.

~Highlight statistical methods as a living, growing field of research.

Complete package of ancillary materials—A web page with additional practice problems and extensive interactive study materials, plus four "mini chapters" covering additional material not in the text, a very substantial test bank; an instructors' manual that provides sample syllabi, lecture outlines, and ready-to-copy (or download) power-point slides or transparencies with examples not in the book; and a very complete students' study guide that also provides a thorough workbook for using SPSS with this book.

SPSS examples–Include with each procedure.

~Shows how to compute procedures in SPSS, including a worked out example with screen prints.

 

Extensively updated throughout– Updated dozens of examples (especially the in-the-research-literature ones), updated controversies and boxes, updated the psychology topics (e.g., more neuroscience); and further streamlined the exposition.

~Students value material that is fresh and current.

 

Reorganization–The self-contained chapters on correlation and regression have been moved after t-test and analysis of variance.

~Maintains flexibility, allowing those who want to teach correlation and regression right after chapter 2 can still do so with no problems.

 

Chapter–Combined the two chapters on one-way analysis of variance into one chapter.

~Makes the whole topic more straightforward.

 

Writing revisions–The authors have thoroughly reviewed every sentence, simplifying constructions and terminology wherever possible and sometimes rewriting from scratch entire paragraphs or sections.

  1. Displaying the order in a group of numbers.

  2. Central tendency and variability.

  3. Some key ingredients for inferential statistics: Z scores, the normal curve, sample versus population, and probability.

  4. Introduction to hypothesis testing.

  5. Hypothesis testing with means of samples.

  6. Making sense of statistical significance: Effect size and statistical power.

  7. Introduction to the t test: Single sample and dependent means.

  8. The t test for independent means.

  9. Introduction to the analysis of variance.

10. Factorial analysis of variance.

11. Correlation.

12. Prediction.

13. Chi-square tests.

14. Strategies when population distributions are not normal: Data transformations and rank-order tests.

15. Integration and the general linear model.

16. Making sense of advanced statistical procedures in research articles.

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