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Introductory Statistics: A Conceptual Approach Using R
Contributor(s): Ware, William B. (Author), Ferron, John M. (Author), Miller, Barbara M. (Author)
ISBN: 0805836519     ISBN-13: 9780805836516
Publisher: Routledge
OUR PRICE:   $356.25  
Product Type: Hardcover - Other Formats
Published: December 2012
Qty:
Annotation:

This comprehensive and uniquely organized text is aimed at undergraduate and graduate level statistics courses in education and psychology. An organization scheme built around common issues and problems rather than statistical techniques allows students to understand the conceptual nature of statistical procedures. Likewise, it is so comprehensive and clearly written that instructors are freed from a considerable amount of didactic presentation thus allowing them to engage more with cases and examples of analysis. Whenever possible, presentations contain explanations of the underlying reasons behind a technique. For example, nearly all introductory texts specify that when doing chi-squared tests on count data, expected cell frequencies should be five or more but most don't tell why. This text does.

Additional Information
BISAC Categories:
- Education | Statistics
- Education | Research
- Psychology | Research & Methodology
Dewey: 519.5
LCCN: 2012024922
Physical Information: 1.13" H x 7" W x 10" (2.45 lbs) 518 pages
 
Descriptions, Reviews, Etc.
Publisher Description:

    This comprehensive and uniquely organized text is aimed at undergraduate and graduate level statistics courses in education, psychology, and other social sciences. A conceptual approach, built around common issues and problems rather than statistical techniques, allows students to understand the conceptual nature of statistical procedures and to focus more on cases and examples of analysis. Wherever possible, presentations contain explanations of the underlying reasons behind a technique. Importantly, this is one of the first statistics texts in the social sciences using R as the principal statistical package. Key features include the following.

    • Conceptual Focus - The focus throughout is more on conceptual understanding and attainment of statistical literacy and thinking than on learning a set of tools and procedures.
    • Problems and Cases - Chapters and sections open with examples of situations related to the forthcoming issues, and major sections ends with a case study. For example, after the section on describing relationships between variables, there is a worked case that demonstrates the analyses, presents computer output, and leads the student through an interpretation of that output.
    • Continuity of Examples - A master data set containing nearly all of the data used in the book's examples is introduced at the beginning of the text. This ensures continuity in the examples used across the text.
    • Companion Website - A companion website contains instructions on how to use R, SAS, and SPSS to solve the end-of-chapter exercises and offers additional exercises.
    • Field Tested - The manuscript has been field tested for three years at two leading institutions.