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Statistical Misconceptions: Classic Edition
Contributor(s): Huck, Schuyler W. (Author)
ISBN: 1138120065     ISBN-13: 9781138120068
Publisher: Routledge
OUR PRICE:   $161.50  
Product Type: Hardcover - Other Formats
Published: December 2015
Qty:
Additional Information
BISAC Categories:
- Psychology | Statistics
- Psychology | Research & Methodology
- Education | Statistics
Dewey: 150.727
LCCN: 2015025799
Series: Psychology Press & Routledge Classic Editions
Physical Information: 0.75" H x 6" W x 9" (1.32 lbs) 320 pages
 
Descriptions, Reviews, Etc.
Publisher Description:

This engaging book helps readers identify and then discard 52 misconceptions about data and statistical summaries. The focus is on major concepts contained in typical undergraduate and graduate courses in statistics, research methods, or quantitative analysis. Interactive Internet exercises that further promote undoing the misconceptions are found on the book's website.

The author's accessible discussion of each misconception has five parts:

The Misconception - a brief description of the misunderstanding

Evidence that the Misconception Exists - examples and claimed prevalence

Why the Misconception is Dangerous - consequence of having the misunderstanding

Undoing the Misconception - how to think correctly about the concept

Internet Assignment - an interactive activity to help readers gain a firm grasp of the statistical concept and overcome the misconception.

The book's statistical misconceptions are grouped into 12 chapters that match the topics typically taught in introductory/intermediate courses. However, each of the 52 discussions is self-contained, thus allowing the misconceptions to be covered in any order without confusing the reader. Organized and presented in this manner, the book is an ideal supplement for any standard textbook.

An ideal supplement for undergraduate and graduate courses in statistics, research methods, or quantitative analysis taught in psychology, education, business, nursing, medicine, and the social sciences. The book also appeals to independent researchers interested in undoing their statistical misconceptions.