Book by Huck Schuyler W
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"There is a great need for a text to discuss the misconceptions in order to eliminate the myths... The author writes exceptionally well." - Nancy L. Leech, University of Colorado at Denver
"I sometimes feel that I spend as much time getting my students to ‘unlearn’ wrong ideas as I do getting them to learn new material ... I have always been impressed by the clarity of Dr. Huck’s writing ... I could well imagine adopting the book as a secondary text in the graduate-level introductory psychology statistics course [and] recommend it to students who come to me for statistical consulting." - Scott Maxwell, University of Notre Dame
"Readable, great examples... and actually fun... The Internet exercises will go a long way in terms of illustrating the misconception... [useful] at either the undergraduate or graduate level." - Richard Lomax, The Ohio State University
"[An] innovative and much-needed focus on the misconceptions that abound around statistical methods ... I consider [the author's books] to be among the best ... available for the undergraduate curriculum." - Joseph S. Rossi, University of Rhode IslandReseña del editor:
Brief and inexpensive, 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. Fun 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 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.
Statistical Misconceptions is appropriate for courses taught in a variety of disciplines including psychology, medicine, education, nursing, business, and the social sciences. The book also will benefit independent researchers interested in undoing their statistical misconceptions.
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