Statistical Misconceptions
Shipping & Delivery
Our Delivery Time Frames Explained
2-4 Working Days: Available in-stock
14-28 Working Days: On Backorder
Will Deliver When Available: On Pre-Order or Reprinting
We ship your order once all items have arrived at our warehouse and are processed. Need those 2-4 day shipping items sooner? Just place a separate order for them!
Product details
- ISBN 9781138120068
- Weight: 589g
- Dimensions: 152 x 229mm
- Publication Date: 15 Dec 2015
- Publisher: Taylor & Francis Ltd
- Publication City/Country: GB
- Product Form: Hardback
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.
