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This brief, inexpensive book is designed to help readers identify and then discard the major statistical misconceptions that have infiltrated the way they think about data.
Each misconception consists of five parts:
- The Misconception - a brief description of the misunderstanding
- Evidence that the Misconception Exists - demonstrates the prevalence of the misconception
- Why the Misconception is Dangerous - explains why it is important to correct it
- Undoing the misconception - explains the proper way to think about the concept
- Internet Assignment - a guided interactive Internet activity to help readers gain a firm grasp of the statistical concept and manipulate variables to see how they influence one another.
Statistical Misconceptions reviews 52 statistical misconceptions, grouped into twelve chapters that coincide with the topics typically taught in introductory/intermediate statistics courses: descriptive statistics, distributional shape, bivariate correlation, reliability & validity, probability, sampling, estimation, hypothesis testing, t-Tests involving one or two means, ANOVA and ANCOVA, significance, power, and effect size, and regression. Each chapter opens with an engaging quote and ends with a list of suggested readings. All misconceptions are self-contained so they can be skipped if the reader does not have that particular misconception.
An ideal supplement for courses covering or using descriptive and inferential statistics such as statistics and/or research methods taught in a variety of departments including psychology, education, nursing, business, and the social sciences, this engaging book will also appeal to researchers interested in undoing their statistical misconceptions. Organized in the same order as most statistics courses the book is easy to assign along with a standard textbook.