* It is a straightforward, conversational introduction to statistics that delivers exactly what its title promises.
* Each chapter begins with a brief overview of a statistic that describes what the statistic does and when to use it, followed by a detailed step-by-step explanation of how the statistic works and exactly what information it provides.
* Chapters also include an example of the statistic (or statistics) in use in real-world research, Worked Examples,
Writing It Up sections that demonstrate how to write about each statistic, Wrapping Up and Looking Forward sections, and practice work problems.
* A new chapter on person-centered analyses, including cluster analysis and latent class analysis (LCA) has been added (Chapter 16).
* Person-centered analysis is an important alternative to the more commonly used variable-centered analyses (e.g., t tests, ANOVA, regression) and is gaining popularity in social-science research.
* The chapter on non-parametric statistics (Chapter 14) was enhanced significantly with in-depth descriptions of Mann-Whitney U, Kruskall-Wallace, and Wilcoxon Signed-Rank analyses.
* These non-parametric statistics are important alternatives to statistics that rely on normally distributed data.
* This new edition also includes more information about the assumptions of various statistics, including a detailed explanation of the assumptions and consequences of violating the assumptions of regression (Chapter 13).
* There is more information provided about the importance of the normal distribution in statistics (Chapters 4 and 7).
* Each of the last nine chapters includes an example from the real world of research that employs the statistic, or statistics, covered in the chapter.
* Altogether, these improvements provide important foundational information about how inferential statistics work and additional statistical tools that are commonly used by researchers in the social sciences.
* The text works as a standalone or as a supplement and covers a range of statistical concepts from descriptive statistics to factor analysis and person-centered analyses.
