ABSTRACT

Statistics in Plain English is a straightforward, conversational introduction to statistics that delivers exactly what its title promises. Each chapter begins with a brief overview of a statistic (or set of statistics) 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) used 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.

Thoroughly updated throughout, this edition features several key additions and changes. First, a new chapter on person-centered analyses, including cluster analysis and latent class analysis (LCA) has been added, providing an important alternative to the more commonly used variable-centered analyses (e.g., t tests, ANOVA, regression). Next, the chapter on non-parametric statistics has been enhanced with in-depth descriptions of Mann-Whitney U, Kruskal-Wallis, and Wilcoxon Signed-Rank analyses, in addition to the detailed discussion of the Chi-square statistic found in the previous edition. These nonparametric statistics are widely used when dealing with nonnormally distributed data. This 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, as well as more coverage of the normal distribution in statistics. Finally, the book features a multitude of real-world examples throughout to aid student understanding and provides them with a solid understanding of how several statistics techniques commonly used by researchers in the social sciences work.

Statistics in Plain English is suitable for a wide range of readers, including students taking their first statistics course, professionals who want to refresh their statistical memory, and undergraduate or graduate students who need a concise companion to a more complicated text used in their class. 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.

chapter Chapter 2|8 pages

Measures of Central Tendency

chapter Chapter 3|12 pages

Measures of Variability

chapter Chapter 4|10 pages

The Normal Distribution

chapter Chapter 5|14 pages

Standardization and z Scores

chapter Chapter 6|16 pages

Standard Errors

chapter Chapter 8|22 pages

t Tests

chapter Chapter 9|20 pages

One-Way Analysis of Variance

chapter Chapter 10|16 pages

Factorial Analysis of Variance

chapter Chapter 11|16 pages

Repeated-Measures Analysis of Variance

chapter Chapter 12|20 pages

Correlation

chapter Chapter 13|24 pages

Regression

chapter Chapter 14|16 pages

Nonparametric Statistics

chapter Chapter 15|14 pages

Factor Analysis and Reliability Analysis

Data Reduction Techniques

chapter Chapter 16|14 pages

Person-Centered Analysis