●Updated discussion of polling and random digit dialing in Section 8.4.
●A new Section 14.11 on the “file drawer effect,” whereby nonsignificant statistical findings are never published and the importance of replication.
●Revised numerical examples.
●New examples and questions throughout the book.
●Computer outputs and website have been updated
●Fundamental concepts and procedures are clearly explained, and special effort has been made to clarify topics in statistics that are often seen as "mystifying."
●Unnecessary math, computational busy work, and subtle technical distinctions are avoided without sacrificing either accuracy or realism.
●Single examples permeate whole chapters, or even several related chapters, serving as handy frames of reference for new concepts and procedures.
●Each chapter begins with a preview and ends with a summary, lists of important terms and key equations, and review questions.
●Key statements appear in bold type, and step-by-step summaries of essential procedures, such as solving normal curve problems, appear in boxes.
●Important definitions and reminders about key points appear in page margins.
●Scattered throughout the book are examples of computer outputs for three of the most prevalent programs: Minitab, SPSS, and SAS.
●Progress Checks are introduced within chapter sections and are designed to minimize cumulative confusion. Each chapter ends with Review Questions.
●Questions have been selected to appeal to student interests and provide real-world examples such as a t-test analysis of global temperatures to evaluate a possible greenhouse effect (13.7).
●Appendix B supplies answers to questions marked with an asterisks while other appendices provide a practical math review complete with self-tests, a glossary, and tables of statistical distribution
PART 1 Descriptive Statistics: Organizing and Summarizing Data
2 Describing Data with Tables and Graphs
3 Describing Data with Averages
4 Describing Variability
5 Normal Distributions and Standard (z) Scores
6 Describing Relationships: Correlation
PART 2 Inferential Statistics: Generalizing Beyond Data
8 Populations, Samples, and Probability
9 Sampling Distribution of the Mean
10 Introduction to Hypothesis Testing: The z Test
11 MORE ABOUT HYPOTHESIS TESTING
12 Estimation (Confidence Intervals)
13 t Test for One Sample
14 t Test for Two Independent Samples
15 t Test for Two Related Samples (Repeated Measures)
16 Analysis of Variance (One Factor)
17 Analysis of Variance (Repeated Measures)
18 Analysis of Variance (Two Factors)
19 Chi-Square (X2) Test For Qualitative (Nominal) Data
20 Tests for Ranked (Ordinal) Data
21 Postscript: Which Test?