We are thrilled to announce that we are moving our textbook to Wiley Canada!
Statistics is a really interesting subject to study. The problem is, despite our best intentions and efforts, it is often hard for instructors and authors to put the concepts into everyday language that students understand. So, in writing this book, we decided to ask students to help us with the language. As we wrote the first six chapters, we asked social science students to read the drafts and provide feedback on their readability and relevance. After completing the first draft, we then piloted the entire book in an introductory statistics class, offered to social science students at the University of Guelph, and then asked those students for feedback. The result, we hope, is a book that will break the statistical language barrier between instructors and students.
Aside from wanting a readable textbook, we also found that instructors and students wanted a book that included only the material they require for a one-semester introductory statistics class. Our original thought was to include 12 chapters. However, after receiving extremely helpful comments from our reviewers, we included an additional chapter in order to separate confidence intervals (Chapter 8) and single sample hypothesis testing (Chapter 9). This allowed for more detail in both areas without being overwhelming. Although you may find that one or two of the chapters are not needed for your course, we believe that we have managed to narrow the focus of the book down to what is typically covered in the majority of introductory courses.
Prior to writing this textbook, we examined the literature on student “statistical anxiety” for insights that might help us shape the structure and content. Cruise and Wilkins (1980) found six reasons for student statistical anxiety: (i) not understanding the value and worth of statistics in their field; (ii) fear of not being able to interpret results properly; (iii) worry about tests and classroom exercises; (iv) lack of confidence regarding the use of statistical computer programs; (v) not asking for help for fear of looking stupid; and (vi) a general nervousness around statistical professors. Armed with this information, we set out with the hope of addressing these areas. We detail our approach in Chapter 1, but would like to highlight a few things that we think students may find of value.
To help students see the relevance of statistics to their chosen field of study, we have included examples of social science research that Canadian researchers have published in peer-reviewed journals. At the end of each chapter, there is a summary of their research, questions about that research that tie into the topics covered in the chapter, and answers to the questions. This will give students the opportunity to see how researchers use the statistical methods.
At the end of each chapter, students will find a list of frequently asked questions (and their answers). Based on student feedback and our own experience, we included some of the most commonly asked questions that students have after reading each chapter. We then provide a detailed response to each.
To provide students with additional information about specific topics we have included “For Your Information” and “Take a Closer Look” sections in each chapter. These are meant to help students become more comfortable with certain topics. For example, in Chapter 5 there is a “For Your Information” section that explains how the normal curve applies to everyday life. In Chapter 8 there is a “Take a Closer Look” section that discusses when students might use a one-sided versus two-sided test.
Cruise and Wilkins (1980) found that students often feel nervous around statistics instructors. As such, we wanted to show that famous statisticians of the past were also normal people. To accomplish this, we included a section at the beginning of each chapter called “A Brief History of…” section where we profile famous statisticians, such as Florence Nightingale.
We have also included a “Did You Know” section in each chapter that provides students with lighthearted and interesting tidbits. For example, in Chapter 4 we explain how the Monty Hall Problem works and in Chapter 11 we discuss the Elevator Paradox.
As we wrote this text, one thing that students and instructors kept asking for was sample problems. In each chapter there are two types of sample problems: exercises and end-of-chapter problems. The exercises have been placed at key points within the text of each chapter. After students have read a certain amount of the material, they can test themselves using the exercise. The answers to these exercises can then be found at the end of the chapter. The end-of-chapter problems include questions that cover the entire chapter. The answers to these questions ARE AVAILABLE HERE.
This textbook includes a number of online resources. Two that we are particularly fond of are the Statistical Concept video tutorials and the Interactive Demonstration tools. The Statistical Concept video tutorials focus on parts of each chapter that we find students tend to have the most problems with. The Interactive Demonstrations allow students to visualize specific types of analyses and then manipulate various settings in the demonstration to see the effects on the results.
You will notice that this textbook does not incorporate the SPSS software within each chapter. The reason for this is twofold. First, given that instructors maybe using different versions of SPSS, we did not want to provide information within the text that might not be consistent with a specific version of SPSS. Second, we found that many instructors are using software other than SPSS, so by not including SPSS material in the textbook, we were able to keep the material relevant to more instructors. However, we have developed a series of short SPSS software video tutorials (including datasets) that demonstrate how to use SPSS for various types of analysis covered in the textbook.
We have often found that instructors want datasets that can be used throughout the entire textbook. We have simulated four datasets, built around fictitious scenarios that contain enough variables to allow the dataset to be used across the entire textbook. Other more topic specific datasets are also available. These datasets are available here.