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in our difficultly processing quantitative information. In Chapter 1, you will learn about your efficient mind, how it naturally makes inferences about the world, where it can lead you astray, and how competence at interpreting statistical information can help you compensate for the drawbacks that come with being the efficient thinker that you are. In addition, basic statistical concepts that will recur throughout the book will be introduced in this opening chapter.

      Chapter 2 through Chapter 5 contain information about descriptive statistics. The statistical tools in these chapters form the foundation for understanding large amounts of data, something you will likely need to do at some point in your career. Chapter 2 uses a study on gender differences in aggression to describe basic considerations in defining and measuring variables in research. Chapter 3 uses a study on academic burnout to help us learn how to interpret and construct frequency distributions and visual displays of large sets of data. Chapter 4 begins our discussion of quantitative information. By using the same study as we used in the previous chapter, we will learn about summarizing large sets of data in ways that are easy to understand. We will learn the pros and cons of various statistical tools that serve the purpose of summarizing data. Finally, Chapter 5 will introduce the notion of data distributions and locating individual scores within a large dataset. Each of these chapters will help you develop your ability to use a statistical software package commonly used in psychological and social science research.

      Chapter 6 through Chapter 14 contain information about inferential statistics. Chapter 6 introduces the notion of inferential statistics and how they are related to descriptive statistics covered in the previous four chapters. Each of the next eight chapters presents one or more inferential statistical tools. Each chapter is divided into two major themes. The first major theme will be Conceptual Understanding of the Tool. Within this major theme will be three subthemes. The first is called “The Study.” Each chapter opens with a description of a fairly mundane situation. For instance, Chapter 11 opens with a discussion of making pizza for dinner. That situation leads into a description of a research study that is used to begin discussion of a statistical tool. As a study is introduced, basic methodological information is presented in an effort to bridge the gap between research methods and the resulting statistical analyses. The second subtheme is called “The Tool,” and it introduces the statistical tool used to answer the research question. The conceptual logic of the statistic and associated formula are presented in detail. As appropriate for a given chapter, information regarding the hypothesis/ses being tested will be provided in this subsection. Finally, the third subtheme is called “Interpreting the Tool,” and it presents pertinent portion(s) of the results sections of published articles. Explanations of these results presentations allow you to connect what has been learned in the first two subsections of the chapter to a published research study. You do not have to read entire primary source journal articles to understand the statistical information presented in a given chapter.

      The second major theme in each chapter will be Using Your New Statistical Tool and will contain two subthemes. The first subtheme will be “Hand-Calculating the Statistical Tool Under Consideration,” where there will be guidance on how to do just that. Although not always the case, efforts will be made to use a hand-calculation example that is related to the study that was used to open the chapter. For instance, in Chapter 7, when hand-calculating the independent samples t test, a dependent variable related to but not used in the actual research study will be introduced. Only a limited number of datapoints will be used in hand-calculations to make doing so manageable. After each hand-calculation subsection, there will be opportunities to practice calculating the statistical tool being presented. The second subtheme will be “Statistical Tool Under Consideration and SPSS.” Here, you will learn how to set up a spreadsheet using the software program IBM® SPSS® Statistics^* for the statistical tool in that chapter. Then, you will read step-by-step instructions of how to do the appropriate statistical analysis in SPSS with screenshots to point out precisely what should be done at each step. Given that SPSS is often how data are analyzed in “real” research (as opposed to computing statistics by hand), this feature will be one that you can refer to in any situation in which you have to analyze data, even after this class is over. Finally, you will learn how to interpret the SPSS output, with call-out bubbles to highlight what the relevant numbers mean on the SPSS printout and how they relate to the statistic under consideration in that chapter.

      Chapter 15, the last chapter of the book, does not present new statistical information. Rather, it focuses on published research studies and the role of statistics in those studies. It starts with a flowchart that helps you decide what inferential statistical tool to use, given the research hypothesis presented and type of research design used. You can use your kit of statistical tools to help determine the appropriate analysis(ses) to use in a given situation. There are descriptions of six published research studies that used various statistical tools covered in the earlier chapters. These descriptions will include a research hypothesis and a description of the methodology. For each of these six studies, we will walk through the flowchart and determine which tool(s) should be used to answer the research question given the stated hypothesis and methodology used. After we finish discussing these six studies, you will read about three additional published studies and answer a series of questions after each one. This series of questions, in conjunction with the flowchart provided, will help you determine the appropriate statistical tool(s) to use to analyze the data in each study.

      Helpful features

      1 Each chapter begins with a series of learning objectives, that is, what you should be able to do after reading and thinking about that chapter. I know as a student I typically never looked at, much less thought about, such learning objectives; however, they are helpful in previewing and organizing what you are about to read. Please read and think about them (i.e., don’t do what I did).

      2 Each chapter contains technical terminology that is highlighted in marginal definitions. As a general rule, don’t simply memorize these definitions but try to think about how they relate to other information in the chapter. Doing so will help you accomplish the learning objectives at the beginning of each chapter.

      3 Throughout each of the first 14 chapters are periodic Learning Checks to help assure you’re understanding the material up to that point in the chapter. The answers to these questions appear in each Learning Check, so you don’t need to flip around the book to locate the answers. Please don’t just look at the answers and say “Yeah, I get it.” Test yourself because if you don’t get the correct answer, that is a signal to go back and reread that section.

      4 At the end of each of these chapters are Chapter Application Questions that help you integrate the information in that chapter. This feature is like a massive Learning Check that we just discussed. These end-of-chapter questions provide a good way to make sure you “get it” after reading each chapter. They contain a variety of short-answer and multiple-choice questions.

      5 After the Chapter Application Questions are Questions for Class Discussion. Try to answer these questions, as your teacher can use them to help you make sure you understand the material and work with you in case there is any confusion that needs to be ironed out.

      Suggestions welcomed!

      If

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