IBM SPSS for Introductory Statistics

Use and Interpretation

George A. Morgan, Karen C. Barrett, Nancy L. Leech, Gene W. Gloeckner

• Editorial: Routledge
• Año: 2019
• ISBN:
  9781000011753
• Edición: 6
• Categoría: Psychologie
• Categoría: Forschung & Methodik in der Psychologie

IBM SPSS for Introductory Statistics is designed to help students learn how to analyze and interpret research. In easy-to-understand language, the authors show readers how to choose the appropriate statistic based on the design, and to interpret outputs appropriately. There is such a wide variety of options and statistics in SPSS, that knowing which ones to use and how to interpret the outputs can be difficult. This book assists students with these challenges.

Comprehensive and user-friendly, the book prepares readers for each step in the research process: design, entering and checking data, testing assumptions, assessing reliability and validity, computing descriptive and inferential parametric and nonparametric statistics, and writing about results. Dialog windows and SPSS syntax, along with the output, are provided. Several realistic data sets, available online, are used to solve the chapter problems. This new edition includes updated screenshots and instructions for IBM SPSS 25, as well as updated pedagogy, such as callout boxes for each chapter indicating crucial elements of APA style and referencing outputs.

IBM SPSS for Introductory Statistics is an invaluable supplemental (or lab text) book for students. In addition, this book and its companion, IBM SPSS for Intermediate Statistics, are useful as guides/reminders to faculty and professionals regarding the specific steps to take to use SPSS and/or how to use and interpret parts of SPSS with which they are unfamiliar.

CHAPTER 1

Variables, Research Problems, and Questions

Research Problems

The research process begins with an issue or problem of interest to the researcher. This research problem is a statement that asks about the relationships between two or more variables; however, almost all research studies have more than two variables.¹ Appendix B provides templates to help you phrase your research problem and different types of research questions. It also provides examples from the expanded high school and beyond (HSB) dataset that is described in this chapter and used throughout the book.

The process of moving from a sense of curiosity, or a feeling that there is an unresolved problem to a clearly defined, researchable problem, can be complex and long. That part of the research process is beyond the scope of this book, but it is discussed in most books about research methods and books about completing a dissertation or thesis.

Variables

Key elements in a research problem are the variables. A variable is defined as a characteristic of the participants or situation in a given study that has different values. A variable must vary or have different values in the study. For example, sex at birth can be a variable because it normally has two values, female or male. Age is a variable that can have a large number of values. Type of treatment/intervention (or type of curriculum) is a variable if there is more than one treatment or a treatment and a control group. The number of days to learn something or to recover from an ailment are common measures of the effect of a treatment and, thus, are also potential variables. Similarly, amount of mathematics knowledge can be a variable because it can vary from none to a lot.

However, even if a characteristic has the potential to be a variable, if it has only one value in a particular study, it is not a variable; it is a constant. Thus, ethnic group is not a variable if all participants in the study are Asian American. Gender is not a variable if all participants in a study are cis-female.

In quantitative research, variables are defined operationally and are commonly divided into independent variables (active or attribute), dependent variables, and extraneous variables. Each of these topics is dealt with briefly in the following sections.

Operational Definitions of Variables

An operational definition describes or defines a variable in terms of the operations or techniques used to make it happen or measure it. When quantitative researchers describe the variables in their study, they specify what they mean by demonstrating how they measured the variable. Demographic variables like age, gender, or ethnic group are usually measured simply by asking the participant to choose the appropriate category from a list.

Types of treatment (or curriculum) are usually operationally defined much more extensively by describing what was done during the treatment or new curriculum. Likewise, abstract concepts like mathematics knowledge, self-concept, or mathematics anxiety need to be defined operationally by spelling out in some detail how they were measured in a particular study. To do this, the investigator may provide sample questions, append the actual instrument, or provide a reference where more information can be found.

Independent Variables

There are two types of independent variables, active and attribute. It is important to distinguish between these types when we discuss the results of a study. As presented in more detail later, an active independent variable is a necessary but not sufficient condition to make cause and effect conclusions.

Active or manipulated independent variables. An active independent variable is a variable, such as a workshop, new curriculum, or other intervention, at least one level of which is given to a group of participants, within a specified period of time during the study.

For example, a researcher might investigate a new kind of therapy compared to the traditional treatment. A second example might be to study the effect of a new teaching method, such as cooperative learning, compared to independent learning. In these two examples, the variable of interest is something that is given to the participants. Thus, active independent variables are given to the participants in the study but are not necessarily given or manipulated by the experimenter. They may be given by a clinic, school, or someone other than the investigator, but from the participants’ point of view, the situation is manipulated. To be considered an active independent variable, the treatment should be given after the study is planned so that there could be a pretest. Other writers have similar but, perhaps, slightly different definitions of active independent variables. Randomized experimental and quasi-experimental studies have an active independent variable.

Attribute or measured independent variables. An independent variable that cannot be manipulated, yet is a major focus of the study, can be called an attribute independent variable. In other words, the values of the independent variable are preexisting attributes of the persons or their ongoing environment that are not systematically changed during the study. For example, level of parental education, socioeconomic status, age, ethnic group, IQ, and self-esteem are attribute variables that could be used as attribute independent variables. Studies with only attribute independent variables are called nonexperimental studies.

Unlike authors of some research methods books, we do not restrict the term independent variable to those variables that are manipulated or active. We define an independent variable more broadly to include any predictors, antecedents, or presumed causes or influences under investigation in the study. Attributes of the participants as well as active independent variables fit within this definition. For the social sciences and education, attribute independent variables are especially important. Type of disability or level of disability may be the major focus of a study. Disability certainly qualifies as a variable because it can take on different values even though they are not given by the researcher during the study. For example, cerebral palsy is different from Down syndrome, which is different from spina bifida, yet all are disabilities. Also, there are different levels of the same disability. People already have defining characteristics or attributes that place them into one of two or more categories. The different disabilities are characteristics of the participants before we begin our study. Thus, we mi...