SPSS for Psychologists

Virginia Harrison, Richard Kemp, Nicola Brace, Rosemary Snelgar

• Publisher: Bloomsbury Academic
• Year: 2020
• Print ISBN: 9781352009941
• eBook ISBN: 9781350312548
• Edition: 7
• Topic: Psychology
• Subtopic: Research & Methodology in Psychology
• Index: Psychology

Students can find statistical analysis a challenging and complex task and, in order to master the techniques and complete their assignments and projects successfully, they need to have a sound understanding of IBM SPSS and its functions. Updated to be compatible with IBM SPSS 25, with handy screen-shots throughout, the seventh edition of this trusted and practical textbook will take students on a step-by-step journey towards carrying out a range of essential tasks with confidence: from performing an analysis to interpreting outputs and reporting the results. This book is an unbeatable, must-have guide to IBM SPSS that will allow undergraduate psychology students to master this powerful software tool.

1	Introduction

In this chapter

• Psychological research and SPSS

• Guide to the statistical tests covered

• Working with SPSS

• Starting SPSS

• How to exit from SPSS

	SPSS for Psychologists online
	Visit macmillanihe.com/harrison-spss-7e for data sets, online tutorials and exercises.

Section 1: PSYCHOLOGICAL RESEARCH AND SPSS

■ IBM SPSS statistics software (SPSS) is a widely used computer program designed to aid the statistical analysis of data, particularly data collected in the course of research.

■ SPSS® has been around in various different forms for many years and has become the ‘industry standard’ software for data analysis.

■ SPSS is the program most widely used by university researchers, especially those working in psychology and the social sciences. SPSS is also widely used in private and government research organisations and many large private companies and nongovernmental organisations.

■ Being able to describe yourself as a competent user of SPSS will enhance your employment prospects considerably.

■ Although at first sight SPSS might appear rather complex, it is not difficult to learn how to undertake a wide range of statistical analyses, and once you have mastered these basics, they will enable you to undertake far more sophisticated research than would be possible without the aid of such software.

But I am studying psychology, not statistics – why do I need to learn to use SPSS?

This is a common question, and the answer lies in the nature of psychology and the type of research that many, if not most, psychologists undertake. It’s important to remember that our current understanding of human behaviour and experience is based on the body of psychological research that has gone before us, so knowing how this research was carried out will allow us to better understand and evaluate the knowledge that we have; and equip us with tools to develop neknowledge.

Much of the research that has been carried out in psychology has used the scientific method, borrowing systematic research frameworks from the sciences. The problem is that people are not the easiest of things to study because they vary both between individuals and over time. That is, different people can react differently to a particular situation; and how a person reacts in a situation today might be quite different from how they react tomorrow. This means that the data collected by psychologists are much more ‘noisy’ than that collected in some other sciences. Consider, for example, a chemist investigating the properties of magnesium. The chemist knows that, under constant conditions, every bit of magnesium will react in the same way as every other bit of magnesium, and that how the magnesium reacts today will be the same as how it reacts tomorrow. Thus, the chemist might only need to do an experiment once using one piece of magnesium to draw firm conclusions about the nature of magnesium in general, and is unlikely to need to use statistics to help explain the results of the observations. The situation facing the psychologist is quite different, and in order to be able to determine how, in general, people react in a given situation, the psychologist will probably need to test a range of different individuals and then make use of statistical techniques to determine what trends are present in the data. So psychologists are particularly likely to need to use statistics in their research.

In recent years, the complexity of the statistical techniques routinely used in psychological research and taught to undergraduate students has increased considerably. This routine reliance on more complex statistical analysis is made possible by the widespread availability of sophisticated statistical analysis software such as SPSS. Thus, in order to be able to undertake psychological research, either as a student or a professional, you need to be able to use software such as SPSS. This book is designed to introduce you to SPSS so that you can use the program to undertake the statistical analyses you need for your course or research.

In the remainder of this section, we will provide a brief overview of some of the concepts relating to research methods, data and statistical analysis that are important to bear in mind when using SPSS to analyse your data. We refer to many of these in later chapters. (You are probably already familiar with many of them from your lectures on research methods.) Additionally, in each chapter we include an overview of some statistical issues, but this book is not intended to be a statistics reference, and you should also refer to a statistics text for full guidance.

Asking questions and collecting data

The aim of psychology research is to try to better understand human experience and behaviour. This is not an easy task when you think about all of the complexities involved in what it is to be a human being. Just think about all of the different feelings, thoughts and behaviours involved in everyday things like managing your workload, engaging with social or mainstream media, maintaining friendships and relationships… and that barely scratches the surface. There are a multitude of different questions that psychologists might want to ask about human behaviour and experience… What makes someone more likely to experience depression than another? What treatments work best for anxiety? Do people act differently on their own and in public? How does social media affect the way we think or act? Does multitasking reduce productivity? What factors predict criminality? Do we make good eyewitnesses? Why do we like some people and not others?

The different types of questions that we can ask about human behaviour are so wide and varied that psychologists have devised a huge array of different methods that we can use to help us better understand this vast topic. Which method we need to use to answer a particular question depends on the type of question we are asking and the type of data we need to answer it.

Some questions we might ask lend themselves to more qualitative methods of research. For example, if we wanted to explore how people subjectively experience or give meaning to certain events, we might want to collect rich qualitative data through interviews or focus groups to answer our question. Alternatively, other questions may be better explored using quantitative methods. Quantitative methods allow you to measure, score or count the things that you are interested in. This allows you to collect numerical data, identify patterns and make inferences about the relationships between different variables. For example, investigating how the amount of exercise people do relates to a measure of their mental health.

Methods commonly used in psychological research include questionnaire studies, interviews, observation and experiments. Each of these methods can result in the collection of quantitative data suitable for analysis using SPSS. What we do with that data will depend on what questions we are trying to answer, or what hypotheses we are trying to test. This book will focus on some of the quantitative methods commonly used in psychological research.

Levels of measurement

SPSS is designed to aid the analysis of quantitative data, which usually consists of a series of measurements of one or more variables. A variable is simply some quantity that varies and can be measured; so, height, time, weight, sex (male or female) and IQ test score are all examples of variables. A typical data set in psychological research will consist of several variables each measured for a set of different participants or cases.

We use a scale to make the measurements of a variable, and the characteristics of the scale determine the characteristics of the data we collect and ultimately what descriptive and inferential statistics we can legitimately undertake on this data. Many statistics texts written for psychology students describe four different types of scales, or levels of measurement: nominal, ordinal, interval and ratio. When entering your data into SPSS you will need to tell SPSS what types of variable you have. SPSS uses the following terms to classify variable types: nominal, ordinal or scale (’scale’ refers to either interval or ratio variables). We describe them briefly below, along with an illustration of the icons SPSS uses to denote these different levels of measurement.

1. Nominal level

Nominal (also referred to as ‘categorical’) variables are categorised rather than measured in the strictest sense. As SPSS needs us to enter numbers to represent our data, we have to assign a numerical value to the different groups or categories within our variable. For example, we might decide to record the sex of our participants and to enter these data into SPSS by adopting the coding scheme 1 = Male, 2 = Female. Assigning 1 or 2 allows us to differentiate between these two groups of participants, but the numbers themselves are meaningless in this context; these values should not be taken to imply any more than a label (or a name, hence the term ‘nominal’...

Table of contents

• Cover
• Titlepage
• Dedication
• Contents
• Preface
• Acknowledgements
• Chapter 1 Introduction
• Chapter 2 Data entry in SPSS
• Chapter 3 Exploring, cleaning and graphing data in SPSS
• Chapter 4 Data handling
• Chapter 5 Tests of difference for one- and two-sample designs
• Chapter 6 Tests of correlation and bivariate regression
• Chapter 7 Tests for nominal data
• Chapter 8 One-way analysis of variance
• Chapter 9 Factorial analysis of variance
• Chapter 10 Multiple regression
• Chapter 11 Analysis of covariance and multivariate analysis of variance
• Chapter 12 Discriminant analysis and logistic regression
• Chapter 13 Factor analysis, and reliability and dimensionality of scales
• Chapter 14 Using syntax and other useful features of SPSS
• Appendix
• Glossary
• References
• Index
• eCopyright