Statistics in Psychology Using R and SPSS

Dieter Rasch, Klaus Kubinger, Takuya Yanagida

• Publisher: Wiley
• Year: 2011
• ISBN:
  9781119952022
• Edition: 1
• Topic: Psychology
• Subtopic: Research & Methodology in Psychology
• Index: Psychology

Statistics in Psychology covers all statistical methods needed in education and research in psychology. This book looks at research questions when planning data sampling, that is to design the intended study and to calculate the sample sizes in advance. In other words, no analysis applies if the minimum size is not determined in order to fulfil certain precision requirements.

The book looks at the process of empirical research into the following seven stages:

• Formulation of the problem
• Stipulation of the precision requirements
• Selecting the statistical model for the planning and analysis
• The (optimal) design of the experiment or survey
• Performing the experiment or the survey
• Statistical analysis of the observed results
• Interpretation of the results.

Part I

INTRODUCTION

This textbook requires a multi-layered view of ‘statistics in psychology’. Within the Bachelor's curriculum it is only possible to demonstrate the correct use of the most important techniques. For the Master's curriculum, however, a certain understanding of these methods is necessary: for the Master's thesis, where usually a scientific question has to be worked on single-handed but under supervision, the student has to refer to statistical analyses in literature concerning the topic, and if necessary to improve the choice of the method used for analysis. For doctoral studies, understanding alone is not enough; a willingness to reflect critically on the statistical methods must be developed. The statistical methods used in the doctoral thesis, which means the entrance to a scientific career, have to be oriented on state-of-the-art methodological developments; the ability to follow these developments requires profound knowledge as well as the aptitude to evaluate new statistical methods regarding their shortcomings.

Since even for doctoral students a repetition of the basics of statistics on an elementary level is often useful, with this book they can be picked up individually where their powers of recollection end – if necessary at the beginning of the Bachelor's education. And in contrast, Bachelor's students are often interested in the contents of a Master's curriculum or where the textbook leads. They can get a taste of that now.

Finally, even lecturers will find something new in this textbook; according to our experience ‘statistics for psychologists’ is not taught by professional statisticians but by psychologists, mostly by those at the beginning of their academic careers; anecdotes may at least help them didactically. These casual reflections can of course also be academically amusing for students.

Accordingly, the three to four mentioned target groups are guided through the book using distinctive design elements.

The running text, without special accentuation, is directed at all target groups. It is information essential for the further study of the textbook and its practical use – as is this introduction before Chapter 1. Also the terminology used in the book has to be conveyed in a standardized way. Finally, some contents, which should be familiar to doctoral students, are nevertheless aimed at all target groups because we think that repetition is useful.

Moreover, special symbols and labels on the outer edge of some pages signal the target group that the information is aimed at. Target groups other than the ones indicated with the symbol can skip these passages without being in danger of missing the respective educational aim.

The symbol

indicates that the material in these passages is aimed particularly at Bachelor's students since it deals only with the Ability to Use. The symbol

on the outer edge indicates that here the reader finds an explanation of the underlying methods, without using a mathematical derivation that is too detailed; this is about Understanding. The symbol

on the outer edge of the page announces that the shortcomings of the method will be discussed and that common misuses will be indicated; this is about Critical Reflection. Finally, the note For Lecturers signals didactically useful observations, entailing understanding of the respective topic in a very demonstrative way.

In order to bring all target groups together again, occasionally a Summary is given. At the beginning of every chapter a short description of its contents is given.

1

Concept of the book

In this chapter, the structure of the book and accordingly the didactic concept are presented to the reader. Moreover, we outline an example that will be used in several chapters in order to demonstrate the analytical methods described there.

In six sections this book conveys the methods of the scientific discipline of ‘statistics’ that are relevant for studies in psychology:

I. Introduction (Chapters 1 to 4)

II. Descriptive statistics (Chapter 5)

III. Inferential statistics for a single character (Chapters 6 to 10)

IV. Descriptive and inferential statistics for two characters (Chapter 11)

V. Inferential statistics for more than two characters (Chapters 12 and 13)

VI. Theory building statistical procedures (Chapters 14 and 15).

Chapter 1 explains the concept underlying our presentation of the methods. Furthermore an empirical example that will be used as an illustration in various parts of the book is provided.

Chapter 2 will demonstrate that quantifying and measuring in psychology is not only possible but also very useful. In addition we would like to give the reader an understanding of the strategy of gaining knowledge in psychology as a science; the approach however is similar to other scientific fields, which is why this book can be used in other fields too.

In Chapter 3 we will address the issue that empirical research is performed in several steps. For all scientific questions that are supposed to be answered by the study (as diverse as they might be regarding contents), exact planning, careful collecting of data, and adequate analysis are always needed.

Within this context we wish the reader to realize that a study does not always have to include all the people that the research question is directed at. Out of practical reasons, most of the time only part of the group of interest can be examined; this part is usually called sample, whereas the group of interest is called the population. Chance plays an important role here. It will be shown that we have to make probability statements for the results of the statistical analysis; the probability calculus used for this is only valid for events for whose occurrence (or non-occurrence) chance is responsible. For example, a certain event might be that a specific person is part of the study in question. We will treat this topic in Chapter 4, as well as in Chapter 7. Since ‘chance’ often has a different meaning in everyday use as opposed to its general meaning in statistics and therefore in this book, we will point out at this early stage that a random event is not necessarily a rare or unanticipated event.

Finally, if data concerning one or more person(s) or character(s) that are of interest have been gathered within the framework of the study, they have to be processed statistically. The data in their totality are too unmanageable to be able to draw conclusions from them that are relevant for answering the scientific question. Therefore, special methods of data compression are necessary. We will deal with this issue in Chapter 5. The decision of which one of these methods is applicable or most appropriate is substantially based on the type of data: for example, whether they have been derived from physical measurements or whether they can only express greater/less than and equal to relations. In the latter case it is important to use methods that have been specially developed for this type of data.

Mathematical-statistical concepts are needed, especially for the generalization of study results; these will be introduced in Chapter 6. For readers who are unpracticed in the use of formulas, this chapter is surely difficult, although we try to formulate as simply as possible.

If the generalization of the study results is the aim, then a prerequisite for the use of appropriate methods is that the collected samples are random samples; information on this topic can be found in Chap...

Table of contents

• Cover
• Title Page
• Copyright
• Preface
• Acknowledgments
• Part I: INTRODUCTION
• Part II: DESCRIPTIVE STATISTICS
• Part III: INFERENTIAL STATISTICS FOR ONE CHARACTER
• Part IV: DESCRIPTIVE AND INFERENTIAL STATISTICS FOR TWO CHARACTERS
• Part V: INFERENTIAL STATISTICS FOR MORE THAN TWO CHARACTERS
• Part VI: MODEL GENERATION AND THEORY-GENERATING PROCEDURES
• Appendix A: Data input
• Appendix B: Tables
• Appendix C: Symbols and notation
• References
• Index