Abstract
PREFACE Read this bit. It will save you time, because it explains the kind of book this is and, perhaps more importantly, the kind of book that it isn't, which will make it easier for you to decide whether you will benefit from reading it or whether you would get more out of doing something else instead. Right at the beginning, we want to make clear that this is not the book for you if you want to cover the world of statistics in a rigorous and exhaustive manner. The guiding principle of this book is the need to know. If you are unlikely to need a particular statistical method in order to analyse the data that you have collected for your project or dissertation, then you won't find any mention of it here. There are enough books on statistics out there, which range from relatively simple introductions to advanced mathematical expositions. This one has a different purpose. It concentrates on what you need for success in your assignment, project or dissertation, and ignores the minor roads and byways that the person very interested in statistics would be pleased to travel. As the textbooks (which, strictly speaking, this isn't) put it, by the end of this book, you will be able to choose and use an appropriate and effective statistical technique that will allow you to analyse your data and write about your results and findings convincingly. In a sense, this is the book that we wish we could have used during our own studies. We both spent far too long in a fog of not understanding which statistics to use, when we should be using them and why we should be using them. As a consequence, the book concentrates on particular statistical tests and their three Ws – what, why, and when – and mainly ignores the details of how to calculate them, leaving this area for the books that not only explain the mathematics behind the techniques, but also how to use statistical software to analyse your data. This is not the book for you if you want what any normal, self-respecting textbook currently supplies: self-check and review questions and tests, case studies, practice exercises, worked examples, activities, boxes for pauses for thought or reflection, lists of learning outcomes or a companion website. Nor will it satisfy you, if you want to know all about the theory behind the statistical calculations of the methods you use. Instead, the book is intended for you if you are undertaking a social science or business and management assignment, project or dissertation as part of an undergraduate or masters qualification. It is designed to help you choose the graphs and statistics that are suitable for your data, and having got some results from your computer, to understand what they actually tell you. The chapters that follow set out to explain the three Ws that you need so that you can produce a successful assignment, project or a dissertation. However, from now on we will just refer to any of these as a ‘project’ as it is less clumsy. Chapter 1 deals with why you can't avoid using statistics in analysing your data, whether this is qualitative or quantitative, and what using statistics can do for your research. Chapter 2 explains the language of statistics so that you understand what the various terms used for statistical techniques and results mean. Chapter 3 clarifies why, if you are using primary data, you need to link the creation of your questionnaire or interview to your analysis plans, and when to do this. Chapter 4 deals with using tables and charts to present your data so that you, and your reader (or examiner) find them easy to understand. Chapter 5 explains the statistics used to describe data and Chapter 6 deals with the statistics used to infer differences and relationships. Finally, Chapter 7 briefly considers what next. The book provides three Appendices; the first provides the types of questions and statements you are likely to use in your project, and the data types associated with them, the second appendix discusses main statistical software that you could use to do your stats calculations for you, and the third provides a table of the alphabet of statistics used in this book. At the end of the book, we give you a glossary of the statistical terms that have been used throughout the book, so that you have them all in one place. Many statistics books divide statistical tests between parametric or non-parametric tests, or they deal with the available tests in terms of their increasing rigour. The main divisions of this book are based on how you will be using statistics: displaying data, describing data and inferring differences or relationships. Explanations of terms such as parametric, non-parametric and rigour are fitted into these divisions, the term which is being explained being emboldened. In writing the book, it was not our intention to give you the information you need to understand the whole field of statistics. Instead, we provide you with the fundamental ideas and the most commonly used techniques that you will need to organise, and then make sense of, your data. Whilst there are no mathematical proofs of the techniques discussed, there is a discussion of the rationale for the chosen statistics. There are very many methods that can be used to analyse your data, many of them with strange names: Chi square, Kolmogorov-Smirnov, paired t-test. You are quite right to feel daunted and confused about which are appropriate for your needs. Which is where this book comes in. 1. It will deal with statistics for your project on a need-to-know basis. If a statistic is interesting, but too sophisticated for your purposes, it might sometimes be mentioned, but is otherwise ignored. 2. What you will therefore have is an explanation and presentation of those statistical activities that are sufficient for you to deal with your data, and to come up with the answers to your questions (and to get your qualification). A FINAL COMMENT We wrote this book because we want to end the fear and anxiety about statistics that we and our students endured, and that many students still endure, and to show you that you can succeed in statistical analysis of your data. There is no doubt that learning statistics takes an investment of time and effort, but this book provides you with the means both to save some of that time and effort, and also to enjoy your analysis without fear of failure. If, after reading this book, you can understand the statistical analysis sections of the journal articles you read, and if you have found out how to make statistics work for you, the book will have accomplished what we set out to provide for you. If you have suggestions on how to improve the book to even better meet your needs, please let us know. Reva Berman Brown Mark NK Saunders