I have started two new projects, a book looking at the how the "Public Sector can use Social Media to Engage and Consult", and a book on "Statistics for Market Researchers". Given the success I had in using a collaborative approach in writing The Handbook of Online and Social Media Research, I intend to adopt a similar approach with both of these books.
Initially, I shall be posting extracts here, as the project expands I shall adopt a more structure approach.
The first posting here set out the scope and vision for the book Statistics for Market Researchers.
This book is written specifically for market researchers. There are books on statistics for a wide range of purposes, for example for scientists, for managers, for biologists, for educational psychologists, and many more. This raises the questions why? Surely, you might think, there is only one set of statistics? However, there are very good reasons for a book to be specific to a discipline and amongst the key benefits perhaps the two most important are:
• The many, many statistical techniques and tools, too many for most people to become familiar with and almost nobody can become skilled at all the possible options, so a specific discipline tends to focus on a sub-set of tools and techniques that match the needs of that discipline and which match the data that is typically available to practitioners in the field.
• In the ‘real’ world most practitioners have to make compromises between theory and practice. These compromises tend to vary by discipline, typically on pragmatic grounds. For example, quite often academic research the compromise is on the selection of research subjects (for example the large number of psychology and behavioural economics studies that use students as the subjects). Different compromises result in different techniques being selected and different rules of thumb being adopted.
In the light to of the views expressed above this book seeks to describe just those statistical and analytical techniques used by market researchers, and where appropriate flagging up where the technique is a mainstream approach (such factor analysis and cluster analysis) or only rarely used in market (such as the ANOVA).
Structure of the descriptions
For each of the techniques and tools covered in this book a template approach has been adopted, based on the following headings:
- What What is the technique seeking to do and (in an over-simplified way) how does it do it?
- Why What sort of problems might are resea4rchers using these technique typically seeking to solve with this technique?
- How Notes on how to set about using this technique?• Strengths and Weaknesses? A review of what the technique is good for, bad for.
- Theory What does the technique require in theory and how should its results be interpreted in theory.
- Practice How the technique is typically used, what compromises are commonly made by market researchers?
- Tips Suggestions about how to make the technique more likely to work, easier to use, and readily explained.
Structure of the Book
The book is divided into several Parts, covering:
- Data. This part looks at the sort of data that are typically available to market researchers, such as proportions, counts, and scales, along with the descriptive statistics that are used with this sort of data.
- Describing and Testing. This part looks at the ways that data are described, investigated, and tested by market researchers.
- Analysis. This part looks at the various techniques used by market researchers to analyse data, for example factor analysis and cluster analysis.
- Designing Fieldwork.This part of the book reviews the link between the problems a market researcher is seeking solve, the techniques the researcher plans to use, and the implications for the type of data that should be collected.
- From Problems to Techniques. Most of the book looks at the statistical tools and techniques available to market researchers and shows how they can be applied to research problems. However, this section turns that process around and explores typical research problems and describes the techniques that are suitable to be used in solving them.
Caveat emptor is a Latin phrase that means buyer beware. In the context of this book what it means is that the author is NOT saying that it is OK to break the rules, is NOT saying that mathematical assumptions can safely be disregarded, and is NOT saying that the techniques described in this book will reveal the truth. The book tends to concentrate not on ‘best practice’, but on typical practice. If you want know and understand best practice, it is probably necessary to enrol on a suitable course and learn about the underlying theory and mathematics.