This book offers an easily accessible and comprehensive guide to the entire market research process, from asking market research questions to collecting and analyzing data by means of quantitative methods. It is intended for all readers who wish to know more about the market research process, data management, and the most commonly used methods in market research. The book helps readers perform analyses, interpret the results, and make sound statistical decisions using IBM SPSS Statistics. Hypothesis tests, ANOVA, regression analysis, principal component analysis, factor analysis, and cluster analysis, as well as essential descriptive statistics, are covered in detail. Highly engaging and hands-on, the book includes many practical examples, tips, and suggestions that help readers apply and interpret the data analysis methods discussed. The new edition uses IBM SPSS version 25 and offers the following new
As a Professor of Marketing in a Global MBA program, I have read many, many books on Market Research. While there are many more famous and widely used textbooks for Marketing professors to use, this one is by far the best I have ever read and used.
Even for students with a background in Statistics or Statistical methods, this book provides a very clear and detailed discussion of exactly how each of the basic quantitative methods are derived and applied, including all of the assumptions related to the data that has been collected, the actual methods themselves, and all post-hoc tests.
In addition to these very detailed and easy-to-understand discussions, this book also comes with a companion website that includes excellent data files to be imported into SPSS. Students can then walk through each of the examples provided in the book following a step-by-step process, and gain an understanding of the most basic Market Research analysis tools including Hypothesis testing and ANOVA, Regression Analysis (OLS), Factor Analysis and Cluster Analysis.
For anyone looking for an introduction to SPSS for Market Research, this is an outstanding first step before jumping into the more advanced multivariate techniques outlined in Hair et al's "Multivariate Data Analysis".