A Concise Guide to Market Research: The Process, Data, and Methods Using IBM SPSS Statistics
| Author | : | |
| Rating | : | 4.17 (972 Votes) |
| Asin | : | 3642125409 |
| Format Type | : | paperback |
| Number of Pages | : | 350 Pages |
| Publish Date | : | 2013-06-08 |
| Language | : | English |
DESCRIPTION:
Each chapter concludes with a case study that illustrates the process based on real-world data. This includes a discussion of what the outputs mean and how they should be interpreted from a market research perspective. Several mobile tags in the text allow readers to quickly browse related web content using a mobile device. An explanation is provided of the theoretical choices a market researcher has to make with regard to each technique, as well as how these are translated into actions in IBM SPSS Statistics. Using the market research process as a framework, the authors explain how to collect and describe the necessary data and present the most important and frequently used quantitative analysis techniques, such as ANOVA, regression analysis, factor analysis, and cluster analysis.
Four Stars Covers many of the relevant subjects.
Marko Sarstedt is an Assistant Professor of Quantitative Methods in Marketing and Management at the Ludwig-Maximilians-University in Munich, Germany, where he earned his diploma, Master of Business Research and doctorate degree. Marko has served as a consultant for various companies in the nonprofit and profit sectors, including companies in the automotive, telecommunications, and industrial goods sectors. He is currently a Visiting Lecturer at the Euro
Several mobile tags in the text allow readers to quickly browse related web content using a mobile device.. An explanation is provided of the theoretical choices a market researcher has to make with regard to each technique, as well as how these are translated into actions in IBM SPSS Statistics. Using the market research process as a framework, the authors explain how to collect and describe the necessary data and present the most important and frequently used quantitative analysis techniques, such as ANOVA, regression analysis, factor an