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Marketing Research, by Donald R. Lehmann, Sunil Gupta, Joel H. Steckel
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For upper-level undergraduate/graduate-level courses in Marketing Research. These renowned members of the academic community offer a textbook that was written with the intent of being more instructive and less encyclopedic than its competitors. Marketing Research tells a story and is more practical in terms of real world applications. It provides students with a complete analysis of benefits and pitfalls of various research methods and contains state-of-the-art and up-to-date coverage of marketing research related topics. It offers the professor and student up-to-date coverage of the latest marketing research issues.
- Sales Rank: #1680953 in Books
- Published on: 1997-12-15
- Original language: English
- Number of items: 1
- Dimensions: 9.09" h x 1.52" w x 7.51" l, 1.10 pounds
- Binding: Paperback
- 950 pages
Most helpful customer reviews
21 of 22 people found the following review helpful.
Inside marketing research
By Dorival MMachado
I received this book as gift from a fellow statistician about two years ago, since then it was never more than three steps away from the place I was working. I continued to search for other Marketing Research titles, from Amazon and other Web dealers to Chicago libraries and bookstores, I didn't find any other title wich such a clear and up-to-date approach. Of course there other respectfull titles, as ESOMAR's Handbook of Marketing and Opinion Research, but the last is, as the name says, a handbook, presenting all techniques and where to find them (it's perfect if you want to use something and don't know where to look for the article) but it doesn't get into applying the stuff. That's the MARKETING RESEARCH major merit, it get's into applied statistics - it describes a technic and explain in wich analytical context it would fit better. Even in the last chapter: "Additional Data Analysis Techniques" - that was dealing with improvements that had just been added to statistical programs as SPSS, like Segmentation Trees, Neural Networks and Structural Equation Modeling, they were able to discuss each technique in a few pages, without being superficial. Last, but not least, the book also presents lots of output examples, full featured in SPSS, SAS and other major statistical programs.
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