| ||Format||Pages||Price|| |
|PDF (196K)||13||$25||  ADD TO CART|
|Complete Source PDF (1.6M)||88||$55||  ADD TO CART|
Cite this document
Research guidance testing can use experimental design and statistical analysis to assure Product Development of success with the consumers. There are two testing approaches for developing a product: the “best shot” approach and the multiple-sample experimental design approach. The advantages of the multiple-sample design approach and its benefits are presented using a series of research guidance tests on salad dressing as examples. The use of sample presentation designs and experimental designs (screening designs, optimizing designs, and factorial designs) enables us to obtain the maximum amount of information from our tests. In addition to the discussion of these designs, data analysis techniques for both normal theory and nonparametric procedures are considered. While multiple-sample experimental designs generally require more planning and initial capital investment than the “best shot” approach, the information gained and total cost savings are greater.
experimental design, balanced incomplete block design, data transformation, hedonic scale, preference, mixture experiment, split-plot design, screening design, optimization, factorial design, regression analyses, nonparametric analyses
Statistician, Thomas J. Lipton, Inc., Englewood Cliffs, NJ