Developing or improving products, streamlining a production process or comparing the performance of alternative formulations, very often represent core issues for researchers and managers (Box, G. E. P. and Woodall, W. H., 2012; Hoerl, R., Snee, R., 2010; Jensen, W. et al., 2012).
In this context, many questions can be viewed as problems of comparison of synthetic measures, such as mean values or proportions, with expected target values, or of comparison among different configurations of the investigated product. Furthermore, statistical modeling and optimization techniques find a vast number of applications when the objective is to study in depth how one or more desirable product characteristics are related to a set of process variables and how to set these variables in order to optimize product performance.
In this chapter, four different case studies are presented to cover several concrete situations that experimenters can encounter in the development and optimization phases.
The first example refers to the development of a new sore throat medication, where the research team aims to check the following issues:
- The mean content of an anesthetic ingredient is not different to the target value of 2.4 mg.
- The percentage of lozenges with total weight greater than 2.85 mg is less than 40%.
One‐sample inferential technique allows us to compare sample means or proportions to target values.
In the second case study, two different ...