Statistical Design

In the early stages of product development, choosing an appropriate experimental design is critically important to success. When statistical knowledge is applied, it enables quality to be built into the product and drives good statistics, which allows for highly confident data-driven decisions.
 
One of the goals of an experimental study is to translate the conclusion made on a small scale to larger populations.  Poorly designed studies can result in erroneous conclusions and poor business decisions when translated into real-world settings.  
 
Additionally, the design is integral to balancing the need for quality outcomes against the cost of performing the study.  Items such as sample size, number of replicates and randomization have direct impacts on quality and cost.  Proper designs strike a balance between these two competing issues.
 
We can help obtain the information you need while ensuring your experiment is cost-effective and reproducible so that you can be assured of making sound business decisions based on high-quality data.