Statistical experimental analysis

Statistical experimental analysis techniques from Arkema are applied to explore the relationships among experimental measurements.  Arkema also provides predictive models.

Response surface modeling allows optimization of model factors

Lab experimental efforts often generate multiple measurements, i.e. either replicate measurements or myriad measurements based on statistical design principles. Statistical analysis can then be used to summarize those observations by estimating the average or graphically exploring inner relationships among experimental measurements, e.g. contour plot, ternary plot or scatter plot matrix. Another important statistical analysis tool involves building effective predictive models which enable researchers to estimate physical or chemical properties derived from unfamiliar experimental conditions. Advanced data analytics techniques (e.g response surface modeling or mixture model) also enable scientists to seek optimal experimental conditions given performance constraints.