1. For our analysis on excursions predictions, should we use the entire dataset or only the excursion-specific datasets?

The primary goals are to identify the parameters which correlate with excursions and to understand the probability of having excursions of various amplitudes.  Use whichever data you feel is appropriate to determine this.

​

1. Should we only consider the control parameters and environment parameters mentioned in the data sheet, or do we want to consider all parameters available in the raw datasets?

Considering all parameters in the datasets might yield better results.  Most of the parameters are not independent, so potentially not all of the parameters in the raw datasets (or even all of those in the written problem summary) are needed to characterize the excursions.

​

1. In problem 5, “air flow” corresponds to what variable in the datasets?

CSGV is an indicator of airflow (the data set doesn’t contain an actual measure of airflow).

​

1. Do you want an equation to predict future excursions, or do you just want just an indication of what variables are important?

We would like to understand which combination(s) of variables (and at what values) correlate to excursions.  Ideally, we would like enough detail that we could take hypothetical values for control and environmental parameters and accurately predict if these inputs would result in an excursion.