When connecting a type node to an Excel source node, what measurement level can be observed if the data is partially instantiated?

When connecting a type node to an Excel source node, the most appropriate measurement level to observe for partially instantiated data is categorical. Categorical data refers to variables that can be divided into distinct categories but do not have a specific order or ranking among them.

In cases where data is partially instantiated, you might have a situation where some observations fall into specific categories, which is characteristic of categorical variables. Since categorical data allows for the classification of information into groups, it effectively accommodates scenarios where not all data points are fully populated.

This contrasts with typeless data, which does not correspond to a specific category or measurement level; nominal data which lacks intrinsic order but does not fit the specifics of being partially instantiated; and flag data which typically denotes binary conditions rather than categorization. Thus, categorical is the most fitting level of measurement in this context, as it emphasizes the capability to group the data into identifiable sets without requiring full instantiation.