The phrase "analysis that could" is correct and usable in written English.
It can be used when discussing potential outcomes or interpretations of an analysis in various contexts, such as academic writing or reports.
Example: "The analysis that could reveal underlying trends in the data is crucial for our research."
Alternatives: "examination that might" or "study that may".
Indeed, we have reached a level of "meta-ness" in analysis that could make one dizzy.
My research group has developed tools and safety analysis that could be a valuable input to this process.
Assessing the interactions between the measures is a separate piece of analysis that could affect the total.
It would have been preventable with an ethical impact analysis that could have considered the discriminatory impact of simple, algorithmic decisions.
Although we may be onto something here (the posse approach to sociometric stardom?), Gibson is serious about the kind of analysis that could be achieved.
Should Facebook, Twitter and RIM give the police privileged access to their networks at times of civil disorder, or help law enforcement by providing more real-time data analysis that could help the police prevent rioting?
At the same time he didn't take himself too seriously as a writer and had an endearing habit of alerting the reader to boring chunks of historical and political analysis that could be skipped.
While Mr. Purdum has done a superb job stitching the reports together into a coherent narrative, he has not provided much of the analysis that could have put this story into its proper context.
We discuss aspects of epidemiological and molecular study design and analysis that could be employed to strengthen the level of human evidence to infer causality.
This interaction is compatible with the existence of two distinct processes working in parallel, namely automatic identification and structural analysis, that could either interfere or act together for the detection of differences.
This paper presents a framework for the use of farm-level and landscape-scale models and data to provide analysis that could be used in NextGen knowledge products, such as mobile applications or personal computer data analysis and visualization software.
