The analytical process

The next phase in the investigative process is the analysis or logical reasoning, which necessitates going beyond just the mere the facts. The disciplined approach to analysis necessitates the maximum amount of data to be considered at the time of integration to decide on its significance. Eliminating data at the start of the process can easily lead us to the significance of a vital piece of evidence that may otherwise be overlooked. Which can lead to incorrect analysis, which could eventually jeopardize an enquiry?

Analysis often identifies additional projects that are tangential to the original one. Some time ago, it was common to carry out these projects at the same time and in conjunction with the main one. This approach led to scattering of resources, interruptions and in general lowering the quality of the final product(s). Through lessons learned, it has now become acknowledged that analytical projects should be carried out sequentially, one at a time, or by independent teams of analysts.

A premise\hypotheses in “inference development” is used for the identification of facts or fragments of information\data that goes together to make a particular point. A premise\hypotheses is the first and significant stage in the true process of data analysis as against data description. Understanding how premise\hypotheses are identified is crucial
to developing inferences.

Premise\hypotheses are the closest relationship to the described information, and consequently are the most objective and accurate representation of data. For any given set of premise\hypotheses derived from a particular set of information, the premise\hypotheses may be joined in different ways to suggest different inferences.

THE INTELLIGENCE PROCESS

There are four types of inferences:
1. Hypothesis—a tentative explanation, a theory that requires additional information for confirmation or rejection.
2. Prediction—an inference about something that will happen in the future.
3. Estimation—an inference made about the whole from a sample, typically quantitative in nature.
4. Conclusion—an explanation that is well supported. It should be noted that all inferences require testing in some manner before they can be accepted
as fact.