Analyzable

Analyzable refers to something that is capable of being analyzed; that is, broken down into its constituent parts to examine their nature, function, and relationships. It implies a degree of complexity or nuance that warrants detailed examination, either qualitatively or quantitatively. The process of analysis aims to reveal patterns, identify key components, and ultimately, gain a deeper understanding of the subject matter. Something analyzable might be a text, a physical system, a set of data, a problem, a situation, or an argument. The degree of analyzability can vary depending on the object, the method of analysis, and the analytical goals.

Analyzable meaning with examples

• The detective considered the crime scene analyzable; every piece of evidence, from the footprints to the blood spatter, held a clue that, when examined carefully, could reveal the culprit. He methodically documented and photographed everything. He employed forensic science to study the blood type. His work, he hoped, would help to solve the mystery and provide justice. This approach showed his ability to determine the crime to be analyzable.
• The professor believed the complex philosophical treatise to be analyzable, despite its abstract concepts. He guided his students through breaking down the text. He examined the arguments and how they were built, identified the author's underlying assumptions, and considered alternative interpretations of the concepts that were presented. He provided examples of the concepts that the students could use to build the concepts in their own minds, which would allow them to comprehend the text in detail.
• The scientist found the new dataset from the experiment to be analyzable, full of patterns waiting to be discovered. They designed several statistical models to identify correlations and dependencies. She meticulously reviewed the data, plotted graphs and charts, and performed various statistical tests. This helped her to generate a better understanding of the processes involved, and led her to publish her findings. The dataset's analyzability spurred the project forward.
• The company's financial performance, including revenue, expenses, and profit margins, was determined to be analyzable. Analysts scrutinized the quarterly reports. They compared them to prior years, identified areas of growth and decline, and assessed risks. They broke down the performance metrics. This allowed the company to optimize its operations and forecast its financial future. The team used this analyzable information to make critical decisions.
• The software bug's behavior proved analyzable with debugging tools and log files. The development team looked for the sequence of events leading up to the error. They reviewed the code, simulated different scenarios, and traced the execution path. They used this information to find the root cause and fix the issue. This led to an improved understanding of the software's architecture. This also showed them how to create a better user experience and make it more effective.