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Data analysis can be categorized into quantitative and qualitative analysis. For instance, when measuring a person's fever, temperature readings (e.g., 100°F or 102°F) exemplify quantitative analysis, providing numerical data essential for diagnosis. However, measuring temperature alone does not reveal the underlying cause of the illness. To understand the cause—such as stomach pain or nausea—a doctor must assess other symptoms, which represents qualitative analysis. Both types of analysis are crucial for patient treatment, and the same principles apply to credit analysis, highlighting the importance of using both approaches for comprehensive understanding.