Learn why predictive analytics is the ideal data analytics tool to determine correlations between variables and specific outcomes in CISA exams. Boost your understanding for better exam performance.
Table of Contents
Question
What type of data analytics tool should be used to determine the correlation between the variables and a specific outcome?
A. Descriptive
B. Predictive
C. Prescriptive
D. Diagnostic
Answer
B. Predictive
Explanation
Predictive analytics is a data analytics approach designed to forecast outcomes based on data patterns and relationships between variables. It uses historical data, statistical algorithms, and machine learning to determine how changes in specific variables influence desired outcomes. This method is particularly suitable for understanding correlations, as it not only identifies relationships but also predicts the potential impact of one variable on another.
Why not Descriptive (A)? Descriptive analytics summarizes historical data, focusing on “what happened” without providing insights into variable relationships or future predictions.
Why not Prescriptive (C)? Prescriptive analytics builds upon predictive models to suggest optimal decision-making actions, but it is not used primarily for correlation detection.
Why not Diagnostic (D)? Diagnostic analytics focuses on determining “why something happened,” typically using root cause analysis, without a forward-looking correlation perspective.
Predictive analytics is widely used in scenarios such as risk assessment, financial forecasting, and customer behavior analysis, aligning with the goal of correlating variables to outcomes effectively.
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