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if we want to explore longitudinal cause and effect relationships, which type of analytics is appropriate

User Mihir Dave
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Final answer:

Regression analysis is appropriate for exploring longitudinal cause and effect relationships. It helps determine the strength and direction of causality between variables.

Step-by-step explanation:

When exploring longitudinal cause and effect relationships, it is appropriate to use regression analysis. Regression analysis is a statistical technique that helps determine the strength and direction of causality between variables. It can be used to analyze the impact of multiple independent variables on a dependent variable over time. For example, in a study examining the effect of fast food consumption on obesity rates, regression analysis could also consider factors like ethnicity, income, and access to parks.

User Clement M
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