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Assumptions in statistics are crucial because they underpin the validity of statistical models and analyses used in daily life. They help define the conditions under which data can be interpreted accurately, guiding decision-making in areas like healthcare, economics, and Social Sciences. Incorrect assumptions can lead to misleading conclusions and poor decisions, emphasizing the need for careful consideration of these foundational elements in any statistical analysis. Ultimately, understanding assumptions enables individuals and organizations to make informed choices based on reliable data.

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