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Statisticians have varying opinions about data science, influenced by factors such as their background, expertise, and professional interests. Some statisticians embrace data science as an interdisciplinary field that complements traditional statistical methods with techniques from computer science, machine learning, and domain expertise. They see data science as an opportunity to expand the scope of statistical analysis, address complex real-world problems, and extract insights from diverse types of data.
However, some statisticians may express concerns about the perceived dominance of machine learning and computational techniques in data science, which they feel may overshadow the importance of rigorous statistical principles and theoretical foundations. They may advocate for maintaining a balance between traditional statistical methods and newer computational approaches within the data science discipline.
Overall, statisticians recognize the value of data science in advancing knowledge, solving practical problems, and driving innovation but may have differing perspectives on its methodologies, emphasis, and relationship to traditional statistics.
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