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第497行： + − − Many statisticians, including Nate Silver, have argued that data science is not a new field, but rather another name for statistics. Others argue that data science is distinct from statistics because it focuses on problems and techniques unique to digital data. Vasant Dhar writes that statistics emphasizes quantitative data and description. In contrast, data science deals with quantitative and qualitative data (e.g. images) and emphasizes prediction and action. Andrew Gelman of Columbia University and data scientist Vincent Granville have described statistics as a nonessential part of data science. − 第507行：
第505行： − − Stanford professor David Donoho writes that data science is not distinguished from statistics by the size of datasets or use of computing, and that many graduate programs misleadingly advertise their analytics and statistics training as the essence of a data science program. He describes data science as an applied field growing out of traditional statistics.
→Relationship to statistics与统计学的关系
Forbes.2013-08-19.
Forbes.2013-08-19.
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Many statisticians, including [[Nate Silver]], have argued that data science is not a new field, but rather another name for statistics.<ref>{{Cite web|url=https://www.statisticsviews.com/details/feature/5133141/Nate-Silver-What-I-need-from-statisticians.html|title=Nate Silver: What I need from statisticians - Statistics Views|website=www.statisticsviews.com|access-date=2020-04-03}}</ref> Others argue that data science is distinct from statistics because it focuses on problems and techniques unique to digital data.<ref>{{Cite web|url=http://priceonomics.com/whats-the-difference-between-data-science-and/|title=What's the Difference Between Data Science and Statistics?|website=Priceonomics|language=en|access-date=2020-04-03}}</ref> [[Vasant Dhar]] writes that statistics emphasizes quantitative data and description. In contrast, data science deals with quantitative and qualitative data (e.g. images) and emphasizes prediction and action.<ref>{{Cite journal|last=DharVasant|date=2013-12-01|title=Data science and prediction|journal=Communications of the ACM|volume=56|issue=12|pages=64–73|language=EN|doi=10.1145/2500499}}</ref> [[Andrew Gelman]] of Columbia University and data scientist Vincent Granville have described statistics as a nonessential part of data science.<ref>{{Cite web|url=https://statmodeling.stat.columbia.edu/2013/11/14/statistics-least-important-part-data-science/|title=Statistics is the least important part of data science « Statistical Modeling, Causal Inference, and Social Science|website=statmodeling.stat.columbia.edu|access-date=2020-04-03}}</ref><ref>{{Cite web|url=https://www.datasciencecentral.com/profiles/blogs/data-science-without-statistics-is-possible-even-desirable|title=Data science without statistics is possible, even desirable|last=Posted by Vincent Granville on December 8|first=2014 at 5:00pm|last2=Blog|first2=View|website=www.datasciencecentral.com|language=en|access-date=2020-04-03}}</ref>
Many statisticians, including [[Nate Silver]], have argued that data science is not a new field, but rather another name for statistics.<ref>{{Cite web|url=https://www.statisticsviews.com/details/feature/5133141/Nate-Silver-What-I-need-from-statisticians.html|title=Nate Silver: What I need from statisticians - Statistics Views|website=www.statisticsviews.com|access-date=2020-04-03}}</ref> Others argue that data science is distinct from statistics because it focuses on problems and techniques unique to digital data.<ref>{{Cite web|url=http://priceonomics.com/whats-the-difference-between-data-science-and/|title=What's the Difference Between Data Science and Statistics?|website=Priceonomics|language=en|access-date=2020-04-03}}</ref> [[Vasant Dhar]] writes that statistics emphasizes quantitative data and description. In contrast, data science deals with quantitative and qualitative data (e.g. images) and emphasizes prediction and action.<ref>{{Cite journal|last=DharVasant|date=2013-12-01|title=Data science and prediction|journal=Communications of the ACM|volume=56|issue=12|pages=64–73|language=EN|doi=10.1145/2500499}}</ref> [[Andrew Gelman]] of Columbia University and data scientist Vincent Granville have described statistics as a nonessential part of data science.<ref>{{Cite web|url=https://statmodeling.stat.columbia.edu/2013/11/14/statistics-least-important-part-data-science/|title=Statistics is the least important part of data science « Statistical Modeling, Causal Inference, and Social Science|website=statmodeling.stat.columbia.edu|access-date=2020-04-03}}</ref><ref>{{Cite web|url=https://www.datasciencecentral.com/profiles/blogs/data-science-without-statistics-is-possible-even-desirable|title=Data science without statistics is possible, even desirable|last=Posted by Vincent Granville on December 8|first=2014 at 5:00pm|last2=Blog|first2=View|website=www.datasciencecentral.com|language=en|access-date=2020-04-03}}</ref>
包括'''纳特•西尔弗 Nate Silver''' 在内的许多统计学家都认为，数据科学不是一个新领域，而是统计的另一个名称。其他人则认为，数据科学与统计学不同，因为它关注的是数字数据特有的问题和技术。'''瓦桑特·达尔 Vasant Dhar'''写道，统计学强调定量数据和描述。相比之下，数据科学处理定量和定性数据(如图像)，强调预测和行动。哥伦比亚大学的'''安德鲁·格尔曼 Andrew Gelman''' 和数据科学家'''文森特·格兰维尔 Vincent Granville'''将统计描述为数据科学中一个不重要的部分。
包括'''纳特•西尔弗 Nate Silver''' 在内的许多统计学家都认为，数据科学不是一个新领域，而是统计的另一个名称。其他人则认为，数据科学与统计学不同，因为它关注的是数字数据特有的问题和技术。'''瓦桑特·达尔 Vasant Dhar'''写道，统计学强调定量数据和描述。相比之下，数据科学处理定量和定性数据(如图像)，强调预测和行动。哥伦比亚大学的'''安德鲁·格尔曼 Andrew Gelman''' 和数据科学家'''文森特·格兰维尔 Vincent Granville'''将统计描述为数据科学中一个不重要的部分。
Stanford professor [[David Donoho]] writes that data science is not distinguished from statistics by the size of datasets or use of computing, and that many graduate programs misleadingly advertise their analytics and statistics training as the essence of a data science program. He describes data science as an applied field growing out of traditional statistics.<ref name=":7" />
Stanford professor [[David Donoho]] writes that data science is not distinguished from statistics by the size of datasets or use of computing, and that many graduate programs misleadingly advertise their analytics and statistics training as the essence of a data science program. He describes data science as an applied field growing out of traditional statistics.<ref name=":7" />
斯坦福大学教授 '''大卫·林奇 David Donoho''' 写道，数据科学与统计学之间并不存在数据集的大小或计算机的使用，许多研究生课程错误地宣传他们的分析学和统计学训练是数据科学课程的本质。他把数据科学描述为从传统统计学中发展出来的一个应用领域。
斯坦福大学教授 '''大卫·林奇 David Donoho''' 写道，数据科学与统计学之间并不存在数据集的大小或计算机的使用，许多研究生课程错误地宣传他们的分析学和统计学训练是数据科学课程的本质。他把数据科学描述为从传统统计学中发展出来的一个应用领域。