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第698行： − + + + + + + + + + + + − − 包括纳特 · 西尔弗在内的许多统计学家都认为，数据科学不是一个新领域，而是统计学的另一个名称。其他人则认为数据科学不同于统计学，因为它专注于数字数据所特有的问题和技术。瓦桑特 · 达尔写道，统计学强调定量数据和描述。相比之下，数据科学研究的是定量和定性的数据。图片) ，并强调预测和行动。哥伦比亚大学的安德鲁 · 格尔曼和数据科学家文森特 · 格兰维尔将统计学描述为数据科学中不重要的部分。 − + 第714行：
第722行： − + − --[[用户:趣木木|趣木木]]（[[用户讨论:趣木木|讨论]]）下为旧版词条中对应部分内容 可进行整合参考并填充 − 飞速增长的职位空缺表明“数据科学”的概念在商业界和学术界可谓一夜蹿红。 − <ref> − Darrow,Barb(May 21, 2015). − [http://fortune.com/2015/05/21/data-science-white-hot/ "Data science is still white hot, but nothing lasts forever"] − .''Fortune.'' Retrieved November 20, 2017. − </ref> − 然而许多持批判态度的学者和新闻记者并没有看出数据科学与[https://en.wikipedia.org/wiki/Statistics 统计学]的区别。吉尔·普莱斯（Gil Press）在[https://en.wikipedia.org/wiki/Forbes 福布斯杂志]上撰文主张数据科学只是一个缺乏清晰定义的[https://en.wikipedia.org/wiki/Buzzword 流行术语]，并且在诸如研究生的课程内容中成了“[https://en.wikipedia.org/wiki/Business_analytics 商业分析]”的简单替代。 − <ref name="GilPress"> − [https://www.forbes.com/sites/gilpress/2013/08/19/data-science-whats-the-half-life-of-a-buzzword/ Data Science: What's The Half-Life Of A Buzzword?]. − Forbes.2013-08-19. − </ref> 第887行：
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→Relationship to statistics与统计学的关系
==Relationship to statistics与统计学的关系==
==Relationship to statistics与统计学的关系==
飞速增长的职位空缺表明“数据科学”的概念在商业界和学术界可谓一夜蹿红。
<ref>
Darrow,Barb(May 21, 2015).
[http://fortune.com/2015/05/21/data-science-white-hot/ "Data science is still white hot, but nothing lasts forever"]
.''Fortune.'' Retrieved November 20, 2017.
</ref>
然而许多持批判态度的学者和新闻记者并没有看出数据科学与[https://en.wikipedia.org/wiki/Statistics 统计学]的区别。吉尔·普莱斯（Gil Press）在[https://en.wikipedia.org/wiki/Forbes 福布斯杂志]上撰文主张数据科学只是一个缺乏清晰定义的[https://en.wikipedia.org/wiki/Buzzword 流行术语]，并且在诸如研究生的课程内容中成了“[https://en.wikipedia.org/wiki/Business_analytics 商业分析]”的简单替代。
<ref name="GilPress">
[https://www.forbes.com/sites/gilpress/2013/08/19/data-science-whats-the-half-life-of-a-buzzword/ Data Science: What's The Half-Life Of A Buzzword?].
Forbes.2013-08-19.
</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>
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. 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.
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.
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.
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.
斯坦福大学教授 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。
在[https://en.wikipedia.org/wiki/American_Statistical_Association 美国统计协会]的联合统计学会议上发表主旨演说后的问答部分，著名应用统计学家[https://en.wikipedia.org/wiki/Nate_Silver 内特·西尔弗]（Nate Silver）说道：“我认为数据科学家对于统计学家是一个富有魅力的词语…统计学是科学的一条分支。数据科学家在某种意义上略显多余，而且人们不应该痛斥统计学家这个词。”
在[https://en.wikipedia.org/wiki/American_Statistical_Association 美国统计协会]的联合统计学会议上发表主旨演说后的问答部分，著名应用统计学家[https://en.wikipedia.org/wiki/Nate_Silver 内特·西尔弗]（Nate Silver）说道：“我认为数据科学家对于统计学家是一个富有魅力的词语…统计学是科学的一条分支。数据科学家在某种意义上略显多余，而且人们不应该痛斥统计学家这个词。”
<ref name="NateSilver">
<ref name="NateSilver">
诚如多诺霍所言蔽之：“数据科学的范围和影响在今后数十年会继续扩充，科研数据和有关科学本身的数据将无处不在、俯拾即是。”
诚如多诺霍所言蔽之：“数据科学的范围和影响在今后数十年会继续扩充，科研数据和有关科学本身的数据将无处不在、俯拾即是。”
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<ref name=":2" />
==References==
==References==