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1.
Many developments have occurred in the practice of survey sampling and survey methodology in the past 60 years or so. These developments have been partly driven by the emergence of computers and the continuous growth in computer power over the years and partly by the increasingly sophisticated demands from the users of survey data. The paper reviews these developments with a main emphasis on survey sampling issues for the design and analysis of social surveys. Design‐based inference based on probability samples was the predominant approach in the early years, but over time, that predominance has been eroded by the need to employ model‐dependent methods to deal with missing data and to satisfy analysts' demands for survey estimates that cannot be met with design‐based methods. With the continuous decline in response rates that has occurred in recent years, much current research has focused on the use of non‐probability samples and data collected from administrative records and web surveys.  相似文献   

2.
Through building and testing theory, the practice of research animates data for human sense-making about the world. The IS field began in an era when research data was scarce; in today's age of big data, it is now abundant. Yet, IS researchers often enact methodological assumptions developed in a time of data scarcity, and many remain uncertain how to systematically take advantage of new opportunities afforded by big data. How should we adapt our research norms, traditions, and practices to reflect newfound data abundance? How can we leverage the availability of big data to generate cumulative and generalizable knowledge claims that are robust to threats to validity? To date, IS academics have largely welcomed the arrival of big data as an overwhelmingly positive development. A common refrain in the discipline is: more data is great, IS researchers know all about data, and we are a well-positioned discipline to leverage big data in research and teaching. In our opinion, many benefits of big data will be realized only with a thoughtful understanding of the implications of big data availability and, increasingly, a deliberate shift in IS research practices. We advocate for a need to re-visit and extend traditional models that are commonly used to guide much of IS research. Based on our analysis, we propose a research approach that incorporates consideration of big data—and associated implications such as data abundance—into a classic approach to building and testing theory. We close our commentary by discussing the implications of this hybrid approach for the organization, execution, and evaluation of theory-informed research. Our recommendations on how to update one approach to IS research practice may have relevance to all theory-informed researchers who seek to leverage big data.  相似文献   

3.
柏林 《价值工程》2011,30(30):157-158
高职院校的课程设置急需解决的问题包括:课程设置定位不准确、课程体系不完善、专业理论课与实训课课时比例差异大、课程设置追求多而不精等等。解决的对策主要包括:高职院校在课程设置时要以就业为导向,关注地方政府决策,设置贴近、服务于地方经济的特色专业课程。  相似文献   

4.
5.
刘畅 《中国工程师》2014,(12):11-13
随着信息技术的不断发展,数据产生途径越来越广泛,数据量日益增加,人们对于“大数据”的研究越来越深入,但数据的有效性、安全性和可信性方面的保证技术却不是特别完善。本文阐述了“大数据”的相关概念、特征和数据产生的渠道,详细介绍了“大数据”的处理技术以及数据的可信技术。  相似文献   

6.
在医疗体制改革日益深化、医疗卫生事业快速发展的背景下,医院档案种类、载体形式和数量有所增加,医院档案的重要性日益凸显。医院档案在医疗服务和医院各项工作开展中发挥着重要作用,医院管理部门要注重医院档案管理工作,为医院改革和发展提供基础保障。在大数据时代,医院需要树立新型档案管理理念,引进大数据技术,创新并优化现有的医院档案管理模式。论文主要对大数据时代医院档案管理工作的创新及优化进行了分析。  相似文献   

7.
The need for new methods to deal with big data is a common theme in most scientific fields, although its definition tends to vary with the context. Statistical ideas are an essential part of this, and as a partial response, a thematic program on statistical inference, learning and models in big data was held in 2015 in Canada, under the general direction of the Canadian Statistical Sciences Institute, with major funding from, and most activities located at, the Fields Institute for Research in Mathematical Sciences. This paper gives an overview of the topics covered, describing challenges and strategies that seem common to many different areas of application and including some examples of applications to make these challenges and strategies more concrete.  相似文献   

8.
随着信息技术的高速发展,大数据技术呈现出爆发增长并逐渐渗入各行各业。基于信息化的大背景,大数据技术已被越来越多的企事业单位广泛运用,为企业发展带来更多可能性。大数据审计作为一种新型内部审计手段,具备独特的优势,将其运用到企业内部审计中可以较大程度提高内部审计的效率。但是它也为内部审计带来了一定不确定性,进而增加其审计风险。论文就大数据审计在企业内部审计中的应用进行了相关分析,并提出了相应的应对措施。  相似文献   

9.
With the rapid, ongoing expansions in the world of data, we need to devise ways of getting more students much further, much faster. One of the choke points affecting both accessibility to a broad spectrum of students and faster progress is classical statistical inference based on normal theory. In this paper, bootstrap‐based confidence intervals and randomisation tests conveyed through dynamic visualisation are developed as a means of reducing cognitive demands and increasing the speed with which application areas can be opened up. We also discuss conceptual pathways and the design of software developed to enable this approach.  相似文献   

10.
近年来,数据呈指数级增长,人们对数据的利用能力越来越高,特别是近几年兴起的大数据、云计算、人工智能等新兴技术汇集了人类有史以来最多最全的数据,但是如何从数据中发现各种关系与规则,从海量数据中找到更有价值的数据,是人们急需解决的问题。数据挖掘技术是解决这一问题的根本方法,而基于标签的数据挖掘技术是完整刻画描述人物特征的基本方法。  相似文献   

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