论网络时代统计发展的八大趋势

网络时代是一个信息化的时代。统计信息作为经济信息的主体,正面临互联网迅猛发展给传统统计带来的严峻挑战,同时,也给传统统计带来新的发展空间。本文旨在论述网络时代统计发展的八大趋势。     

重塑统计文化 打造统计核心竞争力

统计作为一门实务性很强的科学，其发展历来与“社会经济制度、国家政权性质、民族历史传统和科学技术水平紧密相关。当前我国政治、经济、文化等诸领域呈现许多新的特征和变化，统计思想、统计方法制度及统计的开放性等受到强有力的挑战，统计革新成为当前我国统计发展最紧迫的问题，而统计革新又不能仅限于对某些统计理论、     

加入WTO与我国的统计教育改革

加入WTO以后我国统计教育面临着巨大的挑战。本文通过对我国现行统计教育中存在的问题进行探讨,进一步提出几点应对挑战的改革思路。     

水利统计如何适应经济发展的客观要求

随着经济全球化的步步深入,水利统计工作面临着巨大的挑战:一是面临着统计队伍素质难以适应的挑战.目前,统计人员开始由传统的简单统计分析,转向了利用现代化手段,独立地进行统计调查、统计报告、统计监督,这对统计人员的知识结构、工作方法、微机操作等方面都提出了较高的要求.……     

依数据进行统计建模的三个基本分析层次

统计研究的原动力大致上可以归结为四个基本类型,即理论驱动、应用驱动、问题驱动和数据驱动。这些驱动力导致了统计研究所采用的范式各有不同,如理论推导、案例分析、数据模拟等,几乎每一种研究范式都包含了统计建模的内容和要求。本文提出统计建模的三个基本分析层次,即数据呈现、自由拟合与约束效应分析,并且尝试评述了各层级之间的递进关系,试图定义出一个从实践角度判断统计模型优劣的简单标准。     

新形势下经管类专业统计课教学改革研究

随着中国改革开放的进一步深化,统计的应用得到了前所未有的重视。本文将1999年以前的教学模式界定为传统教学模式,分析了在传统模式下,社会经济统计学教学存在的诸多问题,并分析新形势下对本科教学提出的新要求和新挑战,文章重点探讨了在新形势下改革分配经管类专业统计教学内容、手段和方法的基本思路和具体做法。     

统计模型应用面临的挑战与转型

<正>统计量化测度和统计模型是统计学的核心,从统计学诞生之日起,其生命力就在于能够对现实进行量化测度和用统计模型分析实际问题。没有量化测度,经济统计学就不会相对独立于经济学。没有模型应用,数理统计学就还是数学,就不会从数学中分离出来。目前社会已经发展到网络和大数据时代,传统和现代的统计模型无论在方法上还是在应用中都已经受到了挑战。     

企业统计如何走出困境

随着社会主义市场的逐步形成和完善,大中型企业也在积极寻找对策,加紧转换机制,接受市场公开竞争的挑战,但是企业的统计体制长期束缚于传统的靠行政手段组织各种经济活动的计划经济体制之下,这种严重的滞后性阻碍了企业统计工作的发展,处于“要你干的干不好,想要干的干不了”的进退两难的尴尬境地,作为企业的统计如何尽快走出传统的统计模式勇敢地迎接市场的挑战,充分发挥统计信息、咨询、监督的功能迫在眉睫。一、统计在企业的价值统计作为国民经济核算体系的一个不可缺少的组成部分,它具有相对独立的体系和完整的功能。工业企业统计的作用是作为反映工业企业生产活动的一面镜子,从数字资料中显示企业生产经营活动的     

关注统计数据质量

改革开放以来，统计的外部环境和 内部环境都发生了巨大的变化，对传统统计方法下的统计数据质量提出了挑战。同时，统计数据质量问题引发的种种社会和政治问题，已经引起了党中央的高度重视。统计部门近年也不断加大统计执法力量，加速改进工作方法，加强数据质量评估工作。但是，影响统计数据质量的因素是多方面的，不是单靠部门行使统计管理手段就能得以解决，需要引起社会的关注和重视，多管齐下，采取综合治理的办法才能得到有效解决。谈到这个问题，有必要再回过头来分析一下当前数据质量存在的问题。问题之一：领导重视程度不一。统…     

建立统计经济学之思考

市场经济体制的建立,世界贸易组织的加入,使服务于社会经济的我国统计工作面临前所未有的挑战。对包括统计体制、传统统计理论、方法、技术等方面实施全方位的统计创新已势在必行,新形势下建立统计经济学的条件已经成熟。 统计经济学是从不同侧面、不同角度对统计进行经济研究的经济学科。它是用现有的经济学理论、原理和方法考察分析统计活     

数据大集中环境下的统计生产流程再造

随着中国经济结构的不断调整和经济现象的日益复杂化,现有政府统计面临极大的挑战。基于此,以制度领域、技术领域和管理领域的数据大集中为核心架构,构建一种新型的政府统计数据大集中环境,并依托该环境对中国政府统计生产流程进行再造。     

Current challenges in statistics: large-lecture courses

Each semester approximately 80% of the students taught by the Florida State University Department of Statistics are enrolled in STA 3014: Fundamental Business Statistics. During the academic year this course is taught in large lecture sections of 250 students each. It is either the only statistics course or one of two statistics courses taken in their undergraduate career for probably 90% of these students. A similar situation exists in many statistics departments around the nation.

These large introductory courses offer us the opportunity to introduce the power of statistics to a large fraction of our future business leaders. In the past it appears that this opportunity has often been missed. In fact, some suggest that these courses help contribute to the general public's negative attitude toward statistics courses, the discipline of statistics, and statisticians.

Hence, I propose that one of the current challenges in statistics is the challenge of improving the quality of these courses so that statistics may contribute to the improvement of quality and productivity in the United States, a vital national issue. In this paper I report on my experiences in grappling with this challenge in STA 3014.     

Simulation and quality of a synthetic close-to-reality employer–employee population

It is of essential importance that researchers have access to linked employer–employee data, but such data sets are rarely available for researchers or the public. Even in case that survey data have been made available, the evaluation of estimation methods is usually done by complex design-based simulation studies. For this aim, data on population level are needed to know the true parameters that are compared with the estimations derived from complex samples. These samples are usually drawn from the population under various sampling designs, missing values and outlier scenarios. The structural earnings statistics sample survey proposes accurate and harmonized data on the level and structure of remuneration of employees, their individual characteristics and the enterprise or place of employment to which they belong in EU member states and candidate countries. At the basis of this data set, we show how to simulate a synthetic close-to-reality population representing the employer and employee structure of Austria. The proposed simulation is based on work of A. Alfons, S. Kraft, M. Templ, and P. Filzmoser [{\em On the simulation of complex universes in the case of applying the German microcensus}, DACSEIS research paper series No. 4, University of Tübingen, 2003] and R. Münnich and J. Schürle [{\em Simulation of close-to-reality population data for household surveys with application to EU-SILC}, Statistical Methods & Applications 20(3) (2011c), pp. 383–407]. However, new challenges are related to consider the special structure of employer–employee data and the complexity induced with the underlying two-stage design of the survey. By using quality measures in form of simple summary statistics, benchmarking indicators and visualizations, the simulated population is analysed and evaluated. An accompanying study on literature has been made to select the most important benchmarking indicators.     

官方统计应如何面对Big Data 的挑战

 随着信息化、网络化时代的到来,"Big Data"的浪潮为整个社会带来了信息金矿,也给官方统计带来了挑战。本文对官方统计应该如何正确认识"Big Data”,如何积极应对“Big Data”带来的挑战,进行了初步分析,给出了作者的明确回答。     

Data quality: A statistical perspective

We present the old-but-new problem of data quality from a statistical perspective, in part with the goal of attracting more statisticians, especially academics, to become engaged in research on a rich set of exciting challenges. The data quality landscape is described, and its research foundations in computer science, total quality management and statistics are reviewed. Two case studies based on an EDA approach to data quality are used to motivate a set of research challenges for statistics that span theory, methodology and software tools.     

Opportunities and challenges for industrial statisticians

The last 20 years have seen significant advances in the use of statistical methodology in industry, with applications in new product design and development, optimization and control of manufacturing processes, and in the service industries. The field of industrial statistics has emerged as an important branch of statistical science that focuses on this application environment. Yet as applications of statistics in industry have expanded, creating many new opportunities for the modern industrial statistician, many new challenges have arisen. Some of these challenges are technical, while others have managerial and organizational aspects. There are also important concerns pertaining to training and education. This presentation focuses on some of these issues, and identifies some potential solutions.     

Opportunities and challenges for industrial statisticians

The last 20 years have seen significant advances in the use of statistical methodology in industry, with applications in new product design and development, optimization and control of manufacturing processes, and in the service industries. The field of industrial statistics has emerged as an important branch of statistical science that focuses on this application environment. Yet as applications of statistics in industry have expanded, creating many new opportunities for the modern industrial statistician, many new challenges have arisen. Some of these challenges are technical, while others have managerial and organizational aspects. There are also important concerns pertaining to training and education. This presentation focuses on some of these issues, and identifies some potential solutions.     

互联网统计研究

互联网发展从IT到DT已经成为必然的趋势,本文研究了DT时代的统计思维,提出互联网统计概念和互联网统计体系的基本内容,研究了面向未来发展的互联统计、互通统计、互动统计的互联网统计理论体系。考察了国际电信联盟、中国互联网络信息中心的互联网统计体系,以及国家统计局企业信息化和电子商务统计,指出存在的问题和与实际需要的巨大缺口,研究了互联网统计发展所面临的挑战,提出了我国互联网统计发展的政策建议。     

Probabilistic Modeling—From Physics to Computing Science

It is important in computing science to estimate the number of data blocks needed to answer a query. Three different answers to this problem emerged respectively in 1975, 1977, and 1982. This article investigates the basic differences of the three models and observes that the same differences were shared a long time ago by the physicists who used different models for the behavior of elementary particles to obtain the Maxwell-Boltzmann statistics, the Bose-Einstein statistics, and the Fermi-Dirac statistics.     

网上拍卖中竞买者出价数据的特征及分析方法研究

在传统统计分析中，研究者面对的数值型数据有三种形式，即横截面数据、时间序列数据以及混合数据。这些类型的数据具有离散、等间隔分布、密度均匀等特点，它们是传统的描述性统计和推断性统计中最主要的数据分析对象。然而，从拍卖网站收集到的诸如竞买者出价等数据，却不具备这些特点，对传统统计分析方法提出了挑战。因此需要从数据容量、数据的混合性、不等间隔分布及数据密度等方面，对网上拍卖数据的产生机制进行阐释，对其特征进行分析，并结合实际网上拍卖资料给出分析此类数据的方法和过程。