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。     

Three-Factor Cartographic Representation

Statistics and statisticians have contributed to industry. Attention has been given to the appropriate training of statisticians for careers in industry. Statistics is used with benefit to industry in quality control, experimental design in research and development, and management decisions. Statistics can benefit from industry's assistance, the subject of this article. Five premises are set forth, three of them suggesting problems for statistics and industry. They relate to public understanding of statistics, the recruitment of students to statistics, the recruitment of statisticians to industry, and the relevance of research in statistics to the needs of industry. Thirteen recommendations are made on what industry can do for statistics and suggestions are made on how the American Statistical Association and the American Society for Quality Control can provide leadership in meeting the problems posed with the help of industry.     

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.     

一级学科背景下社会经济统计学的发展

 本文基于统计学成为一级学科这个背景，分析了社会经济统计学面临的机遇与挑战，阐述了进一步发展社会经济统计学的四个基点——遵循历史轨迹、深化和拓展对社会经济现象的认识、规律研究与方法研究并重以及立足于对中国社会经济现实问题的研究，并且提出了加强合作、搭建平台的有关设想。     

概率抽样条件下样本代表性事后评估方法探讨

 样本代表性直接牵扯到统计数据质量和统计公布引起的民众反响,目前社会上不乏对政府统计数据的质疑之声,最终影响到政府统计机关的公信力,因此有必要重新审视现行样本代表性的研究。目前相关文献普遍强调不同抽样方式下的样本代表性的相对性内涵,确保样本的代表性仅从抽样方法和样本量两个维度入手,缺乏对既定抽样方法下样本代表性的事后评估体系的探索,以及多样本之间样本代表性优劣的比较方法研究。鉴于此,本文在结合人口普查数据基础上尝试从样本-总体整体分布和内部属性结构两个方面构建样本代表性事后评估的一整套指标和假设检验,进而找到一种多样本代表性比较的依据。最后对浦东新区2010年城镇居民收入调查样本进行了代表性检验的尝试。     

企业统计数据质量影响因素的实证分析

为明确企业统计数据质量的影响因素,定量描述各因素之间的关系,利用SEM模型,通过SPSS AMOS18.0软件进行数据分析,得到企业的信息化程度、企业重视化程度、企业统计力量、统计人员知识水平、统计人员地位、组织正规化程度6个因素的企业统计数据质量结构模型,并比较各个因素对企业统计数据质量影响的大小及各影响因素之间的相关关系,为进一步提高企业的统计数据工作提供了依据。     

关于我国国际服务外包统计体系建立、演进和改革方向的研究

2006年以来,大力发展国际服务外包在扩增量、提质量、优结构、促发展等方面发挥着不可或缺的作用。建立健全统计体系是记录和承载我国国际服务外包发展足迹与功绩的系统性工程。本文对国际服务外包和服务贸易的定义、统计定义和范围,统计的历史沿革和面临的挑战等进行了研究,提出了新时期统计的改革方向和建议。     

基于SAM的宏观统计数据质量评估方法研究

数据质量评估是统计数据质量管理的重要环节。从SAM核算框架入手,提出了宏观统计数据质量的评估方法,主要包括等量核算指标体系评估方法、账户平衡指标体系评估方法及"问题型"评估方法,以期从SAM的角度为宏观统计数据质量的甄别和提高提供一种研究方法。     

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.     

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。     

新时代中国经济社会统计的创新与发展

新时代,我国经济社会发展产生了许多新情况,经济社会管理产生了许多新需求,经济社会统计的理论、方法和应用要实现创新与发展,以适应新时代、反映新情况、满足新需求,在服务宏观经济决策和促进经济社会健康发展,以及促进经济学、社会学发展等方面发挥更加重要的作用。本文从统计理论和方法、学术研究和人才培养等方面阐述了新时代我国经济社会统计面临的严峻挑战和重大发展机遇;从创新研究领域、创新研究方法和创新人才培养方式等方面探讨了新时代我国经济社会统计如何实现创新与发展,以服务于国家重大发展战略、助力解决我国经济社会发展现实问题、对接国际前沿研究领域;提出了新时代我国经济社会统计的若干重点研究领域,包括新经济统计理论和方法研究、全要素生产率研究、服务业核算问题研究、无形资产测度问题研究、全球价值链研究等。     

政府统计生产及其行为研究

政府统计不仅是一种手段,更重要的是一种生产活动。该研究在分析了政府生产性过程的基础上,按照行为理论,以方法论上的个人主义和个人效用最大化作为立论的基点,比较全面地揭示出政府统计用户、统计数据生产者和统计调查对象的行为特点,对于人们总结政府统计规律,规范政府统计行为,提高政府统计数据质量具有重要的参考价值。     

Nontraditional Approaches to Assessing Journal Importance: Case Study of Russian Journals on Earth Sciences

Abstract

Currently, a broad set of bibliometric indices for evaluation of journal quality, the level of its internationalization, and interactions between serials are available. However, some cases require one to obtain more precise methods to assess journals, e.g., when estimating new journals, selecting them into international citation databases, increasing their rank, broadening their readership, or optimizing editorial policy. To cope with new challenges, new approaches have been introduced including altmetrics and various analyses of editorial board composition and impact. Analyzing altmetrics and studying geographic diversity on editorial boards, comparing these data with that of journal authors, and evaluating research efficiency of editorial board members enables one to use new approaches to assess the rank of serials. This paper considers current research reports on altmetrics, geographic diversity, and publication activity of editorial board members of top journals on Earth Sciences published in the Russian Federation and recognized as international serials. It was found that such altmetrics as abstract views, full text views, and a number of viewed papers are now available as additional metrics to evaluate journal quality. Furthermore, provided that the data on altmetrics are complete, they can be considered as a specific predictor for future citations and other citation-based indices. Editorial board analyses demonstrate a correlation of bibliometric indices of editorial board members with that of a journal. As for geographic diversity, only half of the analyzed journals demonstrate a strong correlation between the number of foreign members on editorial boards and geographic representativeness of a journal, mainly due to the local nature of geosciences and trade secret mode in much of mining research. Generally, the obtained findings highlighted the efficiency of new approaches to evaluate journal quality both in the case of the absence of citation-based journal metrics and as an additional tool to traditional indices.     

Percentage points and power calculations for outlier tests in a regression situation

The usefulness of an extra sum of squares statistics Q_K for detecting K outliers has been discussed previously in the context of two-way tables. (See Gentleman and Wilk, 1975a, 1975b; John and Draper 1978; and Draper and John, 1980,) That work is extended here to straight line regression situations arising from, and motivated by, a specific set of research data. Percentage points for the appropriate test statistics are obtained by simulation, and approximations for these percentage points are suggested. Power calculations made for various designs and outlier situations are briefly summarized.     

传统统计面对的挑战

针对统计的黑匣子特性,借用Breiman的两种统计文化的平台,分析传统统计面临的挑战和危机,并探索统计领域究竟要向何处发展的问题。研究表明：统计学必须重新回到针对实际问题而与数据打交道,并且创造有关理论的传统上来。只有这样,才能应对不断产生的新问题所带来的挑战。     

On weighted composite scores for early Alzheimer's trials

Recent research on finding appropriate composite endpoints for preclinical Alzheimer's disease has focused considerable effort on finding “optimized” weights in the construction of a weighted composite score. In this paper, several proposed methods are reviewed. Our results indicate no evidence that these methods will increase the power of the test statistics, and some of these weights will introduce biases to the study. Our recommendation is to focus on identifying more sensitive items from clinical practice and appropriate statistical analyses of a large Alzheimer's data set. Once a set of items has been selected, there is no evidence that adding weights will generate more sensitive composite endpoints.     

从政治算术到大数据分析

本文首先对大数据进行了再认识,包括如何理解大数据的“大”、如何理解大数据的“数据”以及大数据是不是好数据;然后对数据的变化与统计分析方法的发展进行了较为系统的历史梳理,对两者的关系进行了总结;最后探讨了统计学的新发展--大数据分析问题,认为大数据分析是数据科学赋予统计学的新任务,指出了大数据分析面临的挑战与突破口,提出了大数据分析需要达成的共识。     

Considerate approaches to constructing summary statistics for ABC model selection

For nearly any challenging scientific problem evaluation of the likelihood is problematic if not impossible. Approximate Bayesian computation (ABC) allows us to employ the whole Bayesian formalism to problems where we can use simulations from a model, but cannot evaluate the likelihood directly. When summary statistics of real and simulated data are compared??rather than the data directly??information is lost, unless the summary statistics are sufficient. Sufficient statistics are, however, not common but without them statistical inference in ABC inferences are to be considered with caution. Previously other authors have attempted to combine different statistics in order to construct (approximately) sufficient statistics using search and information heuristics. Here we employ an information-theoretical framework that can be used to construct appropriate (approximately sufficient) statistics by combining different statistics until the loss of information is minimized. We start from a potentially large number of different statistics and choose the smallest set that captures (nearly) the same information as the complete set. We then demonstrate that such sets of statistics can be constructed for both parameter estimation and model selection problems, and we apply our approach to a range of illustrative and real-world model selection problems.     

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。     

我国统计学类专业本科教育现状的调查与分析

随着统计学上升为一级学科以及“大数据”时代的到来,我国统计学本科教育得到迅猛的发展。为了保证本科教育的质量,教育部提出要制定各专业教学质量的国家标准。本报告是为了制定统计学专业教学质量的国家标准而开展的对全国统计学专业调查的总结与分析。