季节调整与环比增长率测算最新进展及比较

国家统计局从2011年4月对外公布经季节调整的包括GDP的四项统计指标的环比数据,这标志着季节调整和环比增长率测算在我国统计工作实践中已经起步.本文从季节调整的理论研究和实践两个方面对各种季节调整模型、国内外理论研究和各国统计工作实践的差异进行比较分析,发现国内外在研究基础、理论和应用研究比例、研究模型的广度和基础理论研究等理论研究方面以及季节调整的指标范围、环比增长率测算、数据的公布等实际工作方面均存在较大差异.这对我国进一步完善季节调整模型和软件,不断提高环比统计数据质量,以及逐步建立月、季度统计调查制度具有重要意义.     

Sir Godfrey Thomson: a statistical pioneer

Summary.  Godfrey Thomson (1881–1955) was a leading figure in intelligence testing who made his name in that field first at Armstrong College, Newcastle, and then at the University of Edinburgh. In the course of his practical work he identified many theoretical problems which were essentially statistical in character. In particular, he used maximum likelihood estimation as early as 1919 and his statistical work largely set the course of modern factor analysis and related techniques. His statistical abilities were recognized, at different stages of his career, by both Karl Pearson and Sir Ronald Fisher. His key insight was to recognize the importance of Fisherian inference for the future of that subject.     

A Study of Student Reaction to the Use of Minitab in an Introductory Statistics Course

Traditionally, the introductory statistics course, Principles of Statistics (STAT 101), at Iowa State University has been taught without reference to a statistical analysis computing package. Although important for the implementation of statistical techniques, a computer component has been perceived by instructors to take time away from the coverage of statistical topics. To gauge students' reactions to the usefulness of a statistical computing package, an experiment was conducted during the fall term of 1986. Volunteers from a STAT 101 class were randomly assigned to either a control group or a computer use group. Both groups filled out questionnaires at the beginning and end of the semester. During the semester, the computer use group had access to and instruction in the use of Minitab. This instruction was tied to homework and laboratory assignments for the course. This article presents results of this experiment. On the basis of the responses to the questionnaires, the value of a statistical computing package as a pedagogical tool is examined. Recommendations for the use of a statistical computing package in a large introductory statistics course are made.     

Elementary statistics laboratory

Students in elementary statistics traditionally see experiments and data as words and numbers in a text. They receive little exposure to the important statistical activities of sample selection, data collection, experimental design, development of statistical models, the need for randomization, selection of factors, etc. They often leave the first course without a firm understanding of the role of applied statistics or of the statistician in scientific investigations. In an attempt to improve elementary statistics education, we have developed a statistics laboratory similar to those of other elementary science courses. We will discuss our experiences in teaching a laboratory component with the traditional elementary statistics course. In each lab session, students, working in teams, discuss the design of an experiment, carry out the experiment, and analyze their data using Minitab on a Macintosh or MS-DOS based computer. The students then individually either answer a series of short answer questions or write a formal scientific report. The labs are designed to be relatively inexpensive and portable. They do not require a prior background in science, statistics or computing.     

A Note on “Characteristics of the Membership of the American Statistical Association, 1958”

A second course in statistics, for nonstatisticians who will use packaged statistical software in their work, is outlined. The course is directed toward the wise choice, use, and evaluation of statistical computer packages. The goal of the course is to train educated consumers of statistical programs. Particular attention is paid to computer-based data analysis, interpretation of output, comparison of competing packages, and statistical problems that arise when computers are employed to analyze large data sets.     

论杭州工业主导产业的选择和培育

 摘　　要:本文以经济学主导产业的有关理论为指导，利用统计模型和统计数据，从产业专业化程度、增长优势、带动力、7项技术经济指标对杭州工业37个大类行业进行了综合评价，系统分析了有利条件与不利因素，提出了通信设备计算机及其他电子设备业、通用设备制造业、医药制造业、化学纤维制造业、纺织业、专用设备制造业、仪器仪表及文化办公用机械制造业等七大产业应作为杭州优先发展的主导产业     

Statistical Inference Enables Bad Science; Statistical Thinking Enables Good Science

ABSTRACT

Scientific research of all kinds should be guided by statistical thinking: in the design and conduct of the study, in the disciplined exploration and enlightened display of the data, and to avoid statistical pitfalls in the interpretation of the results. However, formal, probability-based statistical inference should play no role in most scientific research, which is inherently exploratory, requiring flexible methods of analysis that inherently risk overfitting. The nature of exploratory work is that data are used to help guide model choice, and under these circumstances, uncertainty cannot be precisely quantified, because of the inevitable model selection bias that results. To be valid, statistical inference should be restricted to situations where the study design and analysis plan are specified prior to data collection. Exploratory data analysis provides the flexibility needed for most other situations, including statistical methods that are regularized, robust, or nonparametric. Of course, no individual statistical analysis should be considered sufficient to establish scientific validity: research requires many sets of data along many lines of evidence, with a watchfulness for systematic error. Replicating and predicting findings in new data and new settings is a stronger way of validating claims than blessing results from an isolated study with statistical inferences.     

An Examination of the Conceptual Issues Involved in Developing Credit-Scoring Models

Multiple discriminant analysis (MDA) is frequently used to develop statistical credit-scoring models for loan evaluation purposes. Current legislative efforts to insure that credit is being granted in a nondiscriminatory manner have focused considerable attention on the reliability of such models. This article examines the theoretical requirements of the MDA model in the context of a realistic lending situation and illustrates the extent of bias when these theoretical assumptions are not fully met. The article concludes that failure to rigorously meet all the theoretical assumptions of the statistical model may not be as critical as insuring that credit managers fully understand the limitations of these types of decision tools. Furthermore, the evidence indicates that statistical models other than multiple discriminant analysis are possibly more relevant to the credit-granting decision.     

Teaching Communication in a Statistical Collaboration Course: A Feasible,Project-Based,Multimodal Curriculum

Many schools offer a statistical collaboration curriculum using standard instructional methods such as lectures whereby students are taught to successfully apply their training. The process of building statisticians' collaborative skills and characteristics can be challenging due to logistical issues, time constraints, unstructured research problems, and resources. Instructors vary in their pedagogy and topics taught, and students' experiences vary. There is a dearth of literature describing how to implement a course integrating communication skills, critical thinking, collaboration, and the integration of team members in a learner-centered format. Few courses integrate behavior-based learning using role-playing, video demonstration and feedback, case-based teaching activities, and presentation of basic statistical concepts. We have developed and implemented a two-semester biostatistics collaboration course, of which the purpose is to develop the students' knowledge, skills, attitudes, and behaviors necessary to interact effectively with investigators. Our innovative curriculum uses a multimodal, project-based, experiential process to address real-world problems provided by real and/or simulated collaborators while minimizing usual challenges. Rubrics and peer evaluation forms are offered as online supplementary materials. This article describes how a collaboration curriculum focusing on communication and team practice is feasible, how it enhances skill and professionalism, and how it can be implemented at other institutions.     

Teaching Statistical Consulting Before Statistical Methodology

This paper outlines and discusses the advantages of an ‘Introduction to Statistical Consulting’ course (ISC) that exposes students to statistical consulting early in their studies. The course is intended for students before, or while, they study their units in statistical techniques, and assumes only a first‐year introductory statistics unit. The course exposes undergraduate students to the application of statistics and helps develop statistical thinking. An important goal is to introduce students to work as a statistician early in their studies because this motivates some students to study statistics further and provides a framework to motivate the learning of further statistical techniques. The ISC has proved popular with students, and this paper discusses the reasons for this popularity and the benefits of an ISC to statistical education and the statistics profession.     

Enriching Students’ Conceptual Understanding of Confidence Intervals: An Interactive Trivia-Based Classroom Activity

Confidence intervals provide a way to determine plausible values for a population parameter. They are omnipresent in research articles involving statistical analyses. Appropriately, a key statistical literacy learning objective is the ability to interpret and understand confidence intervals in a wide range of settings. As instructors, we devote a considerable amount of time and effort to ensure that students master this topic in introductory courses and beyond. Yet, studies continue to find that confidence intervals are commonly misinterpreted and that even experts have trouble calibrating their individual confidence levels. In this article, we present a 10-min trivia game-based activity that addresses these misconceptions by exposing students to confidence intervals from a personal perspective. We describe how the activity can be integrated into a statistics course as a one-time activity or with repetition at intervals throughout a course, discuss results of using the activity in class, and present possible extensions. Supplementary materials for this article are available online.     

Copula structure analysis

Summary.  We extend the standard approach of correlation structure analysis for dimension reduction of high dimensional statistical data. The classical assumption of a linear model for the distribution of a random vector is replaced by the weaker assumption of a model for the copula. For elliptical copulas a correlation-like structure remains, but different margins and non-existence of moments are possible. After introducing the new concept and deriving some theoretical results we observe in a simulation study the performance of the estimators: the theoretical asymptotic behaviour of the statistics can be observed even for small sample sizes. Finally, we show our method at work for a financial data set and explain differences between our copula-based approach and the classical approach. Our new method yielear models also.     

Multivariate online regression analysis with heterogeneous streaming data

New data collection and storage technologies have given rise to a new field of streaming data analytics, called real-time statistical methodology for online data analyses. Most existing online learning methods are based on homogeneity assumptions, which require the samples in a sequence to be independent and identically distributed. However, inter-data batch correlation and dynamically evolving batch-specific effects are among the key defining features of real-world streaming data such as electronic health records and mobile health data. This article is built under a state-space mixed model framework in which the observed data stream is driven by a latent state process that follows a Markov process. In this setting, online maximum likelihood estimation is made challenging by high-dimensional integrals and complex covariance structures. In this article, we develop a real-time Kalman-filter-based regression analysis method that updates both point estimates and their standard errors for fixed population average effects while adjusting for dynamic hidden effects. Both theoretical justification and numerical experiments demonstrate that our proposed online method has statistical properties similar to those of its offline counterpart and enjoys great computational efficiency. We also apply this method to analyze an electronic health record dataset.     

Investigate Data Dependency for Dynamic Gene Regulatory Network Identification through High-dimensional Differential Equation Approach

Gene regulation plays a fundamental role in biological activities. The gene regulation network (GRN) is a high-dimensional complex system, which can be represented by various mathematical or statistical models. The ordinary differential equation (ODE) model is one of the popular dynamic GRN models. We proposed a comprehensive statistical procedure for ODE model to identify the dynamic GRN. In this article, we applied this model to different segments of time course gene expression data from a simulation experiment and a yeast cell cycle study. We found that the two cell cycle and one cell cycle data provided consistent results, but half cell cycle data produced biased estimation. Therefore, we may conclude that the proposed model can quantify both two cell cycle and one cell cycle gene expression dynamics, but not for half cycle dynamics. The findings suggest that the model can identify the dynamic GRN correctly if the time course gene expression data are sufficient enough to capture the overall dynamics of underlying biological mechanism.     

社会统计学研究与实践迅速繁荣

社会统计学在中国是一门年轻的学科,是发展迅速的,也是有极大潜力的。本文将首先回顾中国社会统计学的发展,阐述中国统计部门与研究人员曾为之付出的努力。其次,分析当下社会统计学的繁荣景象,分析其繁荣的背景、繁荣的根源和繁荣的表现。最后,分析社会统计工作的“关注点”,希望对中国相关部门工作的开展有所帮助。     

国家统计机构比较研究

 内容提要：本研究报告在广泛收集和研究国外相关资料的基础上，介绍了国家统计机构的一般组织结构、官方统计基本原则在各国的实施和经验。在此基础上，剖析了官方统计10项基本原则在我国统计工作中的实施情况，通过对照、检查，指出我国统计工作在很多方面已经达到国际通行的官方统计基本原则要求，在一些方面甚至处于国际领先水平。但是，在某些方面与国际标准相比，仍有一定的差距，需要进一步改进、提高。为此，提出了完善我国统计工作的初步建议。     

Wavelets in statistics: A review

The field of nonparametric function estimation has broadened its appeal in recent years with an array of new tools for statistical analysis. In particular, theoretical and applied research on the field of wavelets has had noticeable influence on statistical topics such as nonparametric regression, nonparametric density estimation, nonparametric discrimination and many other related topics. This is a survey article that attempts to synthetize a broad variety of work on wavelets in statistics and includes some recent developments in nonparametric curve estimation that have been omitted from review articles and books on the subject. After a short introduction to wavelet theory, wavelets are treated in the familiar context of estimation of «smooth» functions. Both «linear» and «nonlinear» wavelet estimation methods are discussed and cross-validation methods for choosing the smoothing parameters are addressed. Finally, some areas of related research are mentioned, such as hypothesis testing, model selection, hazard rate estimation for censored data, and nonparametric change-point problems. The closing section formulates some promising research directions relating to wavelets in statistics.     

《九章算术》中的统计学思想探究

《九章算术》是中国历史上最著名的一部数学经典,该书以应用问题求解的形式为成书体例,而这些问题基本都与社会经济有关,因此书中蕴涵了丰富的统计学思想。本文从统计范围和统计思想的角度对书中的统计知识进行了分析,探讨了书中诸如统计分组、抽样推断、线性回归分析及比例关系等统计理论,并据此对当时中国古代统计思想的发展状况进行了研究。