论统计行为目标

统计行为目标与统计目标有区别和联系,统计行为目标是统计目标和统计行为动机的函数,统计行为动机是现实生活中不可忽视的重要因素。     

论统计行为目标

统计行为目标与统计目标有区别和联系。统计行为目标是统计目标和统计行为动机的函数 ,统计行为动机是现实生活中不可忽视的重要因素     

统计人格与塑造

人格心理结构与统计人格 人格心理结构包含以下几部分: 倾向性.即对周围现实生活持什么样的态度和采取什么样的行为方式,其对人格的所有心理活动起支配作用.统计人格的倾向性表现为不同的统计人员在统计活动中的态度和工作方式.     

统计我们生活的好帮手

统计是认识社会的最有力的武器,现在统计学越来越多地被应用到我们对社会现象的认识中。统计信息在我们的生活中无处不在,但多数人依然将统计和枯燥、高深难懂联系在一起。实际上要是了解了一些统计在生活中的简单运用,将会意识到,其实统计是简单的、易懂的、有趣的,统计能让我们更好地认识社会现象,为我们的生活带来便利。统计在现实生活中运用的例子很多,下边略举一二。     

例解统计认知

统计是人们认知客观世界的有力武器。统计是从数量观察入手来认识客观世界的,它使人们对客观事物的认识细化、深化、具体化,进而能够把握随机现象的统计规律性。在现实生活中,大到国家的经济、社会管理,小到个人的工作和生活,我们总免不了要与各种“数”打交道,也能够时时处处感觉到统计定量认识的重要作用。一、统计的认识作用1、统计使人们的认识得以深化。不妨举个例子,大家知道,“腐败”是危害社会主义现代化建设的一个严重问题,同时也是极难治理的社会毒瘤。原因何在?抛开产生腐败的深层经济、社会原因,单用统计方法来分析,我们也能够…     

统计语言的魅力

作为语言的功能就是传达思想,交流情感。统计语言就是用一系列的指标图表来传达着各种信息,通过具体的数字来表达自己的情感。统计语言以自己特有的方式来反映生动的现实生活,反映着社会和经济现象。 统计语言是用准确及时的统计数据,传达给受众,这是其他形式的语言所不能及的,     

统计与群众——写在“两会”之际

在过去的一年教学中,我对统计有了更加深刻的认识。站在讲台上授课和坐在下面聆听,那是两种感受。对于那些成人教育的学生来说,统计是很难的一门学科,几乎可以和高等数学相抗衡。起初,我还不理解。相比之下,统计更加贴近现实生活,而且用到的数     

加强五项建设全面提升统计基础水平

近年来，杭州市余杭区统计局围绕数据质量这一中心，开拓思路，创新载体，完善机制，切实加强统计基础建设，大力提升统计工作的“准确度”与“精确度”，取得了显著成效。2008年余杭区统计局被国家人力资源和社会保障部、国家统计局授予全国统计系统先进集体荣誉称号，并连续11年在杭州市统计局对各县（市、区）的综合考核中被评为先进单位。     

加强五项建设 全面提升统计基础水平 浙江省杭州市余杭区统计局局长夏雪芬

近年来,杭州市余杭区统计局围绕数据质量这一中心,开拓思路,创新载体,完善机制,切实加强统计基础建设,大力提升统计工作的准确度与精确度,取得了显著成效。2008年余杭区统计局被国家人力资源和社会保障部、国家统计局授予全国统计系统先进     

关于征集国际官方统计协会第二届会议提交论文的公告

国际官方统计协会第二届会议初步确定于1990年10月中旬在北京市举行。兹征集论文,凡愿向会议提交论文的作者,均可撰写。提交论文的参考题目如下:(1)怎样计算总供给与否需求;(2)工业企业统计工作的困境与出路;(3)通货膨胀率的测算方法;(4)人民生活质量的综合评价问题;(5)国民经济结构的统计方法;(6)宏观监测和评价的统计指标;(7)关于加强和完善统计法制的问题;(8)如何提高农村抽样调查的精确度;(9)市场供需平衡统计研究;     

统计虚假成因及治理对策研究

《统计法》已实施20余年,但统计数据虚假现象仍然十分严重。文章从统计体制、统计方法、执法缺陷等方面探析了统计数据虚假成因及治理对策。同时,现行《统计法》亟需修改完善。     

A statistical multivariable optimization method using improved orthogonal algorithm based on large data

Multivariable optimization under large data environment concerns with how to reliably obtain a set of optimization results from a mass of data that influence the object function complexly. This is an important issue in statistical calculation because the complexity between variable parameters leads to repeated statistical calculation analysis and a significant amount of data waste. A statistical multivariable optimization method using improved orthogonal algorithm based on large data is proposed. Considering the optimization problem with multi-parameters under large data environment, a multi-parameter optimization model used for improved orthogonal algorithm is established based on large data. Furthermore, an extensive simulation study on temperature field distribution of anti-/de-icing component was conducted to verify the validity of the statistical calculation analysis optimization method. The optimized temperature field distribution meets the anti-/de-icing requirements through numerical simulation. Simulation results show that the optimization effect is more evident and accurate than the non-optimized temperature distribution with the optimized results of the proposed method. Results verify the effectiveness of the proposed method.     

The robust economic statistical design of the Hotelling's T2 chart

ABSTRACT

Economic statistical designs aim at minimizing the cost of process monitoring when a specific scenario or a set of estimated process and cost parameters is given. But, in practice the process may be affected by more than one scenario which may lead to severe cost penalties if the wrong design is used. Here, we investigate the robust economic statistical design (RESD) of the T² chart in an attempt to reduce these cost penalties when there are multiple scenarios. Our method is to employ the genetic algorithm (GA) optimization method to minimize the total expected monitoring cost across all distinct scenarios. We illustrate the effectiveness of the method using two numerical examples. Simulation studies indicate that robust economic statistical designs should be encouraged in practice.     

A Question of Ethics

This article identifies three consulting roles—helper, leader, and colleague; recommends that statistical consultants ask more questions about basic mechanisms; suggests that statistical consultants regard their primary responsibility as providing guidance about the scientific method itself; discusses the need for continuing education to help improve consulting skills; and describes Wisconsin's Master's degree examination, which was designed to help students become effective practicing statisticians.     

粗糙集方法在医学影像诊断分析中的应用

医学诊断常面对越来越多的医学影像数据信息,比较不同分析方法对于疾病诊断十分必要.对183例脑胶质瘤的MR资料分别使用粗糙集理论和logistic回归分析方法导出影像诊断规则.与病理结果对比后发现,使用粗糙集理论的诊断规则准确性高于其他统计方法.粗糙集理论对提高医学影像学诊断水平有更好的临床应用价值.     

Segmentation,alignment and statistical analysis of biosignals with application to disease classification

We present a novel methodology for a comprehensive statistical analysis of approximately periodic biosignal data. There are two main challenges in such analysis: (1) the automatic extraction (segmentation) of cycles from long, cyclostationary biosignals and (2) the subsequent statistical analysis, which in many cases involves the separation of temporal and amplitude variabilities. The proposed framework provides a principled approach for statistical analysis of such signals, which in turn allows for an efficient cycle segmentation algorithm. This is achieved using a convenient representation of functions called the square-root velocity function (SRVF). The segmented cycles, represented by SRVFs, are temporally aligned using the notion of the Karcher mean, which in turn allows for more efficient statistical summaries of signals. We show the strengths of this method through various disease classification experiments. In the case of myocardial infarction detection and localization, we show that our method compares favorably to methods described in the current literature.     

Detection of multiple change-points in multivariate data

The statistical analysis of change-point detection and estimation has received much attention recently. A time point such that observations follow a certain statistical distribution up to that point and a different distribution – commonly of the same functional form but different parameters after that point – is called a change-point. Multiple change-point problems arise when we have more than one change-point. This paper develops a method for multivariate normally distributed data to detect change-points and estimate within-segment parameters using maximum likelihood estimation.     

模糊数学在统计指标体系分析中的应用

一、传统的统计指标体系评价方法作为统计学基本方法的指标体系分析与综合评价方法已经得到了广泛的运用 ,对经济学科、社会学科、教育学科、管理学科等形成了深刻的影响 ,成为定量化研究标准化方法之一。我们这里称之为“层次型评价模型”。图1展示了一个由两个评价层次构成的“层次评价树”模型 :被评价对象 (目标层 )评价方面二评价方面一1 11 2指标集一1 32 12 2指标集二2 3评价方面三 (准则层 )3 13 2指标集三3 3(指标层 )图 1　层次评价模型如图 1,在指标体系构建时 ,将某一评价对象分解为若干个评价方面 (准则 ) ,并把这种逐层次…     

Model Averaging for Prediction With Fragmentary Data

ABSTRACT

One main challenge for statistical prediction with data from multiple sources is that not all the associated covariate data are available for many sampled subjects. Consequently, we need new statistical methodology to handle this type of “fragmentary data” that has become more and more popular in recent years. In this article, we propose a novel method based on the frequentist model averaging that fits some candidate models using all available covariate data. The weights in model averaging are selected by delete-one cross-validation based on the data from complete cases. The optimality of the selected weights is rigorously proved under some conditions. The finite sample performance of the proposed method is confirmed by simulation studies. An example for personal income prediction based on real data from a leading e-community of wealth management in China is also presented for illustration.     

Federal Statistics in a Complex Environment: The Case of the 1980 Census

The taking and the interpretation of something as big and as complicated as the national census is more than an exercise in statistical thinking. It involves other diverse fields such as ethics, epistemology, law, and politics. This article shows that a national census is more akin to so-called ill-structured problems. Unlike well-structured problems, the formulation of an ill-structured problem varies from field to field and from person to person, and the various aspects of an ill-structured problem (i.e., ethics, epistemology, etc.) cannot be clearly separated from one another. The 1980 census is discussed as an ill-structured problem, and a method for treating such problems is presented, within which statistical information is only one component.