从中美统计的差异看我国统计改革

一、美国的统计机构及其运作多年来,美国统计在全社会有着广泛的渗透,统计协会、政府统计、企业统计、统计公司和统计教研等不同的统计载体共同构筑了美国的大统计范畴。1、联邦一级的政府统计机构与职能。在美国,没有独立的国家级政府统计部门,有关全国社会经济统计数据的收集     

统计教育：回顾过去，思考现在，展望未来

序言:这是曾任美国统计学会会长、国际统计教育协会副会长、佛罗里达州立大学统计系教授Richard L Scheaffer的一篇发表在美国统计学会《统计教育》时事通讯上的文章。该篇文章叙述了统计教育的历史以及未来,希望这篇文章能够给读者提供一些带有启发的信息,对于推动我国统计学的发展起些促进作用。     

探索统计改革 推进事业发展——四川省2006年统计科学研讨会综述

2006年4月26日,在春暖花开的美丽光华校园里,四川省统计局、四川省统计学会和西南财经大学联合召开了为期一天的主题为“统计改革与应用研究”的统计科学研讨会。四川省统计局局长、省统计学会会长胡安荣,总统计师、副会长胡品生,西南财经大学校长王裕国教授、副校长丁任重教授,成都信息工程学院副院长于世祥等领导、四川省统计学会和省内各分会的代表以及来自西南财经大学统计学院的部分师生参加了会议。四川省统计学会副会长庞皓教授主持了大会。大会首先由四川省统计学会副会长谭平祥宣读了中国统计学会发来的贺信。随后,四川省统计局局…     

出席55届国际统计大会的山东统计代表团返济

由山东省统计局、省统计学会组织的“山东统计代表团”，在省统计学会副会长、济南市统计局局长王祯祥团长率领下，圆满完成出席国际统计学会第55届大会的出访任务，于4月13日返回济南。     

统计部门如何缩小统计误差

众所周知,统计数据的准确性是统计工作的生命,提高统计数据质量是统计工作的重中之重。对如何缩小统计数据指标的误差是我们统计部门工作的一个重要任务和目标。为此。对如何缩小统计误差谈一点认识:一、统计误差的分类顾名思义,误差是指一个量的观测值或计算值与其实际值之差;统计误差,即反映某客观现象的一个量在测量、计算、观测过程中由于某些错误或通常由于某些不可控制的因素的影响而造成的变化偏离标准值或规定值的数量。统计误差共有如下几类:1.按产生统计误差的性质来分有:空间误差、时间误差、方法误差和人为误差四种。空间误差是…     

货币统计与金融统计的比较

我国过去面向金融领域的统计一直被称为"金融统计".2000年,自从国际货币基金组织颁布世界上第一部<货币与金融统计手册>(简称MFS)准则后,我国统计工作和统计科学开始出现一个新名词"货币与金融统计".     

继往开来 开拓进取把统计学会工作推上新台阶

黑龙江省统计学会召开了第六次会员代表大会,修改了学会章程,选出了新一届组织机构,学会工作开始了一个新的发展历程。如何使学会始终保持生命力和活力,是当前值得我们关注的问题。 一、正确认识统计学会在当前统计工作中的作用 黑龙江省统计学会是黑龙江省统计事业改革和发展中一支重要的力量,肩负着宣传普及统计科学知识、促进统计学术交流、开展统计科学研究,推动统计科技进步与创新的重要使命。因为统计学会是具有广泛性、     

创新务实 加快发展：—在中国统计学会第六次全国代表大会暨海峡两岸及香港统计科学研讨会上的讲话

各位代表、各位来宾: 大家好! 时值初夏,花重锦官,万象更新,生机盎然.中国统计学会的会员代表与来自台湾、香港的统计专家共聚天府之国,隆重召开中国统计学会第六次全国代表大会暨海峡两岸及香港统计科学研讨会.这是新世纪中国统计学会会员代表及两岸三地统计学者的第一次重要聚会.我相信这次大会的顺利召开,将成为新世纪中国统计科学发展的新起点,成为中国统计学术繁荣与进步的新契机.我谨代表国家统计局和中国统计学会向各位代表和来宾表示热烈的欢迎和诚挚的感谢!     

依托统计学会 弘扬统计文化

我们处在一个发展的时代，统计以及统计学会工作面临着许多新问题、新挑战，也蕴涵着许多新机遇、新希望。基层统计局如何开展统计学会工作？在这方面，我们荣成市统计局做了大量有益的尝试。我们的基本思路就是：以统计学会建设酝酿统计文化氛围，凝聚团结拼搏、求真务实、和谐有序、勇争一流的统计团队，不断开创统计事业发展的新局面。     

非统计专业的统计教学思考

统计的应用范围不断扩大,这无疑给当前的统计教学提出了新的要求,同时也给统计的教学改革提供了机遇。那么如何使学生尤其是非统计专业的学生真正学会用统计方法去解决学习和实践中的各种问题,就成了摆在统计教育工作者面前的一个共同课题。     

A changepoint statistic with uniform type I error probabilities

ABSTRACT

Likelihood ratio tests for a change in mean in a sequence of independent, normal random variables are based on the maximum two-sample t-statistic, where the maximum is taken over all possible changepoints. The maximum t-statistic has the undesirable characteristic that Type I errors are not uniformly distributed across possible changepoints. False positives occur more frequently near the ends of the sequence and occur less frequently near the middle of the sequence. In this paper we describe an alternative statistic that is based upon a minimum p-value, where the minimum is taken over all possible changepoints. The p-value at any particular changepoint is based upon both the two-sample t-statistic at that changepoint and the probability that the maximum two-sample t-statistic is achieved at that changepoint. The new statistic has a more uniform distribution of Type I errors across potential changepoints and it compares favorably with respect to statistical power, false discovery rates, and the mean square error of changepoint estimates.     

Falsification or choice among alternatives: The unsolved dilemma of hypothesis testing

Summary The scientific attitude towards statistical method has always pursued two basic objectives: identifying false assumptions and selecting, amongst the likely assertions, those which are most consistent with a given system. The methodological demarcation between rejection of a statistical statement, because it is ?false?, or exclusion, because it is ?least probable?, lies in the fundamental premises of inferential procedures. In the first class we find the methods proposed by Fisher, Neyman and Pearson; in the second one, the Bayesian techniques. Even if different inferential theories may coexist, any particular solution has a limit of validity strictly bouded, to the conventional procedural rules on which it is based. Invited paper at the Conference on ?Statistical Tests: Methodology and Econometric Applications?, held in Bologna, Italy, 27–28 May 1993.     

The Planning Stage in Statistical Reasoning

An important step in the statistical problem-solving process is the selection of the appropriate statistical procedure for the real-world situation under analysis. A decision-tree term project has been found to be an effective teaching device to help MBA students understand this step. The project requires the students to construct a decision-tree structure, which, through a series of questions and responses, will lead from the statement of a statistical question to the appropriate sampling distribution to use in addressing the question.     

P-Value Precision and Reproducibility

P-values are useful statistical measures of evidence against a null hypothesis. In contrast to other statistical estimates, however, their sample-to-sample variability is usually not considered or estimated, and therefore not fully appreciated. Via a systematic study of log-scale p-value standard errors, bootstrap prediction bounds, and reproducibility probabilities for future replicate p-values, we show that p-values exhibit surprisingly large variability in typical data situations. In addition to providing context to discussions about the failure of statistical results to replicate, our findings shed light on the relative value of exact p-values vis-a-vis approximate p-values, and indicate that the use of *, **, and *** to denote levels .05, .01, and .001 of statistical significance in subject-matter journals is about the right level of precision for reporting p-values when judged by widely accepted rules for rounding statistical estimates.     

小型经济单位从业人员调查抽样方法研究

不执行统计报表制度的小型经济单位的从业人员统计,应当用抽样调查方法进行。小型经济单位的各种统计调查项目,其中如生产统计调查项目、经营统计调查项目、劳动统计调查项目等等,应当合并在一起并分行业进行抽样调查。对小型工业单位进行从业人员调查的抽样技术,包括:样本轮换方针、在样本轮换条件下如何构造估计量、怎样对估计量的方差进行估计等。     

Will the ASA's Efforts to Improve Statistical Practice be Successful? Some Evidence to the Contrary

ABSTRACT

Recent efforts by the American Statistical Association to improve statistical practice, especially in countering the misuse and abuse of null hypothesis significance testing (NHST) and p-values, are to be welcomed. But will they be successful? The present study offers compelling evidence that this will be an extraordinarily difficult task. Dramatic citation-count data on 25 articles and books severely critical of NHST's negative impact on good science, underlining that this issue was/is well known, did nothing to stem its usage over the period 1960–2007. On the contrary, employment of NHST increased during this time. To be successful in this endeavor, as well as restoring the relevance of the statistics profession to the scientific community in the 21st century, the ASA must be prepared to dispense detailed advice. This includes specifying those situations, if they can be identified, in which the p-value plays a clearly valuable role in data analysis and interpretation. The ASA might also consider a statement that recommends abandoning the use of p-values.     

统计概念解析

本文从分析统计的本质属性出发,根据统计广泛性特点,归纳广义统计和狭义统计的概念,建立“统计概念总系”,力求能够包罗统计万象,体现统计全貌,使统计这一事物有一个总纲纪,为人们全面认识统计提供了一个新的视角。文中重点对政府统计纵向构成进行了分析和解读,解开人们在传统认识上的挽扣儿,这是正确理解政府统计构成的关键认识点,由此方能建立起统计概念体系。     

Implementing Monte Carlo tests with p-value buckets

Software packages usually report the results of statistical tests using p-values. Users often interpret these values by comparing them with standard thresholds, for example, 0.1, 1, and 5%, which is sometimes reinforced by a star rating (***, **, and *, respectively). We consider an arbitrary statistical test whose p-value p is not available explicitly, but can be approximated by Monte Carlo samples, for example, by bootstrap or permutation tests. The standard implementation of such tests usually draws a fixed number of samples to approximate p. However, the probability that the exact and the approximated p-value lie on different sides of a threshold (the resampling risk) can be high, particularly for p-values close to a threshold. We present a method to overcome this. We consider a finite set of user-specified intervals that cover [0, 1] and that can be overlapping. We call these p-value buckets. We present algorithms that, with arbitrarily high probability, return a p-value bucket containing p. We prove that for both a bounded resampling risk and a finite runtime, overlapping buckets need to be employed, and that our methods both bound the resampling risk and guarantee a finite runtime for such overlapping buckets. To interpret decisions with overlapping buckets, we propose an extension of the star rating system. We demonstrate that our methods are suitable for use in standard software, including for low p-value thresholds occurring in multiple testing settings, and that they can be computationally more efficient than standard implementations.     

Optimality of the posterior predictive p-value based on the posterior. Odds

Thompson (1997) considered a wide definition of p-value and found the Baves p-value for testing a ooint null hypothesis H₀: θ= θ₀ versus H₁: θ ≠ θ₀. In this paper, the general case of testing H₀: θ ∈ ?₀ versus H₁: θ ∈ ?^c ₀ is studied. A generalization of the concept of p-value is given, and it is proved that the posterior predictive p-value based on the posterior odds is (asymptotically) a Bayes p-value. Finally, it is suggested that this posterior predictive p-value could be used as a reference p-value     

New measures of clumpiness for incidence data

In recent years, growing attention has been placed on the increasing pattern of ‘clumpy data’ in many empirical areas such as financial market microstructure, criminology and seismology, and digital media consumption to name just a few; but a well-defined and careful measurement of clumpiness has remained somewhat elusive. The related ‘hot hand’ effect has long been a widespread belief in sports, and has triggered a branch of interesting research which could shed some light on this domain. However, since many concerns have been raised about the low power of the existing ‘hot hand’ significance tests, we propose a new class of clumpiness measures which are shown to have higher statistical power in extensive simulations under a wide variety of statistical models for repeated outcomes. Finally, an empirical study is provided by using a unique dataset obtained from Hulu.com, an increasingly popular video streaming provider. Our results provide evidence that the ‘clumpiness phenomena’ is widely prevalent in digital content consumption, which supports the lore of ‘bingeability’ of online content believed to exist today.