How Large Are Your G-Values? Try Gosset’s Guinnessometrics When a Little “p” Is Not Enough

Abstract

A crisis of validity has emerged from three related crises of science, that is, the crises of statistical significance and complete randomization, of replication, and of reproducibility. Guinnessometrics takes commonplace assumptions and methods of statistical science and stands them on their head, from little p-values to unstructured Big Data. Guinnessometrics focuses instead on the substantive significance which emerges from a small series of independent and economical yet balanced and repeated experiments. Originally developed and market-tested by William S. Gosset aka “Student” in his job as Head Experimental Brewer at the Guinness Brewery in Dublin, Gosset’s economic and common sense approach to statistical inference and scientific method has been unwisely neglected. In many areas of science and life, the 10 principles of Guinnessometrics or G-values outlined here can help. Other things equal, the larger the G-values, the better the science and judgment. By now a colleague, neighbor, or YouTube junkie has probably shown you one of those wacky psychology experiments in a video involving a gorilla, and testing the limits of human cognition. In one video, a person wearing a gorilla suit suddenly appears on the scene among humans, who are themselves engaged in some ordinary, mundane activity such as passing a basketball. The funny thing is, prankster researchers have discovered, when observers are asked to think about the mundane activity (such as by counting the number of observed passes of a basketball), the unexpected gorilla is frequently unseen (for discussion see Kahneman 2011 Kahneman, D. (2011), Thinking Fast and Slow, New York: Farrar, Straus and Giroux. [Google Scholar]). The gorilla is invisible. People don’t see it.     

“两个大局”思想的辩证思考及其现实意义

“两个大局”思想是贯穿邓小平理论的一个重要战略思想。它的提出既针对当时中国的现实国情,也考虑到将来发展中遇到的问题。“两个大局”蕴舍丰富的辩证思想,体现了现实利益与长远利益、效率与公平、分工与协作、权利与义务的统一。在改革开放已进入关键阶段的今天,“两个大局”思想仍具有重要的现实意义。     

专门用途英语特点及其在ESP课程设计中的应用——以市场营销课程为例

本文通过比较普通用途英语和专门用途英语,阐释专门用途英语的特点,并以市场营销英语教学为例,探讨了其课程内容设计及实现手段。     

通信企业"三网融合"方案设计研究

随着经济和技术的发展,传统的业务服务已经不能满足人们的需求,"三网融合"已经成为网络业务发展的必然趋势.通过对"三网融合"国内外现状的研究,分析了当今"三网融合"面临的问题,结合通信企业的实际情况,提出采用分布式流媒体技术进行通信企业"三网融合"方案设计,并针对不同规模通信企业,提出了紧凑型组网、城域网本地组网、多级分布式组网三种组网方案.该"三网融合"设计方案可以有效地节省骨干网带宽、保证QoS,提高用户满意度,对各级通信企业搭建多媒体数据中心具有一定推广作用.     

金融危机视角的农地制度安排:四村庄个案

由于地域差异明显,各地农地制度的安排与实践也有明显的区别,因而形成了不同的应对金融危机的实践形态。对这些实践形态进行比较分析发现,农地承包关系的灵活抑或刚性、农地产权的集体所有抑或私有并不是一个非此即彼的关系。从公平与效率两者结合的角度出发,构造一种将农村耕地划分为相对刚性的口粮田以保障农户的基本生存和相对灵活的责任田以保障农户的农业生产,并随人口变动而实现农户个体内部的口粮田与责任田自行补充的＂新两田制＂,有利于农村社会和整个国家应对危机,并为其处理危机赢得了相对宽松的时间与空间。     

考虑服务约束的第三方仓库收益与设计优化模型

第三方仓库作为服务提供商, 主要以期望收益最大化为目标, 但是必须满足一定的顾客服务标准。针对高需求环境, 考虑顾客服务水平约束, 提出了一个基于排队论的随机设计优化模型以使仓库的期望收益最大化。采用动态优化算法对模型求解, 选取实例进行了数值实验。结果显示, 模型的优化设计显著地提高了高需求环境下该第三方仓库的期望收益。在此基础上, 找到了服务约束的可行范围和有效范围, 为决策者制定服务标准提供了依据。     

A graphical evaluation of logistic ridge estimator in mixture experiments

In comparison to other experimental studies, multicollinearity appears frequently in mixture experiments, a special study area of response surface methodology, due to the constraints on the components composing the mixture. In the analysis of mixture experiments by using a special generalized linear model, logistic regression model, multicollinearity causes precision problems in the maximum-likelihood logistic regression estimate. Therefore, effects due to multicollinearity can be reduced to a certain extent by using alternative approaches. One of these approaches is to use biased estimators for the estimation of the coefficients. In this paper, we suggest the use of logistic ridge regression (RR) estimator in the cases where there is multicollinearity during the analysis of mixture experiments using logistic regression. Also, for the selection of the biasing parameter, we use fraction of design space plots for evaluating the effect of the logistic RR estimator with respect to the scaled mean squared error of prediction. The suggested graphical approaches are illustrated on the tumor incidence data set.     

Asymptotic Comparison Between Constant-stress Testing and Step-stress Testing for Type-I Censored Data from Exponential Distribution

By running the life tests at higher stress levels than normal operating conditions, accelerated life testing quickly yields information on the lifetime distribution of a test unit. The lifetime at the design stress is then estimated through extrapolation using a regression model. In constant-stress testing, a unit is tested at a fixed stress level until failure or the termination time point of the test, while step-stress testing allows the experimenter to gradually increase the stress levels at some pre-fixed time points during the test. In this article, the optimal k-level constant-stress and step-stress accelerated life tests are compared for the exponential failure data under Type-I censoring. The objective is to quantify the advantage of using the step-stress testing relative to the constant-stress one. A log-linear relationship between the mean lifetime parameter and stress level is assumed and the cumulative exposure model holds for the effect of changing stress in step-stress testing. The optimal design point is then determined under C-optimality, D-optimality, and A-optimality criteria. The efficiency of step-stress testing compared to constant-stress testing is discussed in terms of the ratio of optimal objective functions based on the information matrix.     

非对称成本扰动信息非线性需求函数下的供应链契约设计

为了分析非对称的成本扰动信息对于供应链契约设计的影响,研究了当制造商的成本发生扰动并且扰动信息是非对称的情形下的零售商的最优契约设计问题。假定市场需求是关于价格的非线性函数,使用委托-代理理论,设计了非对称的成本扰动信息下的供应链最优契约菜单,并且分析了非对称的扰动信息对于供应链绩效的影响。研究结果表明,当需求为常数柔性函数或者指数函数形式时,可以设计有效的契约菜单来改善供应链的绩效;在非对称的成本扰动信息下,当生产成本扰动满足一定条件时,初始的生产计划仍然是最优的;非对称的成本扰动信息并不必然会给供应链带来利润损失。最后通过数值算例对模型的结果进行了验证。     

The relative efficiency of the restricted estimators in linear regression models

This paper deals with the problem of multicollinearity in a multiple linear regression model with linear equality restrictions. The restricted two parameter estimator which was proposed in case of multicollinearity satisfies the restrictions. The performance of the restricted two parameter estimator over the restricted least squares (RLS) estimator and the ordinary least squares (OLS) estimator is examined under the mean square error (MSE) matrix criterion when the restrictions are correct and not correct. The necessary and sufficient conditions for the restricted ridge regression, restricted Liu and restricted shrunken estimators, which are the special cases of the restricted two parameter estimator, to have a smaller MSE matrix than the RLS and the OLS estimators are derived when the restrictions hold true and do not hold true. Theoretical results are illustrated with numerical examples based on Webster, Gunst and Mason data and Gorman and Toman data. We conduct a final demonstration of the performance of the estimators by running a Monte Carlo simulation which shows that when the variance of the error term and the correlation between the explanatory variables are large, the restricted two parameter estimator performs better than the RLS estimator and the OLS estimator under the configurations examined.