An Active Learning Exercise for Introducing Agent‐Based Modeling

Recent developments in agent‐based modeling as a method of systems analysis and optimization indicate that students in business analytics need an introduction to the terminology, concepts, and framework of agent‐based modeling. This article presents an active learning exercise for MBA students in business analytics that demonstrates agent‐based modeling by solving a knapsack optimization problem. For the activity, students act as naïve agents by using dice to randomly selecting items for a finite capacity knapsack to maximize the value of the knapsack. Students then design a greedy heuristic to skew the probability of selection item. These pencil‐and‐paper models are then implemented in a spreadsheet model to demonstrate the effects of altering the agents’ behavior. Finally, a binary integer programming model is examined to contrast agent‐based modeling with traditional mathematical programming formulations. This exercise is innovative because it combines student engagement via active learning with an innovative, individual‐based, modeling methodology.     

An Exercise to Introduce Power

In introductory statistics courses, the concept of power is usually presented in the context of testing hypotheses about the population mean. We instead propose an exercise that uses a binomial probability table to introduce the idea of power in the context of testing a population proportion.     

A Demonstration of Regression False Positive Selection in Data Mining

Business analytics courses, such as marketing research, data mining, forecasting, and advanced financial modeling, have substantial predictive modeling components. The predictive modeling in these courses requires students to estimate and test many linear regressions. As a result, false positive variable selection (type I errors) is nearly certain to occur. This article describes an in‐class demonstration that shows the frequency and impact of false positives on data mining regression‐based predictive modeling. In this demonstration, 500 randomly generated independent (X) variables are individually regressed against a single, randomly generated (Y) variable, and the resulting 500 p‐values are sorted and examined. This experiment is repeated and the distribution of the number of variables significant at the 5% level resulting from this simulation is presented and discussed. The demonstration provides a tangible example in which students see the reality and risks of incorrectly inferring statistical significance of independent regression variables. Students have expressed a deeper understanding and appreciation of the risks of type I errors through this demonstration. This demonstration is innovative because the scale of the simulation allows the students to experience the near certainty that the correlations shown in the results are truly random.     

论我国教育惩戒权的两极化运行与理性化回归

当前公众和学界对教育惩戒的关注度日益提升,而研究表明,教育惩戒权的运行呈现出的“惧用”与“滥用”两极化趋势愈发凸显。其原因在于我国教育惩戒制度的缺陷,即教育惩戒边界模糊、主体范围不明、自由裁量空间宽泛以及救济途径不足。此外,家庭结构和舆论环境等外部因素也加剧了两极化现状。因此,为实现教育惩戒权运行的理性回归,教育惩戒内在制度有待完善,外部环境因素也有待改进。     

Using Excel for White's Test—An Important Technique for Evaluating the Equality of Variance Assumption and Model Specification in a Regression Analysis

There is consensus in the statistical literature that severe departures from its assumptions invalidate the use of regression modeling for purposes of inference. The assumptions of regression modeling are usually evaluated subjectively through visual, graphic displays in a residual analysis but such an approach, taken alone, may be insufficient for assessing the appropriateness of the fitted model. Here, an easy‐to‐use test of the assumption of equal variance (i.e., homoscedasticity) as well as model specification is provided. Given the importance of the equal‐variance assumption (i.e., if uncorrected, severe violations preclude the use of statistical inference and moderate violations result in a loss of statistical power) and given the fact that, if uncorrected, a misspecified or underspecified model could invalidate an entire study, the test developed by Halbert White in 1980 is recommended for supplementing a graphic residual analysis when teaching regression modeling to business students at both the undergraduate and graduate levels. Using this confirmatory approach to supplement a traditional residual analysis has value because students often find that graphic displays are too subjective for determining what constitutes severe from moderate departures from the equal variance assumption or for assessing patterns in plots that might indicate model misspecification or underspecification.     

Exploratory Analysis to Identify Concepts,Skills, Knowledge,and Tools to Educate Business Analytics Practitioners

Recent technological advancements in data storage and processing have changed how companies conduct their business. An increasing number of firms have started putting their efforts in extracting information from their databases to improve profitability and reduce costs using quantitative approaches. Thus, the job market has been experiencing a rapidly growing demand for business analytics (BA) practitioners, and universities across the globe are increasingly responding to this newly emerged field by offering both undergraduate and graduate level degrees as well as certificate programs. Thus, this research aims to provide a framework for academic institutions to develop a state‐of‐the‐art master's in business analytics (MSBA) curriculum by identifying concepts, skills, knowledge, and tools (CSKT) that industry seeks in BA practitioners. Our data‐driven methodology utilizes peer institution analysis, indeed.com web scraping, and focus group analysis with mid‐ and senior‐level analytics leaders from major companies. Our contribution to the literature and recommendations to institutions developing MSBA programs are offered at the end.     

回归模型中的预测问题

概率统计在社会的各个领域都有着广泛的应用,尤其是回归模型。对回归模型的预测与控制问题进行了研究。首先介绍了回归模型以及回归模型的预测与控制方法,然后分析了回归模型预测的步骤,最后以企业实例为基础,分别对一元回归模型的预测、二元回归模型的预测进行了分析。     

回归分析在人口预测中的应用

本试用数理统计中回归分析的方法,建立我国人口,总数与时间的一元线性回归模型,用于人口预测。     

Ordinary Least Squares and Quantile Regression: An Inquiry-Based Learning Approach to a Comparison of Regression Methods

We present a short, inquiry-based learning course on concepts and methods underlying ordinary least squares (OLS), least absolute deviation (LAD), and quantile regression (QR). Students investigate squared, absolute, and weighted absolute distance functions (metrics) as location measures. Using differential calculus and properties of convex functions, students discover the sample mean, median, and pth quantile by minimizing sums of distances. Students use these metrics to define loss functions for OLS, LAD, and QR, and explore methods to minimize them. We discuss classroom experiences over two semesters. Classroom activities, Maple worksheets, and R demonstration code are available at a companion website.     

练习设计:回归儿童的生活世界

作为教学过程中重要一环的练习,理应在练习设计中将学生生活纳入自己的视野,创设生活化的练习情境,使练习活动体现儿童生活的特点,促使儿童获得丰富的生活体验,感受现实生活的乐趣和成长的快乐,使现实生活的教育意义得以充分显现。另一方面,练习设计还要服务于儿童未来的可能生活,引导儿童提升构建未来可能生活的能力,实现育人的根本目标。     

回归与ARMA模型在高等教育与经济增长关系研究的应用——以辽宁省为例

运用回归与ARMA模型方法,采用1985-2008年的年度数据,对科教兴国和振兴东北老工业基地的战略背景下辽宁省高等教育发展与经济增长之间的关系进行了实证研究。研究表明,辽宁高等教育发展与经济发展存在着长期的均衡的协整关系,高等教育发展是经济发展的格兰杰原因,但经济发展对高等教育发展的促进作用不是很明显。     

虚拟变量在线性回归模型中的一种应用

若干特异点处的统计量容易导致回归方程拟合不足,本文引入虚拟变量（Dummy Variables)给出一种较为实用的解决途径。     

浅谈精品视频公开课的制作

精品视频公开课区别于一般的校园精品课程,它的特点是高技术质量、受众群体广泛、符合学习者的学习习惯和认知规律。结合本校精品视频公开课建设,详细介绍了精品视频公开课的场地布置方案、人员安排、拍摄方法、后期制作技巧整个过程,并对如何改善组织水平、提高画面质量和利用后期弥补问题做了经验总结。     

The Ordering Challenge: An Online Game to Introduce Independent Demand Inventory Concepts

Students are put in the role of a manager who watches inventory levels decrease and must order at the right time and in the right quantity to minimize costs. This interactive game requires the students to race against time and has levels of increasing difficulty. It introduces the students to the concepts of holding cost, ordering cost, backlog cost, the sawtooth curve, reorder point, order quantity, ABC categorization, and continuous review systems. The game is simple and is available free online. An accompanying assignment is designed to guide the student's reflection process while playing the game.     

解非线性方程的一类改进型牛顿法

牛顿迭代法的改进形式主要有算术平均牛顿法(AN)、几何平均牛顿法(GN)、中点牛顿法(MN)、调和平均牛顿法(HN)、α-幂平均牛顿法(PN)等.通过将算术平均牛顿法(AN)与经典牛顿法结合,提出一种新的牛顿型算法,收敛阶可达6阶.与现有算法相比较,该算法具有计算量少、收敛速度快的优点.     

An Existence Theorem for Strongly Nonlinear Implicit Complementarity Problems

A class of strongly nonlinear implicit complementarity problems for set-valued mappings in Hilbert spaces is studied. Thereupon a new existence theorem is established and proved to be a solution to that kind of problems.     

求拟合曲线的一种代数方法

文本介绍一种十分简捷的代数方法,给出一个求拟合曲线的系数公式。该方法与回归分析中常用的方法相比更简便适用。     

由一道习题引发的思考

就学生对一道习题的错误认识给予纠正,并分析其出错的原因．     

求解非线性方程的单参数类方法的一个改进

基于二次曲线,推导出了求解非线性方程的一类带参数的迭代公式,给出了算法的收敛性分析。新的迭代公式允许在所求根的邻域内出现导数为零的情况。数值试验表明新方法是非常有效的。     

Using Regression Discontinuity to Test the Impact of a Tier 2 Reading Intervention in First Grade

Abstract

?Multitiered systems of reading instruction and intervention, including response to intervention, are widely used in early reading by schools to provide more intense services to students who need them. Research using randomized controlled trials has compared innovative Tier 2 interventions to business-as-usual Tier 2 approaches and established a number of important components that compose effective Tier 2 interventions in early reading. The purpose of this study was to test the impact of a Tier 2 intervention with Tier 2 compared to Tier 1 instruction alone using regression discontinuity. A cut score was used to assign first-grade students at risk for reading difficulties to Tier 2 intervention plus Tier 1 instruction. Students who missed the cut score in the control group received Tier 1 instruction only. Students in the treatment group, just below the cut score, made greater gains on the SAT10 total score and the individual subtests than students just above the cut score. Outcomes were not significant on oral reading fluency.