Improving Students' Data Analysis and Presentation Skills: The Ocean State Circuits,Inc. Forecasting Project

Many potential employers expect that newly hired students will arrive on‐the‐job with the ability to analyze data, utilize spreadsheets, and communicate findings and recommendations. We designed the Ocean State Circuits, Inc. Forecasting Project to address these gaps in our students’ knowledge of analytical tools (such as the vlookup() function and pivot tables), their ability to write mathematical formulas in a spreadsheet, their understanding of more advanced data analysis features (e.g., regression, correlation), and their ability to communicate and present managerial conclusions. The exercise requires student teams to act as “consultants” and utilize spreadsheets to analyze and forecast the demand for a hypothetical set of products and then communicate their findings to “management” in a professionally formatted report document. A survey of students that have completed the exercise indicates that their knowledge level of the tools used in the project increased significantly from before to after they completed the case. Similarly, anecdotal feedback from employers suggests that students that have completed the exercise seem more capable of dissecting data when investigating business issues.     

师资因素对公共计算机基础课程教学效果的影响

该文以2007学年度湖南省高校计算机水平等级考试成绩和各高校的计算机公共课专任教师为研究对象,利用专业统计软件SPSS寻找两者之间的关联,发现不同年龄、学历和职称层次的师资在一定程度上影响学生的考试成绩,利用这一结论可以有的放矢培养和优化教师队伍,为教学改革提供决策依据。     

教育统计学在高校教学效果评价中的应用研究

根据目前我国高校青年教师教学效果工作评价体系的不够健全、完善的现状,运用教育统计学原理,设定德、能、勤、绩等几个考评因素,来更加客观、合理、公平、公正地对体育教师工作进行考评,进一步提高广大青年教师的工作积极性,来进一部完善高校的教学评价体系。     

利用统计软件SPSS进行试卷质量分析

试卷质量分析是教学中的一项重要任务,也是教学效果检查的重要依据.质量好的试卷才能准确地反映出学校的教学水平和学生的学习效果.本文抽取我校2007级国际贸易专业两个班级共90份<统计学>考卷作为样本,利用统计软件SPSS13.0来分析试卷的质量,重点演示包括数据录入、分析成绩分布、试卷难度、区分度、信度及效度等内容,从而科学地进行试卷质量分析,提高教学质量和效率.     

Stochastic synchronization of semi-Markovian jump chaotic Lur’e systems with packet dropouts subject to multiple sampling periods

This paper is concerned with the problem of stochastic synchronization for semi-Markovian jump chaotic Lur’e systems. Firstly, packet dropouts and multiple sampling periods are both considered. By input-delay approach and then fully considering the probability distribution characteristic of packet dropouts in the modeling, the original system is transformed to a stochastic time-delay system. Secondly, by getting the utmost out of the usable information on the actual sampling pattern, the probability distribution values of stochastic delay taking values in m given intervals can be explicitly obtained. Then, a newly augmented Lyapunov-Krasovskii functional is constructed. Based on that, some sufficient conditions in terms of linear matrix inequalities (LMIs) are derived to ensure the stochastic stability of the error system, and thus, the master system stochastically synchronize with the slave system. Finally, the effectiveness and potential of the obtained results is verified by a simulation example.     

Threshold behavior in a stochastic delayed SIS epidemic model with vaccination and double diseases

In this paper, we investigate the threshold dynamics of a stochastic delayed SIS epidemic model with vaccination and double diseases which make the research more difficult. We establish sufficient conditions for extinction and persistence in the mean of the two diseases. We also obtain the threshold between persistence in the mean and extinction of the stochastic system. It is shown that: (i) time delay and environmental white noise have important effects on the persistence and extinction of the two diseases; (ii) the two diseases can coexist under certain conditions. Finally, some numerical simulations are provided to demonstrate the analytical results.     

Design of memory controllers for finite-time stabilization of delayed neural networks with uncertainty

In this paper, we investigate the problem of finite-time stabilization of time-varying delayed neural networks with uncertainty. By employing the Lyapunov approach and linear matrix inequalities (LMIs), two different memory controllers are derived to achieve the finite-time stabilization of the addressed neural networks. Moreover, the upper bound of the setting-time for stabilization can be estimated via different Lyapunov functions. Our results improve and extend some recent works. Finally, the effectiveness and feasibility of the proposed controllers are demonstrated by numerical simulations.     

基于火炬统计的广东高新技术企业发展研究

全面分析2010—2015年国家火炬统计数据,发现"十二五"期间广东高新技术企业总量快速增长,主要经济科技指标均位居全国前列,整体呈现行业、领域、区域、规模、类型集聚发展的态势,但企业竞争力不够强、区域发展仍欠协调等仍制约着高企快速腾飞。基于广东高企发展特征与存在问题,提出做优存量、做强龙头、做大中小企业、做好顶层设计等"四做"对策,以期进一步优化高企增量和调整高企存量,促进广东产业向中高端发展。     

Randomization‐based statistical inference: A resampling and simulation infrastructure

Statistical inference involves drawing scientifically‐based conclusions describing natural processes or observable phenomena from datasets with intrinsic random variation. We designed, implemented, and validated a new portable randomization‐based statistical inference infrastructure ( http://socr.umich.edu/HTML5/Resampling_Webapp ) that blends research‐driven data analytics and interactive learning, and provides a backend computational library for managing large amounts of simulated or user‐provided data. We designed, implemented and validated a new portable randomization‐based statistical inference infrastructure ( http://socr.umich.edu/HTML5/Resampling_Webapp ) that blends research‐driven data analytics and interactive learning, and provides a backend computational library for managing large amounts of simulated or user‐provided data. The core of this framework is a modern randomization webapp, which may be invoked on any device supporting a JavaScript‐enabled web browser. We demonstrate the use of these resources to analyse proportion, mean and other statistics using simulated (virtual experiments) and observed (e.g. Acute Myocardial Infarction, Job Rankings) data. Finally, we draw parallels between parametric inference methods and their distribution‐free alternatives. The Randomization and Resampling webapp can be used for data analytics, as well as for formal, in‐class and informal, out‐of‐the‐classroom learning and teaching of different scientific concepts. Such concepts include sampling, random variation, computational statistical inference and data‐driven analytics. The entire scientific community may utilize, test, expand, modify or embed these resources (data, source‐code, learning activity, webapp) without any restrictions.