基于因果关系的教育研究方法思考

探索、检验因果关系是教育科学研究的重要目标之一,相关分析、回归分析、路径分析等常用统计方法存在许多不足。结构方程模型是针对这些不足提出来的,从统计思路上,它具有优点,但还不够完善,应引起我国教育学界的注意。     

几类矩阵的研究及其应用

对几类矩阵进行了刻划；对于非负阵谱半径的一个重要性质￣［１］，给出了新的简单证明；作为应用，得到有重要实际意义的某些类矩阵之逆的谱半径的界的估计。     

Uncertainty Analysis for Computer Model Projections of Hurricane Losses

Projecting losses associated with hurricanes is a complex and difficult undertaking that is wrought with uncertainties. Hurricane Charley, which struck southwest Florida on August 13, 2004, illustrates the uncertainty of forecasting damages from these storms. Due to shifts in the track and the rapid intensification of the storm, real-time estimates grew from 2 to 3 billion dollars in losses late on August 12 to a peak of 50 billion dollars for a brief time as the storm appeared to be headed for the Tampa Bay area. The storm hit the resort areas of Charlotte Harbor near Punta Gorda and then went on to Orlando in the central part of the state, with early poststorm estimates converging on a damage estimate in the 28 to 31 billion dollars range. Comparable damage to central Florida had not been seen since Hurricane Donna in 1960. The Florida Commission on Hurricane Loss Projection Methodology (FCHLPM) has recognized the role of computer models in projecting losses from hurricanes. The FCHLPM established a professional team to perform onsite (confidential) audits of computer models developed by several different companies in the United States that seek to have their models approved for use in insurance rate filings in Florida. The team's members represent the fields of actuarial science, computer science, meteorology, statistics, and wind and structural engineering. An important part of the auditing process requires uncertainty and sensitivity analyses to be performed with the applicant's proprietary model. To influence future such analyses, an uncertainty and sensitivity analysis has been completed for loss projections arising from use of a Holland B parameter hurricane wind field model. Uncertainty analysis quantifies the expected percentage reduction in the uncertainty of wind speed and loss that is attributable to each of the input variables.     

经济增长差异与农产品比较优势

随着我国加入世贸组织 ,农产品比较优势问题在国内得到普遍的关注。然而 ,由于存在经济增长差异 ,有比较优势的产品 ,在国际市场上不一定有竞争优势。因此 ,要把我国农业培植成具有国际竞争力的产业 ,就必须把现有的比较优势转化为竞争优势。     

英语成绩与焦虑特性的相关性研究

文章以南华大学外国语学院英语专业二年级 4 4名本科生为对象 ,用SPSS统计软件包分析研究了学生英语成绩及若干专业技能与焦虑特性的相关性。研究结果表明 :( 1)学生英语成绩与焦虑特性呈中度负相关 ;( 2 )在听写、听力、阅读、写作这四项单项能力方面 ,听写和听力是与焦虑特性相关性最高的两个 ,而完形填空、词汇与结构与焦虑特性不相关。     

图式理论、学习策略与大学英语口语教学

本研究采用定量分析的方法,对84名天水师范学院非英语专业的学生的口语水平进行测试。根据图式理论,口语任务分为有关键词及句型提示类和无提示类,并对被试的学习策略使用情况做了调查,结果发现,口语任务有提示与无提示对学生的口语成绩有显著影响,这说明图式理论完全适用于大学英语口语教学。     

An affine‐invariant multivariate sign test for cluster correlated data

The author presents a multivariate location model for cluster correlated observations. He proposes an affine‐invariant multivariate sign statistic for testing the value of the location parameter. His statistic is an adaptation of that proposed by Randles (2000). The author shows, under very mild conditions, that his test statistic is asymptotically distributed as a chi‐squared random variable under the null hypothesis. In particular, the test can be used for skewed populations. In the context of a general multivariate normal model, the author obtains values of his test's Pitman asymptotic efficiency relative to another test based on the overall average. He shows that there is an improvement in the relative performance of the new test as soon as intra‐cluster correlation is present Even in the univariate case, the new test can be very competitive for Gaussian data. Furthermore, the statistic is easy to compute, even for large dimensional data. The author shows through simulations that his test performs well compared to the average‐based test. He illustrates its use with real data.     

A spatiotemporal auto-regressive moving average model for solar radiation

Summary.  To investigate the variability in energy output from a network of photovoltaic cells, solar radiation was recorded at 10 sites every 10 min in the Pentland Hills to the south of Edinburgh. We identify spatiotemporal auto-regressive moving average models as the most appropriate to address this problem. Although previously considered computationally prohibitive to work with, we show that by approximating using toroidal space and fitting by matching auto-correlations, calculations can be substantially reduced. We find that a first-order spatiotemporal auto-regressive (STAR(1)) process with a first-order neighbourhood structure and a Matern noise process provide an adequate fit to the data, and we demonstrate its use in simulating realizations of energy output.     

Some results on optimality in models with heteroscedastic errors from partial optimum designs

This paper studies optimum designs for linear models when the errors are heteroscedastic. Sufficient conditions are given in order to obtainD-, A- andE-optimum designs for a complete regression model from partial optimum designs for some sub-parameters. A result about optimality for a complete model from the optimality for the submodels is included. Supported by Junta de Andalucía, research group FQM244.     

A note on measures of similarity based on centrality

This note presents a measure of similarity between connected nodes in terms of centrality based on Euclidean distances, and compares it to ‘assortative mixing’ [Newman, M.E.J., 2002. Assortative mixing in networks. Physical Review Letters 89, 208701], which is based on Pearson correlation coefficient. This study suggests that the measure based on Euclidean distances may be more appropriate for relatively smaller (N < 500) and denser networks.