用EXCEL设计教学督导评价表

学生评教是教学督导的一个很重要的方面,然而其数据统计的工作量却是比较大的,大多数从事教学督导的工作人员都是教育教学工作的专家,而对计算机专业统计软件和编程语言并不精通,造成教学评教统计工作滞后。教学督导组通过几年的实践和研究,发现利用EXCEL强大的数据处理功能,让学生快速输入数据,减少差错,提高数据的统计效率,为教学督导工作的开展奠定基础。     

大数据与农林院校统计学专业建设研究 ——基于2015年安徽农业大学统计专业大数据问卷调查

在大数据视角下,针对安徽农业大学统计学专业教学中存在的问题,利用2015年安徽农业大学统计学专业调查数据,从安徽农业大学统计专业学生的背景,对统计专业课程的学习情况,对大数据与统计专业课程的期望及就业期望四个方面定量分析统计专业学生对大数据及专业课程的了解程度,研究发现,目前统计专业学生对统计系的专业课程认可度不够高,对大数据技术相关课程需求较高,大部分统计专业学生期望从事与本专业相关的工作,并期望老师能够在日常教学中加强对大数据技术的介绍与渗透.     

统计与概率初步

统计是研究如何收集、整理、描述和分析数据,并在此基础上作出推断或预测的学科．统计的特点就是与数据打交道,统计的基本思想是用样本估计总体．在数据的收集和整理过程中,我们利用列表,画折线图、条形图或扇形图等形象化手段,将所收集的数据进行整理与描述;然后通过对平均数、中位数和众数的认识,了解数据的集中趋势;通过对方差、频数、频率以及它们的分布,来了解数据的波动变化和分布情况．在此基础上,进行统计分析,对试验结果作出评估和预测,完成统计工作全过程。     

基于大数据的统计分析模型设计

统计是利用尽可能少的局部样本数据来发现总体规律,处理对象往往数据规模小且数据结构单一。在大数据环境下,面临海量数据的采集与统计,传统方法已无法满足大规模数据集处理。基于Hadoop系统,利用其分布式存储和并行处理机制,设计了大数据环境下的统计分析模型,从海量数据中提取出有用的信息特征,实现数据资源共享,为相关部门决策提供信息服务。     

浅谈如何运用Excel电子表格做好人事档案信息统计工作

利用现代化办公系统,实现人事档案信息管理工作的办公自动化,成为高校人事管理发展的必然趋势。本文结合工作实践,利用Excel电子表格提供了的统计函数和数据统计分析工具,介绍了Excel电子表格在人事档案信息统计工作中的应用。     

浅谈档案利用数据统计与实际效益

收集和管理档案的根本目的 ,主要是为了开发与利用。而在档案信息资源开发利用工作中,存在着传统式的被动服务形式和不重视档案利用信息反馈的问题,严重影响着档案信息资源的开发与利用,以及信息的反馈。据此,笔者重点对档案利用数据统计与档案实际效益作以探讨。     

县乡公路固定资产投资报表的质量和对策

统计报表是统计工作的基本载体。县乡公路固定资产投资报表数据是体现县乡公路发展成就最直观、科学、理性的成果,而基层统计报表是统计调查工作的重要来源,所以,基层统计报表质量的好与坏,直接影响到县乡公路固定资产投资统计工作的成效。     

联合国教科文组织倡导加大教育数据投资

<正>联合国教科文组织统计研究所近日提出,世界需要标准和方法,以确保教育数据准确、始终按性别分类、与政策相关并具有国际可比性。那些尚未评估学习情况的国家可能不得不做出一些改变,以便生成符合其自身需要又与国际标准保持一致的学习数据。据悉,加拿大全球事务部将在今后4年中每年提供100万加元,以支持联合国教科文组织统计研究所的教育数据工作,尤其是按性别分类的数据和性别统计。法国和挪威也致力于将教育作为一项基本人权,更好地利用教育数据的力量。瑞典     

用Excel进行数据的录入与汇总

在我们的日常工作和学习过程中,可能会经常遇到对某些数据进行统计的工作,包括求和、按一定要求求和、计算平均数、按一定要求计算平均数等等。做好数据统计工作首先要做好数据的录入,在保证准确录入的前提下才能做好数据的统计工作。下面以学生学习成绩的统计为例来说明一下如何用好Excel来对数据进行录入与汇总。     

基于VBA的成绩分析的实现及演示文稿的生成

成绩分析是每次考试之后教师的首要工作,利用Office内置的VBA,实现了成绩分析,并且利用统计后的数据自动生成PowerPoint演示文稿,极大地提高了成绩分析的工作效率．     

我国基层统计市场主导模式建设初探

基层统计市场主导模式是由政府规范、市场主导、中介执业的基层统计生产管理模式。它是基层统计生产方式和管理方式的重大变革,对于完善我国统计管理理论,推动基层统计制度、体制机制创新具有深远的理论意义,同时对于稳固统计基础,提高宏观统计数据质量和政府统计公信力都有十分重要的现实意义。     

Evaluation of a New Mean Scaled and Moment Adjusted Test Statistic for SEM

Recently a new mean scaled and skewness adjusted test statistic was developed for evaluating structural equation models in small samples and with potentially nonnormal data, but this statistic has received only limited evaluation. The performance of this statistic is compared to normal theory maximum likelihood and 2 well-known robust test statistics. A modification to the Satorra–Bentler scaled statistic is developed for the condition that sample size is smaller than degrees of freedom. The behavior of the 4 test statistics is evaluated with a Monte Carlo confirmatory factor analysis study that varies 7 sample sizes and 3 distributional conditions obtained using Headrick's fifth-order transformation to nonnormality. The new statistic performs badly in most conditions except under the normal distribution. The goodness-of-fit χ² test based on maximum-likelihood estimation performed well under normal distributions as well as under a condition of asymptotic robustness. The Satorra–Bentler scaled test statistic performed best overall, whereas the mean scaled and variance adjusted test statistic outperformed the others at small and moderate sample sizes under certain distributional conditions.     

Evaluation of Test Statistics for Robust Structural Equation Modeling With Nonnormal Missing Data

A 2-stage robust procedure as well as an R package, rsem, were recently developed for structural equation modeling with nonnormal missing data by Yuan and Zhang (2012). Several test statistics that have been used for complete data analysis are employed to evaluate model fit in the 2-stage robust method. However, properties of these statistics under robust procedures for incomplete nonnormal data analysis have never been studied. This study aims to systematically evaluate and compare 5 test statistics, including a test statistic derived from normal-distribution-based maximum likelihood, a rescaled chi-square statistic, an adjusted chi-square statistic, a corrected residual-based asymptotical distribution-free chi-square statistic, and a residual-based F statistic. These statistics are evaluated under a linear growth curve model by varying 8 factors: population distribution, missing data mechanism, missing data rate, sample size, number of measurement occasions, covariance between the latent intercept and slope, variance of measurement errors, and downweighting rate of the 2-stage robust method. The performance of the test statistics varies and the one derived from the 2-stage normal-distribution-based maximum likelihood performs much worse than the other four. Application of the 2-stage robust method and of the test statistics is illustrated through growth curve analysis of mathematical ability development, using data on the Peabody Individual Achievement Test mathematics assessment from the National Longitudinal Survey of Youth 1997 Cohort.     

民国时期政府统计工作与统计资料述论

民国时期,中国的统计体制逐步建立起来。尤其是在南京国民政府主计处成立以后,统计法规的制定、统计机构的设置、统计方法的统一、统计期刊的编印等都取得了明显的成绩,官方开展了大量调查统计工作,编印完成卷帙浩繁的各类统计资料。民国时期的政府统计资料既有部门性的,也有综合性的,涉及社会发展与变迁的方方面面,在民国史研究中的价值远未充分发掘出来。这类史料为比较方法、计量方法的应用提供了便利,不仅社会史之类史料基础相对薄弱的研究领域可以直接扎根其中,就是史料基础已很扎实的政治史、经济史等亦能从中受益。政府统计资料在民国史研究中的利用也面临不少困难,其考证、整理的任务仍然非常艰巨。     

A New Statistic for Detection of Aberrant Answer Changes

As noted by Fremer and Olson, analysis of answer changes is often used to investigate testing irregularities because the analysis is readily performed and has proven its value in practice. Researchers such as Belov, Sinharay and Johnson, van der Linden and Jeon, van der Linden and Lewis, and Wollack, Cohen, and Eckerly have suggested several statistics for detection of aberrant answer changes. This article suggests a new statistic that is based on the likelihood ratio test. An advantage of the new statistic is that it follows the standard normal distribution under the null hypothesis of no aberrant answer changes. It is demonstrated in a detailed simulation study that the Type I error rate of the new statistic is very close to the nominal level and the power of the new statistic is satisfactory in comparison to those of several existing statistics for detecting aberrant answer changes. The new statistic and several existing statistics were shown to provide useful information for a real data set. Given the increasing interest in analysis of answer changes, the new statistic promises to be useful to measurement practitioners.     

Using an Approximate Chi-Square Statistic to Test the Number of Dimensions Underlying the Responses to a Set of Items

An approximate χ² statistic based on McDonald's (1967) nonlinear factor analytic representation of item response theory was proposed and investigated with simulated data. The results were compared with Stout's T statistic (Nandakumar & Stout, 1993; Stout, 1987). Unidimensional and two-dimensional item response data were simulated under varying levels of sample size, test length, test reliability, and dimension dominance. The approximate χ² statistic had good control over Type I errors when unidimensional data were generated and displayed very good power in identifying the two-dimensional data. The performance of the approximate χ² was at least as good as Stout's T statistic in all conditions and was better than Stout's T statistic with smaller sample sizes and shorter tests. Further implications regarding the potential use of nonlinear factor analysis and the approximate χ² in addressing current measurement issues are discussed.     

加强和改进高校毕业生就业信息统计工作的思考

对我国现行高校毕业生就业信息统计机制进行分析,找出其存在的问题,然后再提出一些合理化设想,并进一步提出改进信息统计分析的方法,使得高校毕业生就业信息统计分析数据更具科学性和合理性,对政府的人才决策和高校教育教学改革等方面更加具有指导意义。     

Maximum Likelihood Estimation of Structural Equation Models for Continuous Data: Standard Errors and Goodness of Fit

Classical accounts of maximum likelihood (ML) estimation of structural equation models for continuous outcomes involve normality assumptions: standard errors (SEs) are obtained using the expected information matrix and the goodness of fit of the model is tested using the likelihood ratio (LR) statistic. Satorra and Bentler (1994) introduced SEs and mean adjustments or mean and variance adjustments to the LR statistic (involving also the expected information matrix) that are robust to nonnormality. However, in recent years, SEs obtained using the observed information matrix and alternative test statistics have become available. We investigate what choice of SE and test statistic yields better results using an extensive simulation study. We found that robust SEs computed using the expected information matrix coupled with a mean- and variance-adjusted LR test statistic (i.e., MLMV) is the optimal choice, even with normally distributed data, as it yielded the best combination of accurate SEs and Type I errors.     

我国卫生资源配置公平性现状分析

卫生资源的公平配置是我国建设和谐社会的重要内容之一.研究根据历年的统计数据,采用国内外公平性研究的统计分析方法,对我国主要卫生资源在各省市自治区配置的公平性进行了分析.分析结果表明:本世纪来,我国三项主要卫生资源指标(医疗机构床位、执业(助理)医师、注册护士)在各省市自治区配置是基本公平的,并且公平性在逐年提高.     

Empirical Validation of DIMTEST on Nonnormal Ability Distributions

DIMTEST is a nonparametric statistical test procedure for assessing unidimensionality of binary item response data. The development of Stout's statistic, T, used in the DIMTEST procedure, does not require the assumption of a particular parametric form for the ability distributions or the item response functions. The purpose of the present study was to empirically investigate the performance of the statistic T with respect to different shapes of ability distributions. Several nonnormal distributions, both symmetric and nonsymmetric, were considered for this purpose. Other factors varied in the study were test length, sample size, and the level of correlation between abilities. The results of Type I error and power studies showed that the test statistic T exhibited consistently similar performance for all different shapes of ability distributions investigated in the study, which confirmed the nonparametric nature of the statistic T.