Rankings - Statistics - Premium Graduate Schools - Education - US News
USNews_StatisticsRankings 统计学排名
Rank within Statistics University OverallRank1 StanfordUniversity 12 University of California, Berkeley 23 HarvardUniversity 6 3 University of Chicago 63 University of Washington 66 Carnegie Mellon University 97 DukeUniversity 10 8 North Carolina State University 128 Texas A&M University 128 University of Pennsylvania 128 University of Wisconsin 1212 University of Michigan 1712 University of Minnesota 1714 Iowa State University 2014 Penn State University 2016 ColumbiaUniversity 22 16 CornellUniversity 22 16 PurdueUniversity 22 16 University of North Carolina 2220 The Ohio State University 2720 University of California, Los Angeles 2720 University of Florida 2723 University of California at Davis 3124 University of Illinois at Urbana-Champaign 3324 University of Iowa 3324 YaleUniversity 33 27 RutgersUniversity 37 28 RiceUniversity 38 29 Colorado State University 4029 Florida State University 4029 University of Connecticut 4032 Michigan State University 4433 University of Pittsburgh 4534 George Washington University 4834 NorthwesternUniversity 48 34 University of Georgia 4834 University of Missouri 4834 Virginia Polytechnic Institute and State University 4839 Southern Methodist University 5340 University of California, Santa Barbara 5541 University of South Carolina 5742 Oregon State University 5842 University of California, Riverside 5842 University of Virginia 5845 Kansas State University 62University 6245 TempleUniversity 6447 Baylor47 University of Kentucky 6449 Case Western Reserve University 6749 Oklahoma State University 67North Dakota State University RNPThe University of Alabama RNPUniversity of Nebraska RNPWestern Michigan University RNPThese are rankings derived from the US News & World Report rankings (/best-graduate-schools/top-statistics-schools/rankings/). They are for US Departments of Statistics that have granted at least one Ph.D. in each of the past five years.RNP denotes departments for which there was insufficient information to provide a ranking.Additional information, including the scores and methodology are available at the US News site referenced above.。
美国大学GPA排名
美国大学GPA排名导读：本文美国大学GPA排名，仅供参考，如果觉得很不错，欢迎点评和分享。
1. 加州理工学院(California Institute of Technology)学生平均GPA：3.933录取率：10.6%学校人数：2,209新生人数：226平均SAT成绩：2230 - 2390学校位置：加州，帕萨迪纳学费：$43,3622.麻省理工学院(Massachusetts Institution of Technology)学生平均GPA：3.924录取率：8.2%学校人数：11,319新生人数：1,043平均SAT成绩：2110 - 2350学校位置：马萨诸塞州，剑桥学费：$45,0163. 哈维穆德学院(Harvey Mudd College)学生平均GPA：3.919录取率：18.2%学校人数：804新生人数：195平均SAT成绩：2098 - 2330学校位置：加州，克莱尔蒙特学费：$48,5944. 杜克大学(Duke University)学生平均GPA：3.911录取率：13.4%学校人数：15,856新生人数：1,721平均SAT成绩：2060 - 2330学校位置：北卡罗来纳州，杜伦学费：$47,2435. 宾夕法尼亚大学(University of Pennsylvania)学生平均GPA：3.894录取率：9.9%学校人数：24,806新生人数：2,425平均SAT成绩：2050 - 2330学校位置：宾夕法尼亚州，费城学费：$47,668。
qs世界大学排名评价指标
qs世界大学排名评价指标
qs世界大学排名的评估指标如下：
1、Academic Reputation 学术声誉（所占比重为40%）
2、Employer Reputation 雇主声誉（所占比重为10%）
3、Faculty/Student Ratio师生比（所占比重为20%）
4、Citations per faculty文献引用数（所占比重为20%）
5、International Faculty Ratio国际教职工比例（所占比重为5%）
6、International Student Ratio国际生比例（所占比重为5%）
QS世界大学排名简介：
QS世界大学排名（QS World University Rankings）是由英国一家国际教育市场咨询公司Quacquarelli Symonds（简称QS）所发表的年度世界大学排名。
QS公司最初与泰晤士高等教育（简称THE）合作，共同推出《THE-QS世界大学排名》，首次发布于2004年，是相对较早的全球大学排名；2010年起，QS和THE终止合作，两者开始发表各自的世界大学排名。
QS全球教育集团一般每年夏季会进行排名更新。
the参考指标
"THE"排名是全球公认的大学评价体系，其参考指标分为五个一级指标：教学、研究、引用、国际展望和产业收入。
在2024年的排名中，这五个一级指标的权重分配分别为：教学占30%，研究占30%，引用占30%，国际展望占7.5%，产业收入占2.5%。
具体来说，“引用”这个一级指标被细化为四个二级指标，分别是研究实力、卓越研究、研究影响力以及专利相关指标。
其中，“研究实力”考察大学整体的引用情况——取大学所有出版物的75%分位数的FWCI；“卓越研究”考察大学在顶尖研究的贡献——取前10% FWCI的论文数量；“研究影响力”考察大学论文被重要论文引用的程度；而新的二级指标“专利”则是衡量一所大学的研究被专利引用的数量。
此外，“产业收入”这个一级指标也引入了一个新的二级指标：“专利”，该指标是衡量一所大学的研究被专利引用的数量。
这些变动使得THE排名更全面地反映了大学的教学质量、研究能力以及与产业的联动效应等方面的表现。
马来留学专业术语
马来留学专业术语
以下是一些在马来西亚留学中可能会遇到的术语和缩写：
1. KPT：这是一个马来西亚教育部设立的项目，旨在为马来西亚公立大学提供更多的博士奖学金。
2. STPM：这是马来西亚高级中学的考试，相当于中国的高考。
3. GPA：这是马来西亚用来评估学生在学术表现的一个标准，全称为Gred Point Average。
4. IELTS：这是国际英语语言测试系统，用于评估学生的英语水平。
5. TOEFL：这是测试英语作为外语的考试，用于评估学生的英语水平。
6. GRE：这是研究生入学考试，用于评估申请攻读研究生学位的学生。
7. GMAT：这是商学院研究生入学考试，用于评估申请攻读商学院研究生学位的学生。
8. O Level：这是马来西亚中学的毕业考试，相当于中国的高中毕业考试。
9. A Level：这是马来西亚高级中学的毕业考试，相当于中国的高考。
10. PLT：这是一个马来西亚教育部设立的项目，旨在为马来西亚公立大学提供更多的博士奖学金。
以上是一些常见的马来西亚留学术语和缩写，希望对你有所帮助。
pennstate university计算公式
Penn State University（宾夕法尼亚州立大学）是一所位于美国宾夕法尼亚州的著名公立大学，其计算机科学、工程学、商科等专业在世界范围内享有盛誉。
本文将介绍Penn State University的计算公式相关信息，希望能为有意向申请该校的学生提供一定的参考。
Penn State University计算公式的相关内容主要包括以下几个方面：1. 入学要求的计算公式：Penn State University对于不同专业的入学要求会有所不同，一般包括GPA、标准化考试成绩等要求。
申请人可以通过以下公式来计算自己的入学资格：入学资格 = GPA x 200 + SAT/ACT成绩 x 10其中GPA为4.0满分制，SAT成绩满分为1600，ACT成绩满分为36。
通过该公式计算后，申请人可以了解自己是否符合Penn State University的入学要求。
2. 奖学金评定公式：在Penn State University中，奖学金的评定将根据学生的成绩、综合素质等多个方面进行综合考量。
一般来说，奖学金的评定公式如下：奖学金金额 = GPA x 1000 + SAT成绩 x 10通过该公式计算后，学生可以初步了解自己获得奖学金的可能性以及奖学金的大致金额。
3. 课程成绩评定公式：在Penn State University中，课程的成绩评定比较注重平时表现和期末考试成绩，一般将平时成绩与期末考试成绩按一定比例综合计算。
具体的课程成绩评定公式如下：总成绩 = 平时成绩 x 0.3 + 期末考试成绩 x 0.7通过该公式计算后，学生可以对自己的课程表现进行有效评估，了解自己在学业上的表现情况。
4. GPA计算公式：在Penn State University中，GPA的计算一般按照以下公式进行：GPA = Σ(课程学分 x 课程成绩) / 总学分其中，Σ表示对所有课程进行求和。
通过该公式计算后，学生可以准确了解自己的GPA情况。
qs世界大学排名的评估指标
qs世界大学排名的评估指标
QS世界大学排名评估指标主要有6项，分别为学术声誉、出版物
引用、研究影响力、师资水平、学生水平和国际性等。
学术声誉：此指标主要考察学校知名度和良好口碑，一般通过对
一批拥有坚实学术背景的国内外学术精英进行调查来衡量大学在学术
界的声誉。
出版物引用：指学校发表的文献被他人引用的数量，isit
Citation Index (SCI)是其中最重要的来源之一。
此指标衡量的是某
个学校的知识产出，及得到共识的水平。
研究影响力：此指标考察学校发表的文献，在主流科学论文中的
出现率，以及被引用的数量。
此指标衡量的是学校的研究影响力，以
及学术事业的重要性。
师资水平：指学校招聘的教师拥有的学历、工作经验及研究成果，以及教学质量等。
此指标衡量学校所聘请教师的学术水平，也反映了
本校的学术信誉。
学生水平：指考入该大学的学生，他们的背景及特点，以及他们
的知识技能和创新能力。
此指标反映了学校教育质量，也是学校学术
发展的根本。
国际性：指学校国际化程度，一般来说，有较强国际化程度的学校，会有较多海外师资及学生，他们会给学校带来较多视野及资源。
此指标反映大学在国际上的名望。
总之，以上评估指标体现了QS世界大学排名对学校实现学术优质
提升的重要意义，体现出学校在国际学术社会中的地位和影响力。
艰难的决定英语作文选大学
艰难的决定英语作文选大学The Difficult Decision of Choosing a UniversityIn the journey of life, we encounter various milestones, and among them, the decision of selecting a university stands tall as a significant milestone. This choice is often fraught with challenges, considering the vast array of options, ranging from the prestige of the institution to its location, course offerings, and extracurricular activities. For many students, it's a balancing act between personal interests, family expectations, and the future prospects of a chosen field.As I stood on this crossroads, faced with the daunting task of picking a university, I realized that it wasn't just about choosing a place to study but also about charting a course for my future. The first consideration was the location. Would I opt for the familiarity of staying close to home or embark on an adventure to a place far away, perhaps even abroad? The pros and cons of each choice were weighted carefully,with considerations such as independence, exploration, and the cost of relocation.Next came the matter of course selection. Would I follow the path of my passions or the one mapped out by society or my loved ones? The pull between following my heart and fulfilling others' expectations was strong. I had to sit with myself and deeply evaluate my interests, strengths, and aspirations. Only then could I make a decision that aligned with my personal growth and happiness.The reputation and rankings of the universities were also crucial factors. Did I want to be part of an institution that boasted high rankings and a prestigious alumni network, or was I more interested in a place that fostered creativity and innovation, regardless of its external label? I had to balance the pull of traditional success metrics with the intangible values of an educational environment.Lastly, the social aspect played a pivotal role. Would I thrive in a diverse, vibrant community or find solace in a smaller, more intimate setting? The university I chose would become my home away from home, and its community would shape my experiences and relationships. After much deliberation and soul-searching, I realized that the right university wasn't just about one factor; it was a harmonious blend of all these elements. It was about finding a place where I could grow, learn, and thrive, both personally and professionally. The difficult decision of choosing a university, therefore, boiled down to understanding oneself and what one truly desired from this crucial chapter of life.In conclusion, choosing a university is not just about education; it's about finding one's place in the world. It's about understanding oneself, one's dreams, and aspirations. It's about weighing the pros and cons, balancing personal and external expectations, and making a choice that aligns with one's heart and future goals. It's a challenging decision, but one that, with care and thoughtfulness, can lead to immense fulfillment and growth.。
重要水平的名词解释
重要水平的名词解释在我们的日常生活中，我们会遇到很多的名词，这些名词往往是特定领域的专业术语，对于大部分人来说可能不太容易理解。
本文将重点解释一些重要水平的名词，以便我们更好地理解和认识它们。
一、重要水平重要水平，也称为显著性水平或α水平，是在统计学中常用的一个概念。
它代表着我们在假设检验时所接受的错误的概率。
一般情况下，我们所设定的重要水平是0.05或0.01。
当我们进行假设检验时，我们会根据样本数据来判断某个假设是否成立。
在这个过程中，我们会计算出一个p值。
如果p值小于我们设定的重要水平，就意味着我们可以拒绝原假设，即我们认为样本数据与原假设有显著差异。
二、零假设和备择假设在统计学中，假设检验是非常重要的一部分。
而对于任何一个假设检验，我们都会有两个假设：零假设和备择假设。
零假设通常表示我们认为不存在任何效应或差异，即我们认为样本数据与原假设没有显著差异。
备择假设则相反，表示我们认为存在某种效应或差异。
在进行假设检验时，我们需要根据样本数据来判断两个假设的可行性。
如果样本数据与零假设相符，我们就接受零假设；如果样本数据与备择假设相符，我们就拒绝零假设。
三、置信水平置信水平与重要水平有些类似，它是在估计过程中常用的一个概念。
置信水平代表我们对于参数估计的可信程度。
通常情况下，我们所设定的置信水平是95%或99%。
例如，当我们选择95%置信水平时，意味着我们相信我们的估计值有95%的概率包含了真实的参数值。
置信区间是置信水平的一个常用表达方式。
置信区间是一个范围，我们相信所估计的参数在这个范围内的可能性较大。
置信区间的计算方法一般是基于样本数据和统计模型来进行推断。
四、标准差标准差是描述一个数据集中的数据离散程度的统计量。
它衡量了数据与均值之间的差异程度。
标准差越大，表示数据之间的差异越大；标准差越小，表示数据之间的差异越小。
标准差的计算公式为数据与均值之差的平方和除以数据个数，然后再取平方根。
uq评分标准
uq评分标准UQ评分标准（University of Queensland Grading Scale）是澳大利亚昆士兰大学（The University of Queensland）采用的学术评分系统，用于评估学生的学业表现和成绩。
UQ评分标准通常采用4.0制（4-point scale），分为以下等级：1. HD（High Distinction）：优秀。
表示学生在课程中表现出色，具有卓越的理解力、技能和分析能力。
分数范围一般是85%以上。
2. D（Distinction）：优秀。
表示学生在课程中表现良好，具有良好的理解力、技能和分析能力。
分数范围一般是75%-84%。
3. C（Credit）：中等成绩。
表示学生在课程中表现一般，具有一定的理解力、技能和分析能力。
分数范围一般是65%-74%。
4. P（Pass）：及格。
表示学生在课程中达到最低要求，具备基本的理解力、技能和分析能力。
分数范围一般是50%-64%。
5. F（Fail）：不及格。
表示学生未能达到课程的最低要求，缺乏理解力、技能和分析能力。
分数低于50%。
此外，UQ还使用一些其他等级和符号来表示特殊情况：1. W：代表学生在注销截止日期之前退课。
2. WN：代表学生在注销截止日期之后退课。
3. I（Incomplete）：代表学生因故未能完成课程要求，并已获得特殊批准延期。
4. S（Satisfactory）：代表学生已满足课程要求，但不会计入GPA（Grade Point Average）计算中。
5. NS（Not Satisfactory）：代表学生未能满足课程要求，不会计入GPA计算中。
需要注意的是，具体的评分方式和标准可能因不同课程、学院或专业而有所差异，学生在选课前应了解所在学校的具体评分规则。
统计学基础专业词汇
population---总体sampling unit---抽样单元sample---样本observed value---观测值descriptive statistics---描述性统计量random sample---随机样本simple random sample---简单随机样本statistics---统计量order statistic---次序统计量sample range---样本极差mid-range---中程数estimator---估计量sample median---样本中位数sample moment of order k---k阶样本矩sample mean---样本均值average---平均数arithmetic mean---算数平均值sample variance---样本方差sample standard deviation---样本标准差sample coefficient of variation---样本变异系数standardized sample random variable---标准化样本随机变量sample skewness coefficient---样本偏度系数sample kurtosis coefficient---样本峰度系数sample covariance---样本协方差sample correlation coefficient---样本相关系数standard error---标准误差interval estimator---区间估计statistical tolerance interval---统计容忍区间statistical tolerance limit---统计容忍限confidence interval---置信区间one-sided confidence interval---单侧置信区间prediction interval---预测区间estimate---估计值error of estimation---估计误差bias---偏差unbiased estimator---无偏估计量maximum likelihood estimator---极大似然估计量estimation---估计maximum likelihood estimation---极大似然估计likelihood function---似然函数profile likelihood function---剖面函数hypothesis---假设null hypothesis---原假设alternative hypothesis---备择假设simple hypothesis---简单假设composite hypothesis---复合假设significance level---显著性水平type i error---第一类错误type ii error---第二类错误statistical test---统计检验significance test---显著性检验p-value---p值power of a test---检验功效power curve---功效曲线test statistic---检验统计量graphical descriptive statistics---图形描述性统计量numerical descriptive statistics---数值描述性统计量classes---类(组)class---类(组)class limits; class boundaries---组限mid-point of class---组中值class width---组距frequency---频数frequency distribution---频数分布histogram---直方图bar chart---条形图cumulative frequency---累积频数relative frequency---频率cumulative relative frequency---累积频率sample space---样本空间event---事件complementary event---对立事件independent events---独立事件probability [of an event A]---[事件A的]概率conditional probability---条件概率distribution function [of a random variable x]---[随机变量X的]分布函数family of distributions---分布族parameter---参数random variable---随机变量probability distribution---概率分布distribution---分布expectation---期望p-quantile---p分位数median---中位数quartile---四分位数one-dimensional probability distribution---一维概率分布one-dimensional distribution---一维分布multivariate probability distribution---多维概率分布multivariate distribution---多维分布marginal probability distribution---边缘概率分布marginal distribution---边缘分布conditional probability distribution---条件概率分布conditional distribution---条件分布regression curve---回归曲线regression surface---回归曲面discrete probability distribution---离散概率分布discrete distribution---离散分布continuous probability distribution---连续概率分布continuous distribution---连续分布probability [mass] function---概率函数mode of probability [mass] function---概率函数的众数probability density function---概率密度函数mode of probability density function---概率密度函数的众数discrete random variable---离散随机变量continuous random variable---连续随机变量centred probability distribution---中心化概率分布centred random variable---中心化随机变量standardized probability distribution---标准化概率分布standardized random variable---标准化随机变量moment of order r---r阶[原点]矩means---均值moment of order r = 1---一阶矩mean---均值variance---方差standard deviation---标准差coefficient of variation---变异系数coefficient of skewness---偏度系数coefficient of kurtosis---峰度系数joint moment of order r and s---(r,s)阶联合[原点]矩joint central moment of order r and s---(r,s)阶联合中心矩covariance---协方差correlation coefficient---相关系数multinomial distribution---多项分布binomial distribution---二项分布poisson distribution---泊松分布hypergeometric distribution---超几何分布negative binomial distribution---负二项分布normal distribution, gaussian distribution---正态分布standard normal distribution, standard gaussian distribution---标准正态分布lognormal distribution---对数正态分布t distribution, student's distribution---t分布degrees of freedom---自由度f distribution---f分布gamma distribution---伽玛分布，t分布chi-squared distribution---卡方分布，x²分布exponential distribution---指数分布beta distribution---贝塔分布，β分布uniform distribution, rectangular distribution---均匀分布type i value distribution, gumbel distribution---i型极值分布type ii value distribution, gumbel distribution---ii型极值分布weibull distribution---韦布尔分布type iii value distribution, gumbel distribution---iii型极值分布multivariate normal distribution---多维正态分布bivariate normal distribution---二维正态分布standard bivariate normal distribution---标准二维正态分布sampling distribution---抽样分布probability space---概率空间analysis of variance (anova)---方差分析covariance---协方差correlation coefficient---相关系数linear regression---线性回归multiple regression---多元回归logistic regression---逻辑回归principal component analysis (pca)---主成分分析cluster analysis---聚类分析factor analysis---因子分析bayesian statistics---贝叶斯统计time series analysis---时间序列分析non-parametric statistics---非参数统计survival analysis---生存分析data mining---数据挖掘machine learning---机器学习big data---大数据decision tree---决策树random forest---随机森林support vector machine (svm)---支持向量机neural network---神经网络deep learning---深度学习outlier detection---异常值检测cross validation---交叉验证moment---矩conditional probability---条件概率joint distribution---联合分布marginal distribution---边缘分布bayes' theorem---贝叶斯定理central limit theorem---中心极限定理law of large numbers---大数定律likelihood function---似然函数consistent estimator---一致性估计point estimation---点估计interval estimation---区间估计decision theory---决策理论bayesian estimation---贝叶斯估计sequential analysis---序列分析stochastic process---随机过程markov chain---马尔可夫链poisson process---泊松过程random sampling---随机抽样stratified sampling---分层抽样systematic sampling---系统抽样cluster sampling---簇抽样nonparametric test---非参数检验chi-square test---卡方检验t-test---t 检验f-test---f 检验。
历年加权平均学分绩点英文名称
历年加权平均学分绩点英文名称The English name for the cumulative weighted average grade point (CGPA) is Cumulative Grade Point Average (CGPA). CGPA is a commonly used metric in higher education institutions to assess a student's academic performanceover their entire academic career. It is calculated by averaging the grade points received for all courses taken, weighted by the credit hours associated with each course.The importance of CGPA lies in its ability to provide a comprehensive overview of a student's academic performance. It takes into account not only the grades achieved in individual courses but also the difficulty level and credit hours associated with those courses. CGPA serves as a reliable indicator of a student's academic standing and can be used to compare students' performance across different programs or institutions.When calculating CGPA, grade points are typically awarded on a scale that varies between institutions. Forexample, some institutions may award 4.0 grade points foran A grade, 3.0 for a B grade, 2.0 for a C grade, and so on. The credit hours associated with each course are also considered, as some courses may be worth more credits than others.The calculation of CGPA involves adding up the grade points received for all courses taken and dividing them by the total credit hours attempted. This gives a weighted average that takes into account both the grades and the credit hours of each course. The resulting CGPA provides a single number that represents the student's overall academic performance.CGPA is often used by universities and employers as a measure of a student's academic ability and commitment.High CGPA scores can indicate strong academic performance and may increase a student's chances of being admitted to competitive programs or securing employment opportunities. However, it is important to note that CGPA is not the only factor considered when evaluating a student's performanceor abilities. Other factors such as extracurricularactivities, leadership roles, and work experience can also play a significant role in a student's success.In conclusion, CGPA is a valuable metric that provides a comprehensive overview of a student's academic performance. It takes into account the grades, difficulty level, and credit hours associated with all courses taken and provides a single number that represents the student's overall academic standing. While it is an important factor in evaluating a student's performance, it should not be the sole criterion for assessing their abilities or potential.。
世界大学评分标准
World University Rankings 2015-2016methodologyChange for the better: fuelled by more comprehensive data, the 2015-2016 rankings probe deeper than everSeptember 24, 2015Source: Peter GrundyTheTimes Higher EducationWorld University Rankings are the only global performance tables that judge research-intensive universities across all their core missions: teaching, research, knowledge transfer and international outlook. We use 13 carefully calibrated performance indicators to provide the most comprehensive and balanced comparisons, trusted by students, academics, university leaders, industry and even governments. The basic methodology for this year’s rankings is similar to that employed since the 2011-12 tables, but we have made important changes to the underlying data. The performance indicators are grouped into five areas:Teaching thelearning environmentResearch volume, income and reputationCitations research influenceInternational outlook staff, students and researchIndustry income knowledge transfer.Note on comparisons with previous yearsBecause of changes in the underlying data, we strongly advise against direct comparisons with previous years’ World University Rankings.ExclusionsUniversities are excluded from the World University Rankings if they do not teach under-graduates or if their research output amounted to fewer than 200 articles per year over the five-year period 2010-14. In exceptional cases, institutions below the 200-paper threshold are included if they have a particular focus on disciplines with generally low publication volumes, such as engineering or the arts.Data collectionInstitutions provide and sign off their institutional data for use in the rankings. On the rare occasions when a particular data point is not provided – which affects only low-weighted indicators such as industrial income –we enter a low estimate between the average value of the indicators and the lowest value reported: the 25th percentile of the other indicators. By doing this, we avoid penalising an institutio n too harshly with a “zero” value for data that it overlooks or does not provide, but we do not reward it for withholding them.Getting to the final resultMoving from a series of specific data points to indicators, and finally toa total score for an institution, requires us to match values that representfundamentally different data. To do this we use a standardisation approach for each indicator, and then combine the indicators in the proportions indicated below.The standardisation approach we use is based on the distribution of data within a particular indicator, where we calculate a cumulative probability function, and evaluate where a particular institution’s indicator sits within that function. A cumulative probability score ofXin essence tells us that a university with random values for that indicator would fall below that scoreXper cent of the time.For all indicators except the Academic Reputation Survey, we calculate the cumulative probability function using a version of Z-scoring. Thedistribution of the data in the Academic Reputation Survey requires us to add an exponential component.Teaching the learning environment: 30%.Reputation survey: 15%.The Academic Reputation Survey run annually that underpins this category was carried out in December 2014 and January 2015. It examined theperceived prestige of institutions in teaching. The responses were statistically representative of the global academy’s geographical and subject mix..Staff-to-student ratio: %.Doctorate-to-bachelor’s ratio: %.Doctorates awarded-to-academic staff ratio: 6%.As well as giving a sense of how committed an institution is to nurturing the next generation of academics, ahigh proportion of postgraduate research students also suggests the provision of teaching at the highest level that is thus attractive to graduates and effective atdeveloping them. This indicator is normalised to take account of a university’s unique subject mix, reflecting that the volume of doctoral awards varies by discipline. .Institutional income: %.This measure of income is scaled against staff numbers and normalised for purchasing-power parity. It indicates an institution’s general status and gives a broad sense of the infrastructure and facilities available to students and staff.Research volume, income and reputation: 30%Reputation survey: 18%The most prominent indicator in this category looks at a university’s reputation for research excellence among its peers, based on the responses to our annual.Research income: 6%Research income is scaled against staff numbers and adjusted for purchasing-power parity PPP. This is a controversial indicator because it can be influenced by national policy and economic circumstances. But income is crucial to the development of world-class research, and because much of it is subject tocompetition and judged by peer review, our experts suggested that it was a valid measure. This indicator is fully normalised totake account of each university’s distinct subject profile, reflecting the fact that research grants in science subjects are often bigger than those awarded for the highest-quality social science, arts and humanities research.Research productivity: 6%We count the number of papers published in the academic journals indexed by Elsevier’s Scopus database per s cholar, scaled for institutional size and normalised for subject. This gives a sense of the university’s ability to get papers published in quality peer-reviewed journals.Citations research influence: 30%Our research influence indicator looks at universi ties’ role in spreading new knowledge and ideas.We examine research influence by capturing the number of times a university’s published work is cited by scholars globally, compared with the number of citations a publication of similar type and subject is expected to have. This year, our bibliometric data supplier Elsevier examined more than 51 million citations to million journal articles, published over five years. The data are drawn from the 23,000 academic journals indexed by Elsevier’s Scopus database and include all indexed journals published between 2010 and 2014. Only three types of publications are analysed: journal articles, conference proceedings and reviews. Citations to these papers made in the six years from 2010 to 2015 are also collected.The indicator is always defined with reference to a global baseline and intrinsically accounts for differences in citation accrual over time, differences in citation rates for different document types reviews typically attract more citations than research articles, for example as well as subject-specific differences in citation frequencies overall and over time and document types. It is one of the most sophisticated indicators in the modern bibliometric toolkit.The citations help to show us how much each university is contributing to the sum of human knowledge: they tell us whose research has stood out, has been picked up and built on by other scholars and, most importantly, has beenshared around the global scholarly community toexpand the boundaries of our understanding, irrespective of discipline.The data are fully normalised to reflect variations in citation volume between different subject areas. This means that institutions with high levels of research activity in subjects with traditionally high citation counts do not gain an unfair advantage.This year we have removed the very small number of papers 649 with more than 1,000 authors from the citations indicator.In previous years we have further normalised citation data within countries, with the aim of reducing the impact of measuring citations of English language publications. The change to Scopus as a data source has allowed us to reduce the level to which we do this. This year, we have blended equal measures of a country-adjusted and non-country-adjusted raw measure of citations scores. This reflects a more rigorous approach to international comparison of research publications.International outlook staff, students, research: %International-to-domestic-student ratio: %International-to-domestic-staff ratio: %The ability of a university toattract undergraduates, postgraduates and faculty from all over the planet is key to its success on the world stage.International collaboration: %In the third international indicator, we calculate the proportion of a university’s total research journal publications that have at least one international co-author and reward higher volumes. This indicator is normalised to account for auniversity’s subject mix and uses the same five-year w indow as the “Citations: research influence” category. Industry income knowledge transfer: %A university’s ability to help industry with innovations, inventions and consultancy has become a core mission ofthe contemporary global academy. This category seeks to capture such knowledge-transfer activity by looking athow much research income an institution earns from industry adjusted for PPP, scaled against the number of academic staff itemploys.The category suggests the extent to which businesses are willing to pay for research and a university’s ability toattract funding in the commercial marketplace –useful indicators of institutional quality.Subject tablesThe subject tables employ the same range of 13 performance indicators used in the overall World University Rankings, brought together with scores provided under the same five categories.However, we continue the three differences from the main World University Rankings methodology:Weightings recalibrated:Here, the overall methodology is carefully recalibrated for each subject, with the weightings changed to best suit the individual fields. In particular, those given to the research indicators have been altered to fit more closely the research culture in each subject, reflecting different publication habits: in the arts and humanities, for instance, where the range of outputs extends well beyond peer-reviewed journals, we give less weight to paper citations.Accordingly, the weight given to “citations: research influence” is halved from 30 per cent in the overall rankings to just 15 per cent for the arts and humanities. More weight is given to other research indicators, including the Academic Reputation Survey. For social sciences, where there is also less faith in the strength of citations alone as an indicator of research excellence, the measure’s weighting is reduced to 25 per cent.By the same token, in those subjects where the vast majority of research outputs come through journal articles and where there are high levels of confidence in the strength of citations data, we have increased the weighting given to the research influence up to 35 per cent for the physical and life sciences and for the clinical, pre-clinical and health tables.Publication eligibility criteria:For the six subject tables, there is an additional threshold within the subject, of 500 papers over 2010-14 for subjects that generate a high volume of publications, and 250 papers over 2010-14 in the social sciences and in the arts and humanities, where the volume tends to be lower.Staff eligibility criteria:We also generally expect an institution to have at least 5 per cent of its staff working in the relevant discipline in order to include it in the subject table.。
aaai 分数对应
aaai 分数对应AAAI分数是一个由美国人工智能协会制定的用来衡量人工智能专业技能水平的标准之一。
它是一种普及性的学术指标，并且可以有效地帮助用户评估他们所在专业的人工智能专业水平。
AAAI分数是由美国国家研究委员会（NSF）和美国人工智能学会（AAAI）联合制定的一个标准，作为衡量行业技术水平的一种可靠的指标。
一般来说，AAAI数是通过普及性和扩展性，结合高层科学家们的专业评估，综合测试来确定的。
AAAI分数可以分为三种，分别是：1）AAAI基准评估；2）AAAI 个人技术能力指数；3）AAAI专家级技术能力指数。
AAAI基准评估是一种可以衡量用户专业技术水平的基准指标，是使用普及性、扩展性等综合的方法，结合国际顶级人工智能领域的科学家们的评估，最终来确定的。
它是最常用的评估方式，其分数范围为1~100分，其中70分以上可以被认定为行业熟练技术水平，90分以上被认定为行业专家级技术水平。
AAAI个人技术能力指数是一种衡量个人技术能力的标准，是根据个人的技术能力的理论水平测试，结合国际顶级人工智能领域的科学家们的评估，最终来确定的。
它是衡量个人技术能力的最佳方式，其分数范围为1~100分，其中70分以上可以被认定为行业熟练技术水平，90分以上被认定为行业专家级技术水平。
AAAI专家级技术能力指数是一种用来衡量专家级技术水平的标准，是根据专家级技术能力的实际水平测试，结合国际顶级人工智能领域的科学家们的评估，最终来确定的。
它是衡量专家技术能力的最佳方式，其分数范围为1~100分，其中85分以上可以被认定为行业专家级技术水平，100分以上可以被认定为行业领先的先进技术水平。
AAAI分数的最终结果是可以准确反映出专业人士的技术水平，能够全面考察专业技术水平，从而为行业用户提供一种可靠的、可衡量的判断。
并且它也是一种有效的、标准的、通用的测试方式，可以使用户能够有效评估他们所在专业的人工智能专业水平。
英国硕士毕业等级
英国硕士毕业等级
英国硕士毕业等级分为以下五个等级：distinction（优等）、merit（良好）、pass（及格）、fail（不及格）和withdrawn （取消）。
英国硕士毕业等级是根据学生在学业和研究项目中的表现来评定的。
以下是对每个等级的说明：
1. Distinction（优等）：这是最高等级，表示学生在学术研究和学业方面表现出色。
学生需要展示出卓越的理解和批判性思维，并成功应用学科知识。
学生的研究项目需要体现自主性和创新性，并对相关领域做出重要贡献。
2. Merit（良好）：这一等级表示学生的表现良好。
学生需要展示出一定程度的理解和批判性思维，并成功应用学科知识。
学生在研究项目中需要展示一定程度的独立性和创新性。
3. Pass（及格）：这是学生必须达到的最低标准。
学生需要证明对学科的基本理解，并且能够基本运用所学知识。
学生的研究项目需要达到预期目标。
4. Fail（不及格）：这表示学生没有达到相关的学术要求。
学生相对于课程和研究项目的目标表现不佳。
这可能是由于学生在学业方面提供了不充分或不准确的证据，或者未能达到课程和项目要求。
5. Withdrawn（取消）：这种等级意味着学生因某种原因从课
程中退出或被取消资格。
这可能是由于学生的违规行为，缺席或其他原因。
需要注意的是，具体的毕业等级评定过程可能因大学和专业而有所不同。
每个学校和专业都有自己的指导手册和标准，用于评估学生的学术表现。
因此，学生在了解和理解所在大学和专业的特定评估标准方面需要格外注意。
国外课程成绩a-评定标准及流程及注意事项
国外课程成绩a-评定标准及流程及注意事项下载提示：该文档是本店铺精心编制而成的，希望大家下载后，能够帮助大家解决实际问题。
文档下载后可定制修改，请根据实际需要进行调整和使用，谢谢！本店铺为大家提供各种类型的实用资料，如教育随笔、日记赏析、句子摘抄、古诗大全、经典美文、话题作文、工作总结、词语解析、文案摘录、其他资料等等，想了解不同资料格式和写法，敬请关注！Download tips: This document is carefully compiled by this editor. I hope that after you download it, it can help you solve practical problems. The document can be customized and modified after downloading, please adjust and use it according to actual needs, thank you! In addition, this shop provides you with various types of practical materials, such as educational essays, diary appreciation, sentence excerpts, ancient poems, classic articles, topic composition, work summary, word parsing, copy excerpts, other materials and so on, want to know different data formats and writing methods, please pay attention!国外课程成绩评定标准及流程及注意事项一、评定标准1. A+：90100分，优秀。
加权平均学分绩点的英文名称
加权平均学分绩点的英文名称英文回答：Weighted Grade Point Average (WGPA) is a measure of academic achievement that takes into account the difficulty of the courses taken. It is calculated by multiplying the grade earned in each course by the number of credits assigned to that course, and then dividing the sum of these products by the total number of credits taken.WGPA is often used to compare students' academic performance with one another, and to determine eligibility for scholarships and other awards. It is also used by colleges and universities to make admissions decisions.There are several different ways to calculate WGPA. The most common method is to use a 4.0 scale, in which A = 4.0, B = 3.0, C = 2.0, D = 1.0, and F = 0.0. However, some schools use a different scale, such as a 5.0 scale or a 10.0 scale.When calculating WGPA, it is important to consider the difficulty of the courses taken. A student who takes a challenging course load will typically have a lower WGPA than a student who takes a less challenging course load. However, the student who takes the challenging course load will likely be better prepared for college and for their future career.中文回答：加权平均学分绩点 (WGPA) 是一种考虑课程难度的学术成就衡量标准。
star共识排名标准
star共识排名标准
STARCHI共识排名标准是由美国科学信息研究所（ISI）制定的一个科学评价指标，用于衡量一个国家或地区的科学研究水平。
它综合考虑了科研论文的数量、质量以及被引用次数等因素，为全球范围内的科研机构、期刊和学者提供了一个相对客观的评价标准。
STARCHI共识排名标准的具体指标包括：
1. 总被引用次数：一个国家或地区发表的论文被其他论文引用的总次数。
2. 篇均被引用次数：一个国家或地区发表的每篇论文平均被引用的次数。
3. 高被引论文数：一个国家或地区发表的被引用次数最多的论文数量。
4. 篇均影响因子：一个国家或地区发表的每篇论文平均影响因子。
5. 学科规范化的影响因子：一个国家或地区发表的论文在特定学科领域中的影响因子。
STARCHI共识排名标准对全球科研领域的影响深远，许多政府、组织和个人都将此作为衡量一个国家或地区科学研究水平的重要指标。
然而，该排名标准也存在一些局限性，例如过度强调量化指标、忽略研究质量等。
因此，在使用STARCHI共识排名标准时，需要综合考虑其他因素，如研究质量、学术声誉等。
- 1、下载文档前请自行甄别文档内容的完整性，平台不提供额外的编辑、内容补充、找答案等附加服务。
- 2、"仅部分预览"的文档,不可在线预览部分如存在完整性等问题,可反馈申请退款(可完整预览的文档不适用该条件!)。
- 3、如文档侵犯您的权益，请联系客服反馈,我们会尽快为您处理(人工客服工作时间：9:00-18:30)。
Thursday, April 15, 2010 Rankings
Statistics
Ranked in 2010
Sort by Rank | Name
Rank College name Distance Score
1Stanford University Stanford, CA Enter your
zip
4.9
2University of California--Berkeley Berkeley, CA Enter your
zip
4.7
3Harvard University Boston, MA Enter your
zip
4.6
3University of Washington Seattle, WA Enter your
zip
4.6
5Johns Hopkins University Baltimore, MD Enter your
zip
4.4
6Harvard University Cambridge, MA Enter your
zip
4.3
6University of Chicago Chicago, IL Enter your
zip
4.3
6University of Washington Seattle, WA Enter your
zip
4.3
9Carnegie Mellon University Pittsburgh, PA Enter your
zip
4.1
10Duke University Durham, NC Enter your
zip
4.0
10University of North Carolina--Chapel Hill Chapel Hill,
NC
Enter your
zip 4.0
12North Carolina State University Raleigh, NC Enter your
zip
3.9
12Texas A&M University--College Station College Station,
TX
Enter your
zip 3.9
Thursday, April 15, 2010 Rankings
Statistics
Ranked in 2010
Sort by Rank | Name
Rank College name Distance Score
22University of North Carolina--Chapel Hill Chapel Hill,
NC
Enter
your zip 3.6
27Ohio State University Columbus, OH Enter
your zip
3.5
27University of California--Los Angeles Los Angeles, CA Enter
your zip
3.5
27University of Florida Gainesville, FL Enter
your zip
3.5
27University of Wisconsin--Madison Madison, WI Enter
your zip
3.5
31University of California--Davis Davis, CA Enter
your zip
3.4
31University of California--Los Angeles Los Angeles, CA Enter
your zip
3.4
33Columbia University New York, NY Enter
your zip
3.3
33University of Illinois--Urbana-Champaign Champaign,
IL
Enter
your zip 3.3
33University of Iowa Iowa City, IA Enter
your zip
3.3
33Yale University New Haven, CT Enter
your zip
3.3
37Rutgers, the State University of New Jersey--New
Brunswick Piscataway, NJ
Enter
your zip
3.2
38Atlanta, GA Enter 3.1
Thursday, April 15, 2010 Rankings
Statistics
Ranked in 2010
Sort by Rank | Name
Rank College name Distance Score
48University of Missouri--Columbia Columbia, MO Enter your
zip
2.7
48Virginia Tech Blacksburg, VA Enter your
zip
2.7
53Southern Methodist University Dallas, TX Enter your
zip
2.6
53University of Texas Health Science Center--
Houston Houston, TX
Enter your
zip
2.6
55Medical College of Wisconsin Milwaukee, WI Enter your
zip
2.5
55University of California--Santa Barbara Santa
Barbara, CA
Enter your
zip 2.5
57University of South Carolina Columbia, SC Enter your
zip
2.4
58Medical University of South Carolina Charleston, SC Enter your
zip
2.3
58Oregon State University Corvallis, OR Enter your
zip
2.3
58University of California--Riverside Riverside, CA Enter your
zip
2.3
58University of Virginia Charlottesville, VA Enter your
zip
2.3
62Kansas State University Manhattan, KS Enter your
zip
2.2 62Temple University (Fox)Philadelphia, PA Enter your 2.2。