计量经济学英文版附录B 翻译
(将下列每段英文翻译成中文)
Translation ( Translate each of the following passage into Chinese )翻译（将下列每段英文翻译成中文）Chapter 1 Summary 蔡信杰03391004 陈彬033910051，Public finance ,also known as public sector economics or public economics, focuses on the taxing and spending activities of government and their influence on the allocation of resources and distribution of income.财政学，即公共经济学，焦点是税收和政府支出以及它们在分配资源和分配收入上的影响。
2，Public finance economists analyze both actual policies and develop guidelines for government activities . In the latter role, economists are influenced by their attitudes toward the role of government in society.财政学同时为政府行为分析现有方针和发展知道思路。
在未来作用中，经济受到在社会中有利于政府的关注者的影响。
3，In all organic view of society , individuals are valued only by their contribution to the realization of social goals. These goals are determined by the government.在一种有机的社会观中，个别价值只是由它们对实现政府目标所做出贡献来评价的。
金融计量经济学(双语版)(全套课件)
• Thus the autocorrelation function will be zero apart from a single peak of 1 at s = 0. • 如果假设yt服从标准正态分布, 则 ˆ s approximately N(0,1/T) • We can use this to do significance tests for the autocorrelation coefficients by constructing a confidence interval. • a 95% confidence interval would be given by 1.96 1 .
5-7
An ACF Example (p234)
• Question: Suppose that we had estimated the first 5 autocorrelation coefficients using a series of length 100 observations, and found them to be (from 1 to 5): 0.207, -0.013, 0.086, 0.005, -0.022. Test each of the individual coefficient for significance, and use both the Box-Pierce and Ljung-Box tests to establish whether they are jointly significant. • Solution: A coefficient would be significant if it lies outside (-0.196,+0.196) at the 5% level, so only the first autocorrelation coefficient is significant. Q=5.09 and Q*=5.26 Compared with a tabulated 2(5)=11.1 at the 5% level, so the 5 coefficients are jointly insignificant. 课件
计量经济学专业英汉词典
计量经济学专业英汉词典计量经济学专业英汉词典中文英文调整的R^2 （确定系数）adjusted R^2调整系数adjustment coefficient调整系数矩阵adjustment coefficient matrix赤池信息准则（AIC）Akaike’s information criterion (AIC) 阿尔蒙分布滞后模型Almen distributed lag model阿尔蒙滞后Almon lags备择假设alternative hypothesis方差分析analysis of variance辅助变量ancillary variable近似协方差矩阵approximate covariance matrix近似正态分布approximate normal distribution自回归模型AR model自回归过程AR process自回归条件异方差模型ARCH model自回归移动平均模型ARMA model假定assumption渐近χ2分布asymptotic χ2 distribution渐近协方差矩阵asymptotic covariance matrix渐近分布asymptotic distribution渐近有效性asymptotic efficiency渐近性质asymptotic properties渐近抽样特性asymptotic sampling properties渐近设定asymptotic specification渐近标准误差asymptotic standard error渐近检验asymptotic test渐近检验统计量asymptotic test statistic渐近逼近asymptotically approximation渐近有效估计式asymptotically efficient estimator渐近无偏估计式asymptotically unbiased estimatorADF检验，增项（增广）DF检验Augmented Dickey-Fuller test AEG检验，增项（增广）EG检验Augmented Engle-Granger test自相关方程误差autocorrelated equation error自相关autocorrelation自相关函数autocorrelation function自协方差autocovariance自协方差函数autocovariance function自回归autoregression自回归条件异方差autoregressive conditional heteroscedasticity自回归分布滞后模型autoregressive distributed lag (ADL) model自回归单整移动平均（ARIMA）autoregressive integrated moving average process 过程自回归（AR）摸型autoregressive model自回归移动平均（ARMA）过程autoregressive moving-average process自回归算子autoregressive operator辅助回归auxiliary regression平均值average行为方程behavioral equation贝拉－哈尔克（BJ）统计量Bera-Jarque statistic贝努利分布Bernoulli distribution最佳决策best decision最佳线性无偏估计式（BLUE）best linear unbiased estimator (BLUE)最佳线性无偏预测best linear unbiased prediction最佳无偏估计式best unbiased estimator偏倚bias偏倚向量bias vector有偏估计式biased estimator二元选择模型binary choice model二项分布binomial distribution二元正态随机变量bivariate normal random variable自举法，靴襻法bootstrap procedure博克斯－考克斯变换Box-Cox transformation博克斯－詹金斯方法Box-Jenkins approach布罗施－帕甘检验Breusch-Pagan test布朗运动Brownian motion典型相关canonical correlation因果性causality中心极限定理central limit theorem特征方程characteristic equation特征根characteristic root特征向量characteristic vector卡埃方分布chi-square distribution古典统计学classical statistics柯布－道格拉斯生产函数Cobb-Douglas production function 科克伦－奥克特方法Cochrane-Orcutt procedure“概率极限”概念concept of “plim”条件推断conditional inference条件概率conditional probability条件概率密度函数conditional probability density function 置信区间confidence interval一致性consistency一致估计式consistent estimator一致性检验consistent test消费函数consumption function同期相关contemporaneous correlation同期协方差矩阵contemporaneous covariance matrix同期扰动相关contemporaneous disturbance correlation同期独立随机回归自变量contemporaneous independent stochastic regressor 连续映射理论continuous mapping theorem 连续随机变量continuous random variable连续回归函数continuous regression function常规抽样理论conventional sampling theory依概率收敛converge in probability收敛convergence依分布收敛convergence in distribution相关correlation相关系数correlation coefficient相关矩阵correlation matrix相关图correlogram成本cost协方差covariance协方差矩阵covariance matrix协方差矩阵估计式covariance matrix estimator克拉美规则Cramér rule克拉美－拉奥不等式Cramér-Rao inequality克拉美－拉奥下界Cramér-Rao lower bound临界区域critical region临界值critical value截面数据cross-section data累积分布函数cumulative distribution function 数据data数据生成过程（dgp）date generation process数据标准化date normalization盲始模型dead-start model决策decision making决策规则decision rule决策规则选择decision rule choice决策理论decision theory演绎系统deductive system定义方程definitional equation解释程度degree of explanation自由度degree of freedom密度函数density function相依变量dependent variable设计矩阵design matrix检验方法detection methods方阵的行列式determinant of a square matrix确定系数，可决系数determination coefficient诊断校验diagnostic checking对角矩阵diagonal matrix对称矩阵的对角化diagonalization of a symmetric matrix 差分difference差分方程difference equation离散随机变量discrete random variable离散样本空间discrete sample space离散随机过程discrete stochastic process非均衡误差disequilibrium error不相交集disjoint set分布滞后distributed lag分布滞后模型distributed lag model分布distribution分布函数distribution function分布理论distribution theory扰动协方差矩阵disturbance covariance matrix扰动方差disturbance variance位移项drift虚拟变量dummy variable虚拟变量估计式dummy variable estimatorDW（德宾—沃森）统计量Durbin-Watson statisticDW（德宾—沃森）检验Durbin-Watson test动态模型dynamic model动态乘数dynamic multiplier动态回归dynamic regression动态联立方程dynamic simultaneous equation计量经济学，经济计量学econometrics经济变量economic variables经济学economics经济economy有效性efficiencyEG检验EG test特征值eigen value弹性elasticity椭圆ellipse空集empty set内生变量endogenous variableEG两步估计量Engel-Granger (EG) two-step estimate EG两步法Engel-Granger (EG) two-step method 方程误差equation error 方程识别equation identification均衡equilibrium均衡分析equilibrium analysis均衡条件equilibrium condition均衡乘子equilibrium multiplier均衡关系equilibrium relationship均衡状态equilibrium state遍历性ergodicity误差error误差分量error component误差修正机制error correction mechanism误差修正模型error correction model误差修正项error correction term误差平方和error sum of squares误差向量error vector估计量estimate估计estimation估计式estimator欧氏空间Euclidean space外生前定变量exogenous predetermined variable 外生变量exogenous variable期望算子expectation operator期望值expected value试验experiment被解释变量explained variable解释变量explaining variable解释explanation指数分布exponential distributionF分布 F distributionF统计量 F statisticF检验 F test因子分解准则factorization criterion反馈feedback最终形式final form有限分布滞后模型finite distribution lag model有限非奇异矩阵finite nonsingular matrix有限多项式滞后finite polynomial lag有限抽样特性finite sampling property有限方差finite variance一阶自回归模型first-order autoregressive model 一阶条件first-order condition一阶差分算子first-order difference operator 一阶泰勒级数first-order Taylor series拟合值fitted value固定回归自变量fixed regressor预测区间forecast interval预测区域forecast region预测方差forecast variance预测forecasting频数，频率frequency完全信息估计full information estimation完全信息极大似然法full information maximum likelihood method 函数形式function form函数空间function space泛函中心极限定理functional central limit theorem (FCLT)伽玛分布Gamma distribution伽玛函数Gamma function广义自回归条件异方差模型GARCH高斯白噪声Gaussian white noise高斯－马尔可夫定理Gauss-Markov theorem高斯－牛顿算法Gauss-Newton algorithm一般协方差矩阵general covariance matrix一般均衡general equilibrium一般线性假设general linear hypothesis一般线性统计模型general linear statistical model一般随机回归自变量模型general stochastic regressor model“一般到特殊”方法general to special method广义自回归算子generalized autoregressive operator广义最小二乘法generalized least squares广义最小二乘估计generalized least squares estimation 广义最小二乘估计式generalized least squares estimator 广义最小二乘方法generalized least squares procedure 广义最小二乘残差generalized least squares residual广义最小二乘规则generalized least squares rule几何滞后模型估计geometric lag model estimation总体极小值global minimum拟合优度goodness of fit格兰杰因果性Granger causality格兰杰因果性检验Granger causality test格兰杰非因果性Granger noncausality格兰杰定理Granger representation theorem增长率模型growth rate model豪斯曼设定检验Hausman specification test重（厚）尾heavy tail海赛矩阵Hessian matrix异方差误差heteroscedastic error异方差heteroscedasticity同一性homogeneity同方差误差homoscedastic error同方差homoscedasticity假设hypothesis假设检验hypothesis test同分布随机变量identically distributed random variable 识别identification识别规则identification rules单位矩阵identity matrix压缩矩阵，影响矩阵impact matrix影响乘数矩阵impact multiplier matrix非一致性inconsistency错误约束incorrect restriction独立同一分布independent and identical distribution (IID) 独立分布independent distribution独立事件independent event独立随机变量independent random variable独立随机回归自变量independent stochastic regressor独立变量independent variable间接最小二乘法indirect least squares不等式约束inequality restriction推断inference无限分布滞后infinite distributed lag无限累加算子infinite summation operator无限方差infinite variance有影响的观测值influential observation信息矩阵information matrix内积inner product新息过程innovation sequence投入产出关系input-output relationship工具变量instrumental variable工具变量估计instrumental variable estimation 单整integration截距intercept区间估计interval estimation区间预测interval forecast不变性invariance逆矩阵inverse matrix信息矩阵的逆inverse of information matrix可逆性invertibility可逆移动平均过程invertible moving-average process 投资investment迭代方法iterative procedure大折刀方法jackknife procedure雅可比变换Jacobian of the transformation联合置信区间joint confidence interval联合置信区域joint confidence region联合密度函数joint density function联合扰动向量joint disturbance vector联合假设检验joint hypothesis test联合区间估计joint interval estimation联合零（原）假设joint null hypothesis联合概率分布joint probability distribution联合被确定变量jointly determined variable恰好识别方程just identified equation核kernel凯恩斯消费函数Keynesian consumption function 凯恩斯模型Keynesian model克莱因－戈德伯格消费函数Klein-Goldberger consumption克莱因－鲁滨效用函数Klein-Rubin utility function柯依克变换Koyck transformation克罗内克尔积Kronecker product库恩－塔克条件Kuhn-Tucker condition峰度，峭度kurtosis滞后lag滞后长度lag length滞后算子lag operator滞后权数lag weight滞后变量lagged variable拉格朗日乘数Lagrange multiplier拉格朗日乘子检验Lagrange multiplier test拉普拉斯展开Laplace expansion大样本特性large sample properties全概率定律law of total probability前导模型leading indication model最小绝对离差least absolute deviation最小绝对误差估计式least absolute error estimator 最小平方偏倚least squares bias最小平方准则least squares criterion最小平方估计式least squares estimator最小平方法least squares procedure最小平方残差least squares residual最小平方规则least squares rule最小平方方差估计式least squares variance estimator左逆矩阵left-inverse matrix显著性水平level of significance杠杆率leverage似然函数likelihood function似然原理likelihood principle似然比原理likelihood ratio principle似然比统计量likelihood ratio statistic似然比检验likelihood ratio test线性代数linear algebra线性联系linear association线性相依linear dependency线性相依向量linear dependent vector线性等式约束linear equality restriction 线性方程linear equation线性方程系统linear equation system线性估计式linear estimator线性形式linear form线性参数linear in parameter线性无关向量linear independent vector线性不等式假设linear inequality hypothesis 线性不等式约束linear inequality restriction 线性损失函数linear loss function 线性算子linear operator线性概率模型linear probability model线性规划模型linear programming model线性约束linear restriction线性规则linear rule线性联立方程linear simultaneous equation 线性统计模型linear statistical model线性变换linear transformation线性无偏估计式linear unbiased estimator线性linearity局部极小值local minima罗基斯迪随机变量logistic random variable罗基特（Logit）模型logit model对数似然函数log-likelihood function对数线性函数log-linear function长期效应long-run effect损失loss损失函数loss function下三角矩阵lower triangular matrix矩（M）估计式M estimator移动平均模型MA model宏观经济学macroeconomics边缘分布marginal distribution边缘概率密度函数marginal probability density function 边际消费倾向marginal propensity to consume数理经济学mathematical economics数学期望mathematical expectation矩阵matrix矩阵分解matrix decomposition极大似然估计maximum likelihood estimation极大似然估计式maximum likelihood estimator极大似然法maximum likelihood method均值mean均方误差mean square error均方误差准则mean square error criterion均方误差矩阵mean square error matrix均值向量mean vector测量误差measurement error中位数median矩法method of moments极小极大准则minimax criterion使损失最小minimizing loss使风险最小minimizing risk最小绝对离差估计式minimum absolute deviation estimator 最小方差minimum variance最小方差无偏估计minimum variance unbiased estimation 错误设定misspecification混合估计mixed estimation众数mode模型model模型设定model specification模数module复数的模modulus of a complex number矩moment蒙特卡罗Monte Carlo蒙特卡罗数据Monte Carlo data蒙特卡罗试验Monte Carlo experiment蒙特卡罗模拟Monte Carlo simulation移动平均moving average移动平均（MA）模型moving average (MA) model移动平均过程moving average process移动平均表示法moving average representation移动平均季节过滤算子moving average seasonal filter多重共线性multicollinearity多项选择模型multinomial choice models多项分布multinomial distribution多元回归multiple regression多重解multiple solution多重时间序列分析multiple time-series analysis乘法multiplication乘子，乘数multiplier多元分布multivariate distribution多元函数multivariate function多元正态分布multivariate normal distribution多元正态随机变量multivariate normal random variable 多元随机变量multivariate random variable多元t 分布multivariate t distribution互斥集mutually exclusive set自然共轭先验概率密度函数natural conjugate prior probability density function半负定矩阵negative semidefinite matrix嵌套nest牛顿－拉夫森算法和方法Newton-Raphson algorithm and method非线性函数nonlinear function参数非线性nonlinear in the parameter非线性最小平方法nonlinear least squares非线性最小平方估计nonlinear least squares estimation非线性似然函数nonlinear likelihood function非线性极大似然估计nonlinear maximum likelihood estimation 非线性回归nonlinear regression非线性似不相关回归方程nonlinear seemingly unrelated regression equation非线性nonlinearity非负定矩阵nonnegative definite matrix非嵌套模型nonnested models非正态分布nonnormal distribution非正态误差nonnormal error非正定矩阵nonpositive definite matrix非纯量单位协方差矩阵nonscalar identity covariance matrix 非奇异矩阵nonsingular matrix非平稳nonstationary非平稳过程nonstationary process非随机变量nonstochatic variable正态分布normal distribution正态分布理论normal distribution theory正态误差的检验normal error testing正态线性统计模型normal linear statistical model正态概率密度函数的核normal probability density function 正态随机向量normal random vector正态变量normal variable正态向量normal vector标准化常数normalizing constant正态分布随机变量normally distribution random variable 多余参数nuisance parameter零（原）假设null hypothesis零矩阵null matrix空集，零集null set可观测随机变量observable random variable可观测随机向量observable random vector观测值样本observation sample观测上的等价模型observationally equivalent model阶order阶条件order condition普通最小二乘法ordinary least squares正交矩阵orthogonal matrix正交向量orthogonal vector正交orthogonality标准正交线性统计模型orthonormal linear statistical model 离群值outliers过度识别方程overidentified equation参数parameter参数估计parameter estimation参数方差parameter variance参数检验parametric test帕累托分布Pareto distribution局部调整分布滞后模型partial adjustment distributed lag model 偏（局部）调整模型partial adjustment model偏自相关partial autocorrelation偏自相关系数partial autocorrelation coefficient偏自相关函数partial autocorrelation function偏相关partial correlation偏相关图partial correlogram偏导数partial derivative局部均衡partial equilibrium分块逆规则partitioned inverse rule完全多重共线性perfect multicollinearity长期收入假设permanent income hypothesis分段线性回归piecewise linear regression分段回归函数piecewise regression function点估计量point estimate点估计point estimation点估计式point estimator点估计式性质point estimator properties多项式polynomial多项式滞后polynomial lag多项式矩阵polynomial matrix合并数据pooling data合并模型pooling model合并模型选择pooling model selection合并时间序列pooling time series合并时间序列数据pooling time series data总体population正定矩阵positive definite matrix正定对称矩阵positive definite symmetric matrix 半正定矩阵positive semidefinite matrix后验密度posterior density后验密度函数posterior density function后验分布posterior distribution后验信息posterior information后验均值posterior mean后验优势posterior odds后验优势比posterior odds ratio后验概率posterior probability后验概率密度函数posterior probability density function 后验概率区域posterior probability region假设过程postulation process功效函数power function检验功效power of a test前定变量predetermined variable预测误差prediction error随机分量的预测prediction of random components预测精度prediction precision主分量模型principal components model先验协方差矩阵prior covariance matrix先验分布prior distribution先验均值prior mean先验概率prior probability先验概率密度函数prior probability density function先验概率区域prior probability region概率probability概率密度probability density概率分布probability distribution离散随机变量的概率分布probability distribution for discrete random variable概率分布函数probability distribution function概率测度probability measure概率单位（probit）模型probit model积矩product moment积矩量矩阵product moment matrix积算子product operator生产函数production function生产过程production process比例响应模型proportional response model 伪样本数据pseudo sample data二次型quadratic form二次损失函数quadratic loss function二次矩阵quadratic matrix定量选择模型quantitative choice model 定量因素quantitative factors定量信息quantitative information随机系数模型random coefficient model随机分量预测random component prediction 随机误差random error随机试验random experiment随机变量random variable随机向量random vector随机向量分量random vector component随机游走random walk秩rank秩条件rank condition矩阵的秩rank of a matrix简化型reduced form简化型系数reduced form coefficient简化型扰动reduced form disturbance简化型方程reduced form equation简化型估计式reduced form estimator。
计量经济学(英文版)Basic Econometrics-Long.
• The Data Types
Chapter 1 Introduction
-- Time-series data data that represent repeated observations of some variable in subsequent time periods. A time-series variable is often subscripted with the letter t. -- Cross-sectional data data that represent a set of observations of some variable at one specific instant over several agents. A crosssectional variable is often subscripted with the letter i. -- Time-series cross-sectional data data that are both time series and cross-sectional. An special case of time-series cross-sectional data is panel data. Panel data are observations of the same set of agents over time.
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• The qualitative and quantitative relation among various variables --non-exact quantitative relations:
Q = f (P) Q = a + bP + ; --where f may not represent single relation like linear -- a and b are conditionally exact number, --The term represent those condition under which what are the data of Q and P. ex1. The relation between supply and demand see textbook: coffee ex2. income and consume: multi-relation and no exact sole parameters to determine the relation
英汉对照计量经济学术语
英汉对照计量经济学术语第一篇：英汉对照计量经济学术语计量经济学术语A 校正R2（Adjusted R-Squared）：多元回归分析中拟合优度的量度，在估计误差的方差时对添加的解释变量用一个自由度来调整。
对立假设（Alternative Hypothesis）：检验虚拟假设时的相对假设。
AR（1）序列相关（AR(1)Serial Correlation）：时间序列回归模型中的误差遵循AR（1）模型。
渐近置信区间（Asymptotic Confidence Interval）：大样本容量下近似成立的置信区间。
渐近正态性（Asymptotic Normality）：适当正态化后样本分布收敛到标准正态分布的估计量。
渐近性质（Asymptotic Properties）：当样本容量无限增长时适用的估计量和检验统计量性质。
渐近标准误（Asymptotic Standard Error）：大样本下生效的标准误。
渐近t 统计量（Asymptotic t Statistic）：大样本下近似服从标准正态分布的t 统计量。
渐近方差（Asymptotic Variance）：为了获得渐近标准正态分布，我们必须用以除估计量的平方值。
渐近有效（Asymptotically Efficient）：对于服从渐近正态分布的一致性估计量，有最小渐近方差的估计量。
渐近不相关（Asymptotically Uncorrelated）：时间序列过程中，随着两个时点上的随机变量的时间间隔增加，它们之间的相关趋于零。
衰减偏误（Attenuation Bias）：总是朝向零的估计量偏误，因而有衰减偏误的估计量的期望值小于参数的绝对值。
自回归条件异方差性（Autoregressive Conditional Heteroskedasticity, ARCH）：动态异方差性模型，即给定过去信息，误差项的方差线性依赖于过去的误差的平方。
一阶自回归过程[AR（1）]（Autoregressive Process of Order One [AR(1)]）：一个时间序列模型，其当前值线性依赖于最近的值加上一个无法预测的扰动。
计量经济学英文课件共35页
One-Sided Alternatives (cont)
Having picked a significance level, a, we look up the (1 – a)th percentile in a t distribution with n – k – 1 df and call this c, the critical value We can reject the null hypothesis if the t statistic is greater than the critical value If the t statistic is less than the critical value then we fail to reject the null
Under the CLM assumptions, conditional on the sample values of the independent variable s
bˆ j ~ Normal b j ,Var bˆ j , so that
bˆ j b j sd bˆ j ~ Normal 0,1
7
t Test: One-Sided Alternatives
Besides our null, H0, we need an alternative hypothesis, H1, and a significance level H1 may be one-sided, or two-sided
because we have to estimate s 2by sˆ 2
Note the degrees of freedom : n k 1
5
The t Test (cont)
计量经济学(英文)重点知识点考试必备
第一章1. Econo metrics （计量经济学）：the social scie nee in which the tools of econo mic theory, mathematics, and statistical inference are applied to the an alysis of econo mic phe nomena.the result of a certain outlook on the role of economics, consists of the application of mathematical statistics to econo mic data to lend empirical support to the models con structed by mathematical econo mics and to obta in nu merical results.2. Econo metric an alysis proceeds along the followi ng lines计量经济学分析步骤1）Creat ing a stateme nt of theory or hypothesi建立一个理论假说2）Collecting data.收集数据3）Specify ing the mathematical model of theory 设定数学模型4）Specify ing the statistical, or econo metric, model of theory设立统计或经济计量模型5）Estimati ng the parameters of the chose n econo metric mod估计经济计量模型参数6）Check ing for model adequacy : Model specificati on test ing 核查模型的适用性：模型设定检验7）Testi ng the hypothesis derived from the mode检验自模型的假设8）Using the model for prediction or forecasting禾U用模型进行预测Step2：收集数据Three types of data三类可用于分析的数据1）Time series（时间序歹U数据）:Collected over a period of time, are collected at regular in tervals.按时间跨度收集得到2）Cross-sectional截面数据:Collected over a period of time, are collected at regular in tervals.按时间跨度收集得到3）Pooled data合并数据（上两种的结合）Step3:设定数学模型1. plot scatter diagram or scattergram2. write the mathematical modelStep4：设立统计或经济计量模型CLFPR is depe nde nt variable应变量CUNR is in depe nde nt or expla natory variable独立或解释变量（自变量）We give a catchall variable U to stand for all these neglected factorsIn lin ear regressi on an alysis our primary objective is to expla in the behavior of the depe ndent variable in relati on to the behavior of one or more other variables, allowi ng for the data that the relati on ship betwee n them is in exacts 性回归分析的主要目标就是解释一个变量（应变量）与其他一个或多个变量（自变量）只见的行为关系，当然这种关系并非完全正确Step5:估计经济计量模型参数In short, the estimated regressi on line gives the relati on ship betwee n average CLFPR and CUNR简言之，估计的回归直线给出了平均应变量和自变量之间的关系That is, on average, how the depe ndent variable resp onds to a unit cha nge in the in depe nde nt variable单位因变量的变化引起的自变量平均变化量的多少。
大学伍德里奇计量经济学第三版教师手册-APPENDIX B
20XX年复习资料大学复习资料专业：班级：科目老师：日期：APPENDIX BSOLUTIONS TO PROBLEMSB.1 Before the student takes the SAT exam, we do not know – nor can we predict with certainty –what the score will be. The actual score depends on numerous factors, many of which we cannot even list, let alone know ahead of time. (The student’s innate ability, how the student feels on exam day, and which particular questions were asked, are just a few.) The eventual SAT score clearly satisfies the requirements of a random variable.B.2 (i) P(X 6) = P[(X– 5)/2 (6 – 5)/2] =P(Z.5) ≈.692, where Z denotes a Normal (0,1) random variable. [We obtain P(Z£ .5) from Table G.1.](ii) P(X> 4) = P[(X–5)/2 > (4 –5)/2] = P(Z> .5) = P(Z£ .5) .692.(iii) P(|X–5| > 1) = P(X–5 > 1) + P(X–5 < –1) = P(X> 6) + P(X< 4) ≈ (1 –.692) + (1 –.692) = .620XXXX, where we have used answers from parts (i) and (ii).B.3(i) Let Y it be the binary variable equal to one if fund i outperforms the market in year t. By assumption, P(Y it= 1) = .5 (a 50-50 chance of outperforming the market for each fund in each year). Now, for any fund, we are also assuming that performance relative to the market is independent across years. But then the probability that fund i outperforms the market in all 20XXXX years, P(Y i1= 1,Y i2= 1, , Y i,20XXXX= 1), is just the product of the probabilities: P(Y i1= = 1) P(Y i,20XXXX= 1) = (.5)20XXXX= 1/20XXXX0XX4 (which is1)⋅P(Yi2slightly less than .001). In fact, if we define a binary random variable Y i such that Y i= 1 if and only if fund i outperformed the market in all 20XXXX years, then P(Y i= 1) = 1/20XXXX0XX4.(ii) Let X denote the number of funds out of 4,20XXXX0 that outperform the market in all 20XXXX years. Then X= Y1+ Y2+ + Y4,20XXXX0. If we assume that performance relative to the market is independent across funds, then X has the Binomial (n,) distribution with n= 4,20XXXX0 and = 1/20XXXX0XX4. We want to compute P(X≥ 1)= 1 –P(X= 0) = 1 –P(Y1= 0, Y2= 0, …, Y4,20XXXX0 = 0) = 1 – P(Y1 = 0) P(Y2= 0)P(Y4,20XXXX0= 0) = 1 –(20XXXX0XX3/20XXXX0XX4)420XXXX0≈.20XXXX3. This means, if performance relative to the market is random and independent acrossfunds, it is almost certain that at least one fund will outperform the market in all 20XXXX years.(iii) Using the Stata command Binomial(420XXXX0,5,1/20XXXX0XX4), the answer is about .385. So there is a nontrivial chance that at least five funds will outperform the market in all 20XXXX years. B.4 We want P(X .6). Because X is continuous, this is the same as P(X> .6) = 1 –P(X£.6) = F(.6) = 3(.6)2–2(.6)3= .648. One way to interpret this is that almost 65% of all counties have an elderly employment rate of .6 or higher.B.5(i) As stated in the hint, if X is the number of jurors convinced of Sim pson’s innocence, then X~ Binomial(20XXXX,.20XX). We want P(X 1) = 1 – P(X= 0) = 1 – (.8)20XXXX≈ .931.(ii) Above, we computed P(X= 0) as about .20XXXX9. We needP(X= 1), which we obtain from (B.20XXXX) with n= 20XXXX, = .2, and x= 1: P(X= 1) = 20XXXX (.2)(.8)20XXXX≈ .220XXXX. Therefore, P(X 2) ≈ 1 – (.20XXXX9 + .220XXXX) = .725, so there is almost a three in four chance that the jury had at least two members co nvinced of Simpson’s innocence prior to the trial.B.6 E(X ) = 30()xf x dx ⎰ = 320[(1/9)] x x dx ⎰ = (1/9) 330x dx ⎰.But 330x dx ⎰ = (1/4)x 430| = 81/4. Therefore, E(X ) = (1/9)(81/4) = 9/4, or 2.25 years.B.7 In eight attempts the expected number of free throws is 8(.74) =5.92, or about six free throws.B.8 The weights for the two-, three-, and four-credit courses are 2/9, 3/9, and 4/9, respectively. Let Y j be the grade in the j thcourse, j = 1, 2, and 3, and let X be the overall grade point average. Then X = (2/9)Y 1 + (3/9)Y 2 + (4/9)Y 3 and the expected value is E(X ) =(2/9)E(Y 1) + (3/9)E(Y 2) + (4/9)E(Y 3) = (2/9)(3.5) +(3/9)(3.0) + (4/9)(3.0) = (7 + 9 + 20XXXX)/93.20XXXX.B.9 If Y is salary in dollars then Y = 20XXXX00⋅X , and so the expected value of Y is 1,000 times the expected value of X , and the standard deviation of Y is 1,000 times the standard deviation of X . Therefore, the expected value and standard deviation of salary, measured in dollars, are $52,300 and $20XXXX,600, respectively.B.20XXXX (i) E(GPA |SAT = 800) = .70 + .020XXXX(800) = 2.3. Similarly, E(GPA |SAT = 1,400) = .70 + .020XXXX(20XXXX00) = 3.5.The difference in expected GPAs is substantial, but the difference in SAT scores is also rather large.(ii) Following the hint, we use the law of iterated expectations. Since E(GPA|SAT) = .70 + .020XXXX SAT, the (unconditional) expected value of GPA is .70 + .020XXXXE(SAT) = .70 + .020XXXX(20XXXX0XX0) = 2.9.。
计量经济学Econometrics专业词汇中英文对照
Econometrics 专业词汇中英文对照（按课件顺序）Ch1-3Causal effects：因果影响，指的是当x变化时，会引起y的变化；Elasticity：弹性；correlation (coefficient) 相关（系数），相关系数没有单位，unit free；estimation：估计；hypothesis testing：假设检验；confidence interval：置信区间；difference-in-means test：均值差异检验，即检验两个样本的均值是否相同；standard error：标准差；statistical inference：统计推断；Moments of distribution：分布的矩函数；conditional distribution (means)：条件分布（均值）；variance：方差；standard deviation：标准差（指总体方差的平方根）；standard error：标准误差，指样本方差的平方根；skewness：偏度，度量分布的对称性；kurtosis：峰度，度量厚尾性，即度量离散程度；joint distribution：联合分布；conditional expectation：条件期望（指总体）；randomness：随机性i.i.d., independently and identically distributed：独立同分布的；sampling distribution：抽样分布，指的是当抽取不同的随机样本时，统计量的取值会有所不同，而当取遍所有的样本量为n的样本时，统计量有一个取值规律，即抽样分布，即统计量的随机性来自样本的随机性consistent (consistency)：相合的（相合性），指当样本量趋于无穷大时，估计量依概率收敛到真实值；此外，在统计的语言中，还有一个叫模型选择的相合性，指的是能依概率选取到正确的模型Central limit theory：中心极限定理；unbiased estimator：无偏估计量；uncertainty：不确定性；approximation：逼近；least squares estimator：最小二乘估计量；provisional decision：临时的决定，用于假设检验，指的是，我们现在下的结论是基于现在的数据的，如果数据变化，我们的结论可能会发生变化significance level：显著性水平，一般取0.05或者0.01,0.1，是一个预先给定的数值，指的是在原假设成立的假设下，我们可能犯的错误的概率，即拒绝原假设的概率；p-value：p-值，指的是观测到比现在观测到的统计量更极端的概率，一般p-值很小的时候要拒绝原假设，因为这说明要观测到比现在观测到的统计量更极端的情况的概率很小，进而说明现在的统计量很极端。
计量经济学中英文词汇对照
Common variance Common variation Communality variance Comparability Comparison of bathes Comparison value Compartment model Compassion Complement of an event Complete association Complete dissociation Complete statistics Completely randomized design Composite event Composite events Concavity Conditional expectation Conditional likelihood Conditional probability Conditionally linear Confidence interval Confidence limit Confidence lower limit Confidence upper limit Confirmatory Factor Analysis Confirmatory research Confounding factor Conjoint Consistency Consistency check Consistent asymptotically normal estimate Consistent estimate Constrained nonlinear regression Constraint Contaminated distribution Contaminated Gausssian Contaminated normal distribution Contamination Contamination model Contingency table Contour Contribution rate Control
基本无害的计量经济学 英文版
基本无害的计量经济学英文版以下为您生成 20 个关于“写基本无害的计量经济学”（Writing Essentially harmless econometrics）的相关英语释义、短语、单词、用法和双语例句：1. **单词**：econometrics （英语释义：The branch of economics that uses statistical methods to analyze economic data. ）- 用法：“Econometrics is a complex subject.”（计量经济学是一门复杂的学科。
）2. **单词**：harmless （英语释义：Not causing harm or damage. ）- 用法：“The snake is harmless.”（这条蛇无害。
）3. **单词**：essentially （英语释义：In the most important or fundamental way. ）- 用法：“Essentially, this is a difficult problem.”（从根本上说，这是个难题。
）4. **单词**：writing （英语释义：The activity of putting words on paper or a computer screen. ）- 用法：“I enjoy writing stories.”（我喜欢写故事。
）5. **短语**：statistical method （英语释义：A way of dealing with and analyzing data using statistics. ）- 用法：“We used statistical methods to analyze the data.”（我们使用统计方法来分析数据。
）6. **短语**：economic data （英语释义：Information related to the economy. ）- 用法：“The research is based on extensive economic data.”（这项研究基于大量的经济数据。
计量经济学中英文对照词汇
计量经济学中英文对照词汇(总21页)-CAL-FENGHAI.-(YICAI)-Company One1-CAL-本页仅作为文档封面，使用请直接删除计量经济学中英对照词汇Absolute deviation, 绝对离差Absolute number, 绝对数Absolute residuals, 绝对残差Acceleration array, 加速度立体阵Acceleration in an arbitrary direction, 任意方向上的加速度Acceleration normal, 法向加速度Acceleration space dimension, 加速度空间的维数Acceleration tangential, 切向加速度Acceleration vector, 加速度向量Acceptable hypothesis, 可接受假设Accumulation, 累积Accuracy, 准确度Actual frequency, 实际频数Adaptive estimator, 自适应估计量Addition, 相加Addition theorem, 加法定理Additive Noise, 加性噪声Additivity, 可加性Adjusted rate, 调整率Adjusted value, 校正值Admissible error, 容许误差Aggregation, 聚集性Alpha factoring,α因子法Alternative hypothesis, 备择假设Among groups, 组间Amounts, 总量Analysis of correlation, 相关分析Analysis of covariance, 协方差分析Analysis Of Effects, 效应分析Analysis Of Variance, 方差分析Analysis of regression, 回归分析Analysis of time series, 时间序列分析Analysis of variance, 方差分析Angular transformation, 角转换ANOVA （analysis of variance）, 方差分析ANOVA Models, 方差分析模型ANOVA table and eta, 分组计算方差分析Arcing, 弧/弧旋Arcsine transformation, 反正弦变换Area 区域图Area under the curve, 曲线面积AREG , 评估从一个时间点到下一个时间点回归相关时的误差ARIMA, 季节和非季节性单变量模型的极大似然估计Arithmetic grid paper, 算术格纸Arithmetic mean, 算术平均数Arrhenius relation, 艾恩尼斯关系Assessing fit, 拟合的评估Associative laws, 结合律Asymmetric distribution, 非对称分布Asymptotic bias, 渐近偏倚Asymptotic efficiency, 渐近效率Asymptotic variance, 渐近方差Attributable risk, 归因危险度Attribute data, 属性资料Attribution, 属性Autocorrelation, 自相关Autocorrelation of residuals, 残差的自相关Average, 平均数Average confidence interval length, 平均置信区间长度Average growth rate, 平均增长率Bar chart, 条形图Bar graph, 条形图Base period, 基期Bayes' theorem , Bayes定理Bell-shaped curve, 钟形曲线Bernoulli distribution, 伯努力分布Best-trim estimator, 最好切尾估计量Bias, 偏性Binary logistic regression, 二元逻辑斯蒂回归Binomial distribution, 二项分布Bisquare, 双平方Bivariate Correlate, 二变量相关Bivariate normal distribution, 双变量正态分布Bivariate normal population, 双变量正态总体Biweight interval, 双权区间Biweight M-estimator, 双权M估计量Block, 区组/配伍组BMDP(Biomedical computer programs), BMDP统计软件包Boxplots, 箱线图/箱尾图Breakdown bound, 崩溃界/崩溃点Canonical correlation, 典型相关Caption, 纵标目Case-control study, 病例对照研究Categorical variable, 分类变量Catenary, 悬链线Cauchy distribution, 柯西分布Cause-and-effect relationship, 因果关系Cell, 单元Censoring, 终检Center of symmetry, 对称中心Centering and scaling, 中心化和定标Central tendency, 集中趋势Central value, 中心值CHAID -χ2 Automatic Interaction Detector, 卡方自动交互检测Chance, 机遇Chance error, 随机误差Chance variable, 随机变量Characteristic equation, 特征方程Characteristic root, 特征根Characteristic vector, 特征向量Chebshev criterion of fit, 拟合的切比雪夫准则Chernoff faces, 切尔诺夫脸谱图Chi-square test, 卡方检验/χ2检验Choleskey decomposition, 乔洛斯基分解Circle chart, 圆图Class interval, 组距Class mid-value, 组中值Class upper limit, 组上限Classified variable, 分类变量Cluster analysis, 聚类分析Cluster sampling, 整群抽样Code, 代码Coded data, 编码数据Coding, 编码Coefficient of contingency, 列联系数Coefficient of determination, 决定系数Coefficient of multiple correlation, 多重相关系数Coefficient of partial correlation, 偏相关系数Coefficient of production-moment correlation, 积差相关系数Coefficient of rank correlation, 等级相关系数Coefficient of regression, 回归系数Coefficient of skewness, 偏度系数Coefficient of variation, 变异系数Cohort study, 队列研究Collinearity, 共线性Column, 列Column effect, 列效应Column factor, 列因素Combination pool, 合并Combinative table, 组合表Common factor, 共性因子Common regression coefficient, 公共回归系数Common value, 共同值Common variance, 公共方差Common variation, 公共变异Communality variance, 共性方差Comparability, 可比性Comparison of bathes, 批比较Comparison value, 比较值Compartment model, 分部模型Compassion, 伸缩Complement of an event, 补事件Complete association, 完全正相关Complete dissociation, 完全不相关Complete statistics, 完备统计量Completely randomized design, 完全随机化设计Composite event, 联合事件Composite events, 复合事件Concavity, 凹性Conditional expectation, 条件期望Conditional likelihood, 条件似然Conditional probability, 条件概率Conditionally linear, 依条件线性Confidence interval, 置信区间Confidence limit, 置信限Confidence lower limit, 置信下限Confidence upper limit, 置信上限Confirmatory Factor Analysis , 验证性因子分析Confirmatory research, 证实性实验研究Confounding factor, 混杂因素Conjoint, 联合分析Consistency, 相合性Consistency check, 一致性检验Consistent asymptotically normal estimate, 相合渐近正态估计Consistent estimate, 相合估计Constrained nonlinear regression, 受约束非线性回归Constraint, 约束Contaminated distribution, 污染分布Contaminated Gausssian, 污染高斯分布Contaminated normal distribution, 污染正态分布Contamination, 污染Contamination model, 污染模型Contingency table, 列联表Contour, 边界线Contribution rate, 贡献率Control, 对照, 质量控制图Controlled experiments, 对照实验Conventional depth, 常规深度Convolution, 卷积Corrected factor, 校正因子Corrected mean, 校正均值Correction coefficient, 校正系数Correctness, 正确性Correlation coefficient, 相关系数Correlation, 相关性Correlation index, 相关指数Correspondence, 对应Counting, 计数Counts, 计数/频数Covariance, 协方差Covariant, 共变Cox Regression, Cox回归Criteria for fitting, 拟合准则Criteria of least squares, 最小二乘准则Critical ratio, 临界比Critical region, 拒绝域Critical value, 临界值Cross-over design, 交叉设计Cross-section analysis, 横断面分析Cross-section survey, 横断面调查Crosstabs , 交叉表Crosstabs 列联表分析Cross-tabulation table, 复合表Cube root, 立方根Cumulative distribution function, 分布函数Cumulative probability, 累计概率Curvature, 曲率/弯曲Curvature, 曲率Curve Estimation, 曲线拟合Curve fit , 曲线拟和Curve fitting, 曲线拟合Curvilinear regression, 曲线回归Curvilinear relation, 曲线关系Cut-and-try method, 尝试法Cycle, 周期Cyclist, 周期性D test, D检验Data acquisition, 资料收集Data bank, 数据库Data capacity, 数据容量Data deficiencies, 数据缺乏Data handling, 数据处理Data manipulation, 数据处理Data processing, 数据处理Data reduction, 数据缩减Data set, 数据集Data sources, 数据来源Data transformation, 数据变换Data validity, 数据有效性Data-in, 数据输入Data-out, 数据输出Dead time, 停滞期Degree of freedom, 自由度Degree of precision, 精密度Degree of reliability, 可靠性程度Degression, 递减Density function, 密度函数Density of data points, 数据点的密度Dependent variable, 应变量/依变量/因变量Dependent variable, 因变量Depth, 深度Derivative matrix, 导数矩阵Derivative-free methods, 无导数方法Design, 设计Determinacy, 确定性Determinant, 行列式Determinant, 决定因素Deviation, 离差Deviation from average, 离均差Diagnostic plot, 诊断图Dichotomous variable, 二分变量Differential equation, 微分方程Direct standardization, 直接标准化法Direct Oblimin, 斜交旋转Discrete variable, 离散型变量DISCRIMINANT, 判断Discriminant analysis, 判别分析Discriminant coefficient, 判别系数Discriminant function, 判别值Dispersion, 散布/分散度Disproportional, 不成比例的Disproportionate sub-class numbers, 不成比例次级组含量Distribution free, 分布无关性/免分布Distribution shape, 分布形状Distribution-free method, 任意分布法Distributive laws, 分配律Disturbance, 随机扰动项Dose response curve, 剂量反应曲线Double blind method, 双盲法Double blind trial, 双盲试验Double exponential distribution, 双指数分布Double logarithmic, 双对数Downward rank, 降秩Dual-space plot, 对偶空间图DUD, 无导数方法Duncan's new multiple range method, 新复极差法/Duncan新法Error Bar, 均值相关区间图Effect, 实验效应Eigenvalue, 特征值Eigenvector, 特征向量Ellipse, 椭圆Empirical distribution, 经验分布Empirical probability, 经验概率单位Enumeration data, 计数资料Equal sun-class number, 相等次级组含量Equally likely, 等可能Equivariance, 同变性Error, 误差/错误Error of estimate, 估计误差Error type I, 第一类错误Error type II, 第二类错误Estimand, 被估量Estimated error mean squares, 估计误差均方Estimated error sum of squares, 估计误差平方和Euclidean distance, 欧式距离Event, 事件Event, 事件Exceptional data point, 异常数据点Expectation plane, 期望平面Expectation surface, 期望曲面Expected values, 期望值Experiment, 实验Experimental sampling, 试验抽样Experimental unit, 试验单位Explained variance （已说明方差）Explanatory variable, 说明变量Exploratory data analysis, 探索性数据分析Explore Summarize, 探索-摘要Exponential curve, 指数曲线Exponential growth, 指数式增长EXSMOOTH, 指数平滑方法Extended fit, 扩充拟合Extra parameter, 附加参数Extrapolation, 外推法Extreme observation, 末端观测值Extremes, 极端值/极值F distribution, F分布F test, F检验Factor, 因素/因子Factor analysis, 因子分析Factor Analysis, 因子分析Factor score, 因子得分Factorial, 阶乘Factorial design, 析因试验设计False negative, 假阴性False negative error, 假阴性错误Family of distributions, 分布族Family of estimators, 估计量族Fanning, 扇面Fatality rate, 病死率Field investigation, 现场调查Field survey, 现场调查Finite population, 有限总体Finite-sample, 有限样本First derivative, 一阶导数First principal component, 第一主成分First quartile, 第一四分位数Fisher information, 费雪信息量Fitted value, 拟合值Fitting a curve, 曲线拟合Fixed base, 定基Fluctuation, 随机起伏Forecast, 预测Four fold table, 四格表Fourth, 四分点Fraction blow, 左侧比率Fractional error, 相对误差Frequency, 频率Frequency polygon, 频数多边图Frontier point, 界限点Function relationship, 泛函关系Gamma distribution, 伽玛分布Gauss increment, 高斯增量Gaussian distribution, 高斯分布/正态分布Gauss-Newton increment, 高斯-牛顿增量General census, 全面普查Generalized least squares, 综合最小平方法GENLOG (Generalized liner models), 广义线性模型Geometric mean, 几何平均数Gini's mean difference, 基尼均差GLM (General liner models), 通用线性模型Goodness of fit, 拟和优度/配合度Gradient of determinant, 行列式的梯度Graeco-Latin square, 希腊拉丁方Grand mean, 总均值Gross errors, 重大错误Gross-error sensitivity, 大错敏感度Group averages, 分组平均Grouped data, 分组资料Guessed mean, 假定平均数Half-life, 半衰期Hampel M-estimators, 汉佩尔M估计量Happenstance, 偶然事件Harmonic mean, 调和均数Hazard function, 风险均数Hazard rate, 风险率Heading, 标目Heavy-tailed distribution, 重尾分布Hessian array, 海森立体阵Heterogeneity, 不同质Heterogeneity of variance, 方差不齐Hierarchical classification, 组内分组Hierarchical clustering method, 系统聚类法High-leverage point, 高杠杆率点High-Low, 低区域图Higher Order Interaction Effects，高阶交互作用HILOGLINEAR, 多维列联表的层次对数线性模型Hinge, 折叶点Histogram, 直方图Historical cohort study, 历史性队列研究Holes, 空洞HOMALS, 多重响应分析Homogeneity of variance, 方差齐性Homogeneity test, 齐性检验Huber M-estimators, 休伯M估计量Hyperbola, 双曲线Hypothesis testing, 假设检验Hypothetical universe, 假设总体Image factoring,, 多元回归法Impossible event, 不可能事件Independence, 独立性Independent variable, 自变量Index, 指标/指数Indirect standardization, 间接标准化法Individual, 个体Inference band, 推断带Infinite population, 无限总体Infinitely great, 无穷大Infinitely small, 无穷小Influence curve, 影响曲线Information capacity, 信息容量Initial condition, 初始条件Initial estimate, 初始估计值Initial level, 最初水平Interaction, 交互作用Interaction terms, 交互作用项Intercept, 截距Interpolation, 内插法Interquartile range, 四分位距Interval estimation, 区间估计Intervals of equal probability, 等概率区间Intrinsic curvature, 固有曲率Invariance, 不变性Inverse matrix, 逆矩阵Inverse probability, 逆概率Inverse sine transformation, 反正弦变换Iteration, 迭代Jacobian determinant, 雅可比行列式Joint distribution function, 分布函数Joint probability, 联合概率Joint probability distribution, 联合概率分布K-Means Cluster逐步聚类分析K means method, 逐步聚类法Kaplan-Meier, 评估事件的时间长度Kaplan-Merier chart, Kaplan-Merier图Kendall's rank correlation, Kendall等级相关Kinetic, 动力学Kolmogorov-Smirnove test, 柯尔莫哥洛夫-斯米尔诺夫检验Kruskal and Wallis test, Kruskal及Wallis检验/多样本的秩和检验/H检验Kurtosis, 峰度Lack of fit, 失拟Ladder of powers, 幂阶梯Lag, 滞后Large sample, 大样本Large sample test, 大样本检验Latin square, 拉丁方Latin square design, 拉丁方设计Leakage, 泄漏Least favorable configuration, 最不利构形Least favorable distribution, 最不利分布Least significant difference, 最小显著差法Least square method, 最小二乘法Least Squared Criterion，最小二乘方准则Least-absolute-residuals estimates, 最小绝对残差估计Least-absolute-residuals fit, 最小绝对残差拟合Least-absolute-residuals line, 最小绝对残差线Legend, 图例L-estimator, L估计量L-estimator of location, 位置L估计量L-estimator of scale, 尺度L估计量Level, 水平Leveage Correction，杠杆率校正Life expectance, 预期期望寿命Life table, 寿命表Life table method, 生命表法Light-tailed distribution, 轻尾分布Likelihood function, 似然函数Likelihood ratio, 似然比line graph, 线图Linear correlation, 直线相关Linear equation, 线性方程Linear programming, 线性规划Linear regression, 直线回归Linear Regression, 线性回归Linear trend, 线性趋势Loading, 载荷Location and scale equivariance, 位置尺度同变性Location equivariance, 位置同变性Location invariance, 位置不变性Location scale family, 位置尺度族Log rank test, 时序检验Logarithmic curve, 对数曲线Logarithmic normal distribution, 对数正态分布Logarithmic scale, 对数尺度Logarithmic transformation, 对数变换Logic check, 逻辑检查Logistic distribution, 逻辑斯特分布Logit transformation, Logit转换LOGLINEAR, 多维列联表通用模型Lognormal distribution, 对数正态分布Lost function, 损失函数Low correlation, 低度相关Lower limit, 下限Lowest-attained variance, 最小可达方差LSD, 最小显著差法的简称Lurking variable, 潜在变量Main effect, 主效应Major heading, 主辞标目Marginal density function, 边缘密度函数Marginal probability, 边缘概率Marginal probability distribution, 边缘概率分布Matched data, 配对资料Matched distribution, 匹配过分布Matching of distribution, 分布的匹配Matching of transformation, 变换的匹配Mathematical expectation, 数学期望Mathematical model, 数学模型Maximum L-estimator, 极大极小L 估计量Maximum likelihood method, 最大似然法Mean, 均数Mean squares between groups, 组间均方Mean squares within group, 组内均方Means (Compare means), 均值-均值比较Median, 中位数Median effective dose, 半数效量Median lethal dose, 半数致死量Median polish, 中位数平滑Median test, 中位数检验Minimal sufficient statistic, 最小充分统计量Minimum distance estimation, 最小距离估计Minimum effective dose, 最小有效量Minimum lethal dose, 最小致死量Minimum variance estimator, 最小方差估计量MINITAB, 统计软件包Minor heading, 宾词标目Missing data, 缺失值Model specification, 模型的确定Modeling Statistics , 模型统计Models for outliers, 离群值模型Modifying the model, 模型的修正Modulus of continuity, 连续性模Morbidity, 发病率Most favorable configuration, 最有利构形MSC（多元散射校正）Multidimensional Scaling (ASCAL), 多维尺度/多维标度Multinomial Logistic Regression , 多项逻辑斯蒂回归Multiple comparison, 多重比较Multiple correlation , 复相关Multiple covariance, 多元协方差Multiple linear regression, 多元线性回归Multiple response , 多重选项Multiple solutions, 多解Multiplication theorem, 乘法定理Multiresponse, 多元响应Multi-stage sampling, 多阶段抽样Multivariate T distribution, 多元T分布Mutual exclusive, 互不相容Mutual independence, 互相独立Natural boundary, 自然边界Natural dead, 自然死亡Natural zero, 自然零Negative correlation, 负相关Negative linear correlation, 负线性相关Negatively skewed, 负偏Newman-Keuls method, q检验NK method, q检验No statistical significance, 无统计意义Nominal variable, 名义变量Nonconstancy of variability, 变异的非定常性Nonlinear regression, 非线性相关Nonparametric statistics, 非参数统计Nonparametric test, 非参数检验Nonparametric tests, 非参数检验Normal deviate, 正态离差Normal distribution, 正态分布Normal equation, 正规方程组Normal P-P, 正态概率分布图Normal Q-Q, 正态概率单位分布图Normal ranges, 正常范围Normal value, 正常值Normalization 归一化Nuisance parameter, 多余参数/讨厌参数Null hypothesis, 无效假设Numerical variable, 数值变量Objective function, 目标函数Observation unit, 观察单位Observed value, 观察值One sided test, 单侧检验One-way analysis of variance, 单因素方差分析Oneway ANOVA , 单因素方差分析Open sequential trial, 开放型序贯设计Optrim, 优切尾Optrim efficiency, 优切尾效率Order statistics, 顺序统计量Ordered categories, 有序分类Ordinal logistic regression , 序数逻辑斯蒂回归Ordinal variable, 有序变量Orthogonal basis, 正交基Orthogonal design, 正交试验设计Orthogonality conditions, 正交条件ORTHOPLAN, 正交设计Outlier cutoffs, 离群值截断点Outliers, 极端值OVERALS , 多组变量的非线性正规相关Overshoot, 迭代过度Paired design, 配对设计Paired sample, 配对样本Pairwise slopes, 成对斜率Parabola, 抛物线Parallel tests, 平行试验Parameter, 参数Parametric statistics, 参数统计Parametric test, 参数检验Pareto, 直条构成线图（又称佩尔托图）Partial correlation, 偏相关Partial regression, 偏回归Partial sorting, 偏排序Partials residuals, 偏残差Pattern, 模式PCA（主成分分析）Pearson curves, 皮尔逊曲线Peeling, 退层Percent bar graph, 百分条形图Percentage, 百分比Percentile, 百分位数Percentile curves, 百分位曲线Periodicity, 周期性Permutation, 排列P-estimator, P估计量Pie graph, 构成图,饼图Pitman estimator, 皮特曼估计量Pivot, 枢轴量Planar, 平坦Planar assumption, 平面的假设PLANCARDS, 生成试验的计划卡PLS（偏最小二乘法）Point estimation, 点估计Poisson distribution, 泊松分布Polishing, 平滑Polled standard deviation, 合并标准差Polled variance, 合并方差Polygon, 多边图Polynomial, 多项式Polynomial curve, 多项式曲线Population, 总体Population attributable risk, 人群归因危险度Positive correlation, 正相关Positively skewed, 正偏Posterior distribution, 后验分布Power of a test, 检验效能Precision, 精密度Predicted value, 预测值Preliminary analysis, 预备性分析Principal axis factoring,主轴因子法Principal component analysis, 主成分分析Prior distribution, 先验分布Prior probability, 先验概率Probabilistic model, 概率模型probability, 概率Probability density, 概率密度Product moment, 乘积矩/协方差Profile trace, 截面迹图Proportion, 比/构成比Proportion allocation in stratified random sampling, 按比例分层随机抽样Proportionate, 成比例Proportionate sub-class numbers, 成比例次级组含量Prospective study, 前瞻性调查Proximities, 亲近性Pseudo F test, 近似F检验Pseudo model, 近似模型Pseudosigma, 伪标准差Purposive sampling, 有目的抽样QR decomposition, QR分解Quadratic approximation, 二次近似Qualitative classification, 属性分类Qualitative method, 定性方法Quantile-quantile plot, 分位数-分位数图/Q-Q图Quantitative analysis, 定量分析Quartile, 四分位数Quick Cluster, 快速聚类Radix sort, 基数排序Random allocation, 随机化分组Random blocks design, 随机区组设计Random event, 随机事件Randomization, 随机化Range, 极差/全距Rank correlation, 等级相关Rank sum test, 秩和检验Rank test, 秩检验Ranked data, 等级资料Rate, 比率Ratio, 比例Raw data, 原始资料Raw residual, 原始残差Rayleigh's test, 雷氏检验Rayleigh's Z, 雷氏Z值Reciprocal, 倒数Reciprocal transformation, 倒数变换Recording, 记录Redescending estimators, 回降估计量Reducing dimensions, 降维Re-expression, 重新表达Reference set, 标准组Region of acceptance, 接受域Regression coefficient, 回归系数Regression sum of square, 回归平方和Rejection point, 拒绝点Relative dispersion, 相对离散度Relative number, 相对数Reliability, 可靠性Reparametrization, 重新设置参数Replication, 重复Report Summaries, 报告摘要Residual sum of square, 剩余平方和residual variance (剩余方差)Resistance, 耐抗性Resistant line, 耐抗线Resistant technique, 耐抗技术R-estimator of location, 位置R估计量R-estimator of scale, 尺度R估计量Retrospective study, 回顾性调查Ridge trace, 岭迹Ridit analysis, Ridit分析Rotation, 旋转Rounding, 舍入Row, 行Row effects, 行效应Row factor, 行因素RXC table, RXC表Sample, 样本Sample regression coefficient, 样本回归系数Sample size, 样本量Sample standard deviation, 样本标准差Sampling error, 抽样误差SAS(Statistical analysis system ), SAS统计软件包Scale, 尺度/量表Scatter diagram, 散点图Schematic plot, 示意图/简图Score test, 计分检验Screening, 筛检SEASON, 季节分析Second derivative, 二阶导数Second principal component, 第二主成分SEM (Structural equation modeling), 结构化方程模型Semi-logarithmic graph, 半对数图Semi-logarithmic paper, 半对数格纸Sensitivity curve, 敏感度曲线Sequential analysis, 贯序分析Sequence, 普通序列图Sequential data set, 顺序数据集Sequential design, 贯序设计Sequential method, 贯序法Sequential test, 贯序检验法Serial tests, 系列试验Short-cut method, 简捷法Sigmoid curve, S形曲线Sign function, 正负号函数Sign test, 符号检验Signed rank, 符号秩Significant Level, 显著水平Significance test, 显著性检验Significant figure, 有效数字Simple cluster sampling, 简单整群抽样Simple correlation, 简单相关Simple random sampling, 简单随机抽样Simple regression, 简单回归simple table, 简单表Sine estimator, 正弦估计量Single-valued estimate, 单值估计Singular matrix, 奇异矩阵Skewed distribution, 偏斜分布Skewness, 偏度Slash distribution, 斜线分布Slope, 斜率Smirnov test, 斯米尔诺夫检验Source of variation, 变异来源Spearman rank correlation, 斯皮尔曼等级相关Specific factor, 特殊因子Specific factor variance, 特殊因子方差Spectra , 频谱Spherical distribution, 球型正态分布Spread, 展布SPSS(Statistical package for the social science), SPSS统计软件包Spurious correlation, 假性相关Square root transformation, 平方根变换Stabilizing variance, 稳定方差Standard deviation, 标准差Standard error, 标准误Standard error of difference, 差别的标准误Standard error of estimate, 标准估计误差Standard error of rate, 率的标准误Standard normal distribution, 标准正态分布Standardization, 标准化Starting value, 起始值Statistic, 统计量Statistical control, 统计控制Statistical graph, 统计图Statistical inference, 统计推断Statistical table, 统计表Steepest descent, 最速下降法Stem and leaf display, 茎叶图Step factor, 步长因子Stepwise regression, 逐步回归Storage, 存Strata, 层（复数）Stratified sampling, 分层抽样Stratified sampling, 分层抽样Strength, 强度Stringency, 严密性Structural relationship, 结构关系Studentized residual, 学生化残差/t化残差Sub-class numbers, 次级组含量Subdividing, 分割Sufficient statistic, 充分统计量Sum of products, 积和Sum of squares, 离差平方和Sum of squares about regression, 回归平方和Sum of squares between groups, 组间平方和Sum of squares of partial regression, 偏回归平方和Sure event, 必然事件Survey, 调查Survival, 生存分析Survival rate, 生存率Suspended root gram, 悬吊根图Symmetry, 对称Systematic error, 系统误差Systematic sampling, 系统抽样Tags, 标签Tail area, 尾部面积Tail length, 尾长Tail weight, 尾重Tangent line, 切线Target distribution, 目标分布Taylor series, 泰勒级数Test(检验)Test of linearity, 线性检验Tendency of dispersion, 离散趋势Testing of hypotheses, 假设检验Theoretical frequency, 理论频数Time series, 时间序列Tolerance interval, 容忍区间Tolerance lower limit, 容忍下限Tolerance upper limit, 容忍上限Torsion, 扰率Total sum of square, 总平方和Total variation, 总变异Transformation, 转换Treatment, 处理Trend, 趋势Trend of percentage, 百分比趋势Trial, 试验Trial and error method, 试错法Tuning constant, 细调常数Two sided test, 双向检验Two-stage least squares, 二阶最小平方Two-stage sampling, 二阶段抽样Two-tailed test, 双侧检验Two-way analysis of variance, 双因素方差分析Two-way table, 双向表Type I error, 一类错误/α错误Type II error, 二类错误/β错误UMVU, 方差一致最小无偏估计简称Unbiased estimate, 无偏估计Unconstrained nonlinear regression , 无约束非线性回归Unequal subclass number, 不等次级组含量Ungrouped data, 不分组资料Uniform coordinate, 均匀坐标Uniform distribution, 均匀分布Uniformly minimum variance unbiased estimate, 方差一致最小无偏估计Unit, 单元Unordered categories, 无序分类Unweighted least squares, 未加权最小平方法Upper limit, 上限Upward rank, 升秩Vague concept, 模糊概念Validity, 有效性VARCOMP (Variance component estimation), 方差元素估计Variability, 变异性Variable, 变量Variance, 方差Variation, 变异Varimax orthogonal rotation, 方差最大正交旋转Volume of distribution, 容积W test, W检验Weibull distribution, 威布尔分布Weight, 权数Weighted Chi-square test, 加权卡方检验/Cochran检验Weighted linear regression method, 加权直线回归Weighted mean, 加权平均数Weighted mean square, 加权平均方差Weighted sum of square, 加权平方和Weighting coefficient, 权重系数Weighting method, 加权法W-estimation, W估计量W-estimation of location, 位置W估计量Width, 宽度Wilcoxon paired test, 威斯康星配对法/配对符号秩和检验Wild point, 野点/狂点Wild value, 野值/狂值Winsorized mean, 缩尾均值Withdraw, 失访Youden's index, 尤登指数Z test, Z检验Zero correlation, 零相关Z-transformation, Z变换Z-transformation, Z变换。
计量经济学英文解释
计量经济学英文解释English:Econometrics is a branch of economics that applies statistical methods and mathematical models to analyze and quantify the relationships between economic variables. It aims to provide empirical evidence and test economic theories by using real-world data. By employing various econometric techniques, such as regression analysis, time series analysis, and panel data analysis, econometricians are able to estimate and measure the parameters of economic models, assess the significance of different factors, and make predictions or forecasts about future economic outcomes. Econometrics plays a crucial role in several areas of economics, including macroeconomics, microeconomics, finance, and labor economics, as it helps in understanding economic phenomena, formulating economic policies, and making informed decisions. In addition to its theoretical applications, econometrics also has practical applications in business, government, and research institutions where data-driven decision-making is important. Overall, econometrics provides a systematic and quantitative approach toeconomics, allowing economists to study and analyze economic behavior and relationships in a rigorous and scientific manner.中文翻译:计量经济学是经济学的一个分支，它应用统计方法和数学模型来分析和量化经济变量之间的关系。
计量经济学英语词汇
计量经济学英语词汇Absolute deviation, 绝对离差Absolute number, 绝对数Absolute residuals, 绝对残差Acceleration array, 加速度立体阵Acceleration in an arbitrary direction, 任意方向上的加速度Acceleration normal, 法向加速度Acceleration space dimension, 加速度空间的维数Acceleration tangential, 切向加速度Acceleration vector, 加速度向量Acceptable hypothesis, 可接受假设Accumulation, 累积Accuracy, 准确度Actual frequency, 实际频数Adaptive estimator, 自适应估计量Addition, 相加Addition theorem, 加法定理Additive Noise, 加性噪声Additivity, 可加性Adjusted rate, 调整率Adjusted value, 校正值Admissible error, 容许误差Aggregation, 聚集性Alpha factoring,α因子法Alternative hypothesis, 备择假设Among groups, 组间Amounts, 总量Analysis of correlation, 相关分析Analysis of covariance, 协方差分析Analysis Of Effects, 效应分析Analysis Of Variance, 方差分析Analysis of regression, 回归分析Analysis of time series, 时间序列分析Analysis of variance, 方差分析Angular transformation, 角转换ANOVA （analysis of variance）, 方差分析ANOVA Models, 方差分析模型ANOVA table and eta, 分组计算方差分析Arcing, 弧/弧旋Arcsine transformation, 反正弦变换Area 区域图Area under the curve, 曲线面积AREG , 评估从一个时间点到下一个时间点回归相关时的误差ARIMA, 季节和非季节性单变量模型的极大似然估计Arithmetic grid paper, 算术格纸Arithmetic mean, 算术平均数Arrhenius relation, 艾恩尼斯关系Assessing fit, 拟合的评估Associative laws, 结合律Asymmetric distribution, 非对称分布Asymptotic bias, 渐近偏倚Asymptotic efficiency, 渐近效率Asymptotic variance, 渐近方差Attributable risk, 归因危险度Attribute data, 属性资料Attribution, 属性Autocorrelation, 自相关Autocorrelation of residuals, 残差的自相关Average, 平均数Average confidence interval length, 平均置信区间长度Average growth rate, 平均增长率Bar chart, 条形图Bar graph, 条形图Base period, 基期Bayes' theorem , Bayes定理Bell-shaped curve, 钟形曲线Bernoulli distribution, 伯努力分布Best-trim estimator, 最好切尾估计量Bias, 偏性Binary logistic regression, 二元逻辑斯蒂回归Binomial distribution, 二项分布Bisquare, 双平方Bivariate Correlate, 二变量相关Bivariate normal distribution, 双变量正态分布Bivariate normal population, 双变量正态总体Biweight interval, 双权区间Biweight M-estimator, 双权M估计量Block, 区组/配伍组BMDP(Biomedical computer programs), BMDP统计软件包Boxplots, 箱线图/箱尾图Breakdown bound, 崩溃界/崩溃点Canonical correlation, 典型相关Caption, 纵标目Case-control study, 病例对照研究Categorical variable, 分类变量Catenary, 悬链线Cauchy distribution, 柯西分布Cause-and-effect relationship, 因果关系Cell, 单元Censoring, 终检Center of symmetry, 对称中心Centering and scaling, 中心化和定标Central tendency, 集中趋势Central value, 中心值CHAID -χ2 Automatic Interaction Detector, 卡方自动交互检测Chance, 机遇Chance error, 随机误差Chance variable, 随机变量Characteristic equation, 特征方程Characteristic root, 特征根Characteristic vector, 特征向量Chebshev criterion of fit, 拟合的切比雪夫准则Chernoff faces, 切尔诺夫脸谱图Chi-square test, 卡方检验/χ2检验Choleskey decomposition, 乔洛斯基分解Circle chart, 圆图Class interval, 组距Class mid-value, 组中值Class upper limit, 组上限Classified variable, 分类变量Cluster analysis, 聚类分析Cluster sampling, 整群抽样Code, 代码Coded data, 编码数据Coding, 编码Coefficient of contingency, 列联系数Coefficient of determination, 决定系数Coefficient of multiple correlation, 多重相关系数Coefficient of partial correlation, 偏相关系数Coefficient of production-moment correlation, 积差相关系数Coefficient of rank correlation, 等级相关系数Coefficient of regression, 回归系数Coefficient of skewness, 偏度系数Coefficient of variation, 变异系数Cohort study, 队列研究Collinearity, 共线性Column, 列Column effect, 列效应Column factor, 列因素Combination pool, 合并Combinative table, 组合表Common factor, 共性因子Common regression coefficient, 公共回归系数Common value, 共同值Common variance, 公共方差Common variation, 公共变异Communality variance, 共性方差Comparability, 可比性Comparison of bathes, 批比较Comparison value, 比较值Compartment model, 分部模型Compassion, 伸缩Complement of an event, 补事件Complete association, 完全正相关Complete dissociation, 完全不相关Complete statistics, 完备统计量Completely randomized design, 完全随机化设计Composite event, 联合事件Composite events, 复合事件Concavity, 凹性Conditional expectation, 条件期望Conditional likelihood, 条件似然Conditional probability, 条件概率Conditionally linear, 依条件线性Confidence interval, 置信区间Confidence limit, 置信限Confidence lower limit, 置信下限Confidence upper limit, 置信上限Confirmatory Factor Analysis , 验证性因子分析Confirmatory research, 证实性实验研究Confounding factor, 混杂因素Conjoint, 联合分析Consistency, 相合性Consistency check, 一致性检验Consistent asymptotically normal estimate, 相合渐近正态估计Consistent estimate, 相合估计Constrained nonlinear regression, 受约束非线性回归Constraint, 约束Contaminated distribution, 污染分布Contaminated Gausssian, 污染高斯分布Contaminated normal distribution, 污染正态分布Contamination, 污染Contamination model, 污染模型Contingency table, 列联表Contour, 边界线Contribution rate, 贡献率Control, 对照, 质量控制图Controlled experiments, 对照实验Conventional depth, 常规深度Convolution, 卷积Corrected factor, 校正因子Corrected mean, 校正均值Correction coefficient, 校正系数Correctness, 正确性Correlation coefficient, 相关系数Correlation, 相关性Correlation index, 相关指数Correspondence, 对应Counting, 计数Counts, 计数/频数Covariance, 协方差Covariant, 共变Cox Regression, Cox回归Criteria for fitting, 拟合准则Criteria of least squares, 最小二乘准则Critical ratio, 临界比Critical region, 拒绝域Critical value, 临界值Cross-over design, 交叉设计Cross-section analysis, 横断面分析Cross-section survey, 横断面调查Crosstabs , 交叉表Crosstabs 列联表分析Cross-tabulation table, 复合表Cube root, 立方根Cumulative distribution function, 分布函数Cumulative probability, 累计概率Curvature, 曲率/弯曲Curvature, 曲率Curve Estimation, 曲线拟合Curve fit , 曲线拟和Curve fitting, 曲线拟合Curvilinear regression, 曲线回归Curvilinear relation, 曲线关系Cut-and-try method, 尝试法Cycle, 周期Cyclist, 周期性D test, D检验Data acquisition, 资料收集Data bank, 数据库Data capacity, 数据容量Data deficiencies, 数据缺乏Data handling, 数据处理Data manipulation, 数据处理Data processing, 数据处理Data reduction, 数据缩减Data set, 数据集Data sources, 数据来源Data transformation, 数据变换Data validity, 数据有效性Data-in, 数据输入Data-out, 数据输出Dead time, 停滞期Degree of freedom, 自由度Degree of precision, 精密度Degree of reliability, 可靠性程度Degression, 递减Density function, 密度函数Density of data points, 数据点的密度Dependent variable, 应变量/依变量/因变量Dependent variable, 因变量Depth, 深度Derivative matrix, 导数矩阵Derivative-free methods, 无导数方法Design, 设计Determinacy, 确定性Determinant, 行列式Determinant, 决定因素Deviation, 离差Deviation from average, 离均差Diagnostic plot, 诊断图Dichotomous variable, 二分变量Differential equation, 微分方程Direct standardization, 直接标准化法Direct Oblimin, 斜交旋转Discrete variable, 离散型变量DISCRIMINANT, 判断Discriminant analysis, 判别分析Discriminant coefficient, 判别系数Discriminant function, 判别值Dispersion, 散布/分散度Disproportional, 不成比例的Disproportionate sub-class numbers, 不成比例次级组含量Distribution free, 分布无关性/免分布Distribution shape, 分布形状Distribution-free method, 任意分布法Distributive laws, 分配律Disturbance, 随机扰动项Dose response curve, 剂量反应曲线Double blind method, 双盲法Double blind trial, 双盲试验Double exponential distribution, 双指数分布Double logarithmic, 双对数Downward rank, 降秩Dual-space plot, 对偶空间图DUD, 无导数方法Duncan's new multiple range method, 新复极差法/Duncan新法Error Bar, 均值相关区间图Effect, 实验效应Eigenvalue, 特征值Eigenvector, 特征向量Ellipse, 椭圆Empirical distribution, 经验分布Empirical probability, 经验概率单位Enumeration data, 计数资料Equal sun-class number, 相等次级组含量Equally likely, 等可能Equivariance, 同变性Error, 误差/错误Error of estimate, 估计误差Error type I, 第一类错误Error type II, 第二类错误Estimand, 被估量Estimated error mean squares, 估计误差均方Estimated error sum of squares, 估计误差平方和Euclidean distance, 欧式距离Event, 事件Event, 事件Exceptional data point, 异常数据点Expectation plane, 期望平面Expectation surface, 期望曲面Expected values, 期望值Experiment, 实验Experimental sampling, 试验抽样Experimental unit, 试验单位Explained variance （已说明方差）Explanatory variable, 说明变量Exploratory data analysis, 探索性数据分析Explore Summarize, 探索-摘要Exponential curve, 指数曲线Exponential growth, 指数式增长EXSMOOTH, 指数平滑方法Extended fit, 扩充拟合Extra parameter, 附加参数Extrapolation, 外推法Extreme observation, 末端观测值Extremes, 极端值/极值F distribution, F分布F test, F检验Factor, 因素/因子Factor analysis, 因子分析Factor Analysis, 因子分析Factor score, 因子得分Factorial, 阶乘Factorial design, 析因试验设计False negative, 假阴性False negative error, 假阴性错误Family of distributions, 分布族Family of estimators, 估计量族Fanning, 扇面Fatality rate, 病死率Field investigation, 现场调查Field survey, 现场调查Finite population, 有限总体Finite-sample, 有限样本First derivative, 一阶导数First principal component, 第一主成分First quartile, 第一四分位数Fisher information, 费雪信息量Fitted value, 拟合值Fitting a curve, 曲线拟合Fixed base, 定基Fluctuation, 随机起伏Forecast, 预测Four fold table, 四格表Fourth, 四分点Fraction blow, 左侧比率Fractional error, 相对误差Frequency, 频率Frequency polygon, 频数多边图Frontier point, 界限点Function relationship, 泛函关系Gamma distribution, 伽玛分布Gauss increment, 高斯增量Gaussian distribution, 高斯分布/正态分布Gauss-Newton increment, 高斯-牛顿增量General census, 全面普查Generalized least squares, 综合最小平方法GENLOG (Generalized liner models), 广义线性模型Geometric mean, 几何平均数Gini's mean difference, 基尼均差GLM (General liner models), 通用线性模型Goodness of fit, 拟和优度/配合度Gradient of determinant, 行列式的梯度Graeco-Latin square, 希腊拉丁方Grand mean, 总均值Gross errors, 重大错误Gross-error sensitivity, 大错敏感度Group averages, 分组平均Grouped data, 分组资料Guessed mean, 假定平均数Half-life, 半衰期Hampel M-estimators, 汉佩尔M估计量Happenstance, 偶然事件Harmonic mean, 调和均数Hazard function, 风险均数Hazard rate, 风险率Heading, 标目Heavy-tailed distribution, 重尾分布Hessian array, 海森立体阵Heterogeneity, 不同质Heterogeneity of variance, 方差不齐Hierarchical classification, 组内分组Hierarchical clustering method, 系统聚类法High-leverage point, 高杠杆率点High-Low, 低区域图Higher Order Interaction Effects，高阶交互作用HILOGLINEAR, 多维列联表的层次对数线性模型Hinge, 折叶点Histogram, 直方图Historical cohort study, 历史性队列研究Holes, 空洞HOMALS, 多重响应分析Homogeneity of variance, 方差齐性Homogeneity test, 齐性检验Huber M-estimators, 休伯M估计量Hyperbola, 双曲线Hypothesis testing, 假设检验Hypothetical universe, 假设总体Image factoring,, 多元回归法Impossible event, 不可能事件Independence, 独立性Independent variable, 自变量Index, 指标/指数Indirect standardization, 间接标准化法Individual, 个体Inference band, 推断带Infinite population, 无限总体Infinitely great, 无穷大Infinitely small, 无穷小Influence curve, 影响曲线Information capacity, 信息容量Initial condition, 初始条件Initial estimate, 初始估计值Initial level, 最初水平Interaction, 交互作用Interaction terms, 交互作用项Intercept, 截距Interpolation, 内插法Interquartile range, 四分位距Interval estimation, 区间估计Intervals of equal probability, 等概率区间Intrinsic curvature, 固有曲率Invariance, 不变性Inverse matrix, 逆矩阵Inverse probability, 逆概率Inverse sine transformation, 反正弦变换Iteration, 迭代Jacobian determinant, 雅可比行列式Joint distribution function, 分布函数Joint probability, 联合概率Joint probability distribution, 联合概率分布K-Means Cluster逐步聚类分析K means method, 逐步聚类法Kaplan-Meier, 评估事件的时间长度Kaplan-Merier chart,Kaplan-Merier图Kendall's rank correlation, Kendall等级相关Kinetic, 动力学Kolmogorov-Smirnove test, 柯尔莫哥洛夫-斯米尔诺夫检验Kruskal and Wallis test, Kruskal 及Wallis检验/多样本的秩和检验/H 检验Kurtosis, 峰度Lack of fit, 失拟Ladder of powers, 幂阶梯Lag, 滞后Large sample, 大样本Large sample test, 大样本检验Latin square, 拉丁方Latin square design, 拉丁方设计Leakage, 泄漏Least favorable configuration, 最不利构形Least favorable distribution, 最不利分布Least significant difference, 最小显着差法Least square method, 最小二乘法Least Squared Criterion，最小二乘方准则Least-absolute-residuals estimates, 最小绝对残差估计Least-absolute-residuals fit, 最小绝对残差拟合Least-absolute-residuals line, 最小绝对残差线Legend, 图例L-estimator, L估计量L-estimator of location, 位置L估计量L-estimator of scale, 尺度L估计量Level, 水平Leveage Correction，杠杆率校正Life expectance, 预期期望寿命Life table, 寿命表Life table method, 生命表法Light-tailed distribution, 轻尾分布Likelihood function, 似然函数Likelihood ratio, 似然比line graph, 线图Linear correlation, 直线相关Linear equation, 线性方程Linear programming, 线性规划Linear regression, 直线回归Linear Regression, 线性回归Linear trend, 线性趋势Loading, 载荷Location and scale equivariance, 位置尺度同变性Location equivariance, 位置同变性Location invariance, 位置不变性Location scale family, 位置尺度族Log rank test, 时序检验Logarithmic curve, 对数曲线Logarithmic normal distribution, 对数正态分布Logarithmic scale, 对数尺度Logarithmic transformation, 对数变换Logic check, 逻辑检查Logistic distribution, 逻辑斯特分布Logit transformation, Logit转换LOGLINEAR, 多维列联表通用模型Lognormal distribution, 对数正态分布Lost function, 损失函数Low correlation, 低度相关Lower limit, 下限Lowest-attained variance, 最小可达方差LSD, 最小显着差法的简称Lurking variable, 潜在变量Main effect, 主效应Major heading, 主辞标目Marginal density function, 边缘密度函数Marginal probability, 边缘概率Marginal probability distribution, 边缘概率分布Matched data, 配对资料Matched distribution, 匹配过分布Matching of distribution, 分布的匹配Matching of transformation, 变换的匹配Mathematical expectation, 数学期望Mathematical model, 数学模型Maximum L-estimator, 极大极小L 估计量Maximum likelihood method, 最大似然法Mean, 均数Mean squares between groups, 组间均方Mean squares within group, 组内均方Means (Compare means), 均值-均值比较Median, 中位数Median effective dose, 半数效量Median lethal dose, 半数致死量Median polish, 中位数平滑Median test, 中位数检验Minimal sufficient statistic, 最小充分统计量Minimum distance estimation, 最小距离估计Minimum effective dose, 最小有效量Minimum lethal dose, 最小致死量Minimum variance estimator, 最小方差估计量MINITAB, 统计软件包Minor heading, 宾词标目Missing data, 缺失值Model specification, 模型的确定Modeling Statistics , 模型统计Models for outliers, 离群值模型Modifying the model, 模型的修正Modulus of continuity, 连续性模Morbidity, 发病率Most favorable configuration, 最有利构形MSC（多元散射校正）Multidimensional Scaling (ASCAL), 多维尺度/多维标度Multinomial Logistic Regression , 多项逻辑斯蒂回归Multiple comparison, 多重比较Multiple correlation , 复相关Multiple covariance, 多元协方差Multiple linear regression, 多元线性回归Multiple response , 多重选项Multiple solutions, 多解Multiplication theorem, 乘法定理Multiresponse, 多元响应Multi-stage sampling, 多阶段抽样Multivariate T distribution, 多元T分布Mutual exclusive, 互不相容Mutual independence, 互相独立Natural boundary, 自然边界Natural dead, 自然死亡Natural zero, 自然零Negative correlation, 负相关Negative linear correlation, 负线性相关Negatively skewed, 负偏Newman-Keuls method, q检验NK method, q检验No statistical significance, 无统计意义Nominal variable, 名义变量Nonconstancy of variability, 变异的非定常性Nonlinear regression, 非线性相关Nonparametric statistics, 非参数统计Nonparametric test, 非参数检验Nonparametric tests, 非参数检验Normal deviate, 正态离差Normal distribution, 正态分布Normal equation, 正规方程组Normal P-P, 正态概率分布图Normal Q-Q, 正态概率单位分布图Normal ranges, 正常范围Normal value, 正常值Normalization 归一化Nuisance parameter, 多余参数/讨厌参数Null hypothesis, 无效假设Numerical variable, 数值变量Objective function, 目标函数Observation unit, 观察单位Observed value, 观察值One sided test, 单侧检验One-way analysis of variance, 单因素方差分析Oneway ANOVA , 单因素方差分析Open sequential trial, 开放型序贯设计Optrim, 优切尾Optrim efficiency, 优切尾效率Order statistics, 顺序统计量Ordered categories, 有序分类Ordinal logistic regression , 序数逻辑斯蒂回归Ordinal variable, 有序变量Orthogonal basis, 正交基Orthogonal design, 正交试验设计Orthogonality conditions, 正交条件ORTHOPLAN, 正交设计Outlier cutoffs, 离群值截断点Outliers, 极端值OVERALS , 多组变量的非线性正规相关Overshoot, 迭代过度Paired design, 配对设计Paired sample, 配对样本Pairwise slopes, 成对斜率Parabola, 抛物线Parallel tests, 平行试验Parameter, 参数Parametric statistics, 参数统计Parametric test, 参数检验Pareto, 直条构成线图（又称佩尔托图）Partial correlation, 偏相关Partial regression, 偏回归Partial sorting, 偏排序Partials residuals, 偏残差Pattern, 模式PCA（主成分分析）Pearson curves, 皮尔逊曲线Peeling, 退层Percent bar graph, 百分条形图Percentage, 百分比Percentile, 百分位数Percentile curves, 百分位曲线Periodicity, 周期性Permutation, 排列P-estimator, P估计量Pie graph, 构成图,饼图Pitman estimator, 皮特曼估计量Pivot, 枢轴量Planar, 平坦Planar assumption, 平面的假设PLANCARDS, 生成试验的计划卡PLS（偏最小二乘法）Point estimation, 点估计Poisson distribution, 泊松分布Polishing, 平滑Polled standard deviation, 合并标准差Polled variance, 合并方差Polygon, 多边图Polynomial, 多项式Polynomial curve, 多项式曲线Population, 总体Population attributable risk, 人群归因危险度Positive correlation, 正相关Positively skewed, 正偏Posterior distribution, 后验分布Power of a test, 检验效能Precision, 精密度Predicted value, 预测值Preliminary analysis, 预备性分析Principal axis factoring,主轴因子法Principal component analysis, 主成分分析Prior distribution, 先验分布Prior probability, 先验概率Probabilistic model, 概率模型probability, 概率Probability density, 概率密度Product moment, 乘积矩/协方差Profile trace, 截面迹图Proportion, 比/构成比Proportion allocation in stratified random sampling, 按比例分层随机抽样Proportionate, 成比例Proportionate sub-class numbers, 成比例次级组含量Prospective study, 前瞻性调查Proximities, 亲近性Pseudo F test, 近似F检验Pseudo model, 近似模型Pseudosigma, 伪标准差Purposive sampling, 有目的抽样QR decomposition, QR分解Quadratic approximation, 二次近似Qualitative classification, 属性分类Qualitative method, 定性方法Quantile-quantile plot, 分位数-分位数图/Q-Q图Quantitative analysis, 定量分析Quartile, 四分位数Quick Cluster, 快速聚类Radix sort, 基数排序Random allocation, 随机化分组Random blocks design, 随机区组设计Random event, 随机事件Randomization, 随机化Range, 极差/全距Rank correlation, 等级相关Rank sum test, 秩和检验Rank test, 秩检验Ranked data, 等级资料Rate, 比率Ratio, 比例Raw data, 原始资料Raw residual, 原始残差Rayleigh's test, 雷氏检验Rayleigh's Z, 雷氏Z值Reciprocal, 倒数Reciprocal transformation, 倒数变换Recording, 记录Redescending estimators, 回降估计量Reducing dimensions, 降维Re-expression, 重新表达Reference set, 标准组Region of acceptance, 接受域Regression coefficient, 回归系数Regression sum of square, 回归平方和Rejection point, 拒绝点Relative dispersion, 相对离散度Relative number, 相对数Reliability, 可靠性Reparametrization, 重新设置参数Replication, 重复Report Summaries, 报告摘要Residual sum of square, 剩余平方和residual variance (剩余方差) Resistance, 耐抗性Resistant line, 耐抗线Resistant technique, 耐抗技术R-estimator of location, 位置R估计量R-estimator of scale, 尺度R估计量Retrospective study, 回顾性调查Ridge trace, 岭迹Ridit analysis, Ridit分析Rotation, 旋转Rounding, 舍入Row, 行Row effects, 行效应Row factor, 行因素RXC table, RXC表Sample, 样本Sample regression coefficient, 样本回归系数Sample size, 样本量Sample standard deviation, 样本标准差Sampling error, 抽样误差SAS(Statistical analysis system ), SAS统计软件包Scale, 尺度/量表Scatter diagram, 散点图Schematic plot, 示意图/简图Score test, 计分检验Screening, 筛检SEASON, 季节分析Second derivative, 二阶导数Second principal component, 第二主成分SEM (Structural equation modeling), 结构化方程模型Semi-logarithmic graph, 半对数图Semi-logarithmic paper, 半对数格纸Sensitivity curve, 敏感度曲线Sequential analysis, 贯序分析Sequence, 普通序列图Sequential data set, 顺序数据集Sequential design, 贯序设计Sequential method, 贯序法Sequential test, 贯序检验法Serial tests, 系列试验Short-cut method, 简捷法Sigmoid curve, S形曲线Sign function, 正负号函数Sign test, 符号检验Signed rank, 符号秩Significant Level, 显着水平Significance test, 显着性检验Significant figure, 有效数字Simple cluster sampling, 简单整群抽样Simple correlation, 简单相关Simple random sampling, 简单随机抽样Simple regression, 简单回归simple table, 简单表Sine estimator, 正弦估计量Single-valued estimate, 单值估计Singular matrix, 奇异矩阵Skewed distribution, 偏斜分布Skewness, 偏度Slash distribution, 斜线分布Slope, 斜率Smirnov test, 斯米尔诺夫检验Source of variation, 变异来源Spearman rank correlation, 斯皮尔曼等级相关Specific factor, 特殊因子Specific factor variance, 特殊因子方差Spectra , 频谱Spherical distribution, 球型正态分布Spread, 展布SPSS(Statistical package for the social science), SPSS统计软件包Spurious correlation, 假性相关Square root transformation, 平方根变换Stabilizing variance, 稳定方差Standard deviation, 标准差Standard error, 标准误Standard error of difference, 差别的标准误Standard error of estimate, 标准估计误差Standard error of rate, 率的标准误Standard normal distribution, 标准正态分布Standardization, 标准化Starting value, 起始值Statistic, 统计量Statistical control, 统计控制Statistical graph, 统计图Statistical inference, 统计推断Statistical table, 统计表Steepest descent, 最速下降法Stem and leaf display, 茎叶图Step factor, 步长因子Stepwise regression, 逐步回归Storage, 存Strata, 层（复数）Stratified sampling, 分层抽样Stratified sampling, 分层抽样Strength, 强度Stringency, 严密性Structural relationship, 结构关系Studentized residual, 学生化残差/t化残差Sub-class numbers, 次级组含量Subdividing, 分割Sufficient statistic, 充分统计量Sum of products, 积和Sum of squares, 离差平方和Sum of squares about regression, 回归平方和Sum of squares between groups, 组间平方和Sum of squares of partial regression, 偏回归平方和Sure event, 必然事件Survey, 调查Survival, 生存分析Survival rate, 生存率Suspended root gram, 悬吊根图Symmetry, 对称Systematic error, 系统误差Systematic sampling, 系统抽样Tags, 标签Tail area, 尾部面积Tail length, 尾长Tail weight, 尾重Tangent line, 切线Target distribution, 目标分布Taylor series, 泰勒级数Test(检验)Test of linearity, 线性检验Tendency of dispersion, 离散趋势Testing of hypotheses, 假设检验Theoretical frequency, 理论频数Time series, 时间序列Tolerance interval, 容忍区间Tolerance lower limit, 容忍下限Tolerance upper limit, 容忍上限Torsion, 扰率Total sum of square, 总平方和Total variation, 总变异Transformation, 转换Treatment, 处理Trend, 趋势Trend of percentage, 百分比趋势Trial, 试验Trial and error method, 试错法Tuning constant, 细调常数Two sided test, 双向检验Two-stage least squares, 二阶最小平方Two-stage sampling, 二阶段抽样Two-tailed test, 双侧检验Two-way analysis of variance, 双因素方差分析Two-way table, 双向表Type I error, 一类错误/α错误Type II error, 二类错误/β错误UMVU, 方差一致最小无偏估计简称Unbiased estimate, 无偏估计Unconstrained nonlinear regression , 无约束非线性回归Unequal subclass number, 不等次级组含量Ungrouped data, 不分组资料Uniform coordinate, 均匀坐标Uniform distribution, 均匀分布Uniformly minimum variance unbiased estimate, 方差一致最小无偏估计Unit, 单元Unordered categories, 无序分类Unweighted least squares, 未加权最小平方法Upper limit, 上限Upward rank, 升秩Vague concept, 模糊概念Validity, 有效性VARCOMP (Variance component estimation), 方差元素估计Variability, 变异性Variable, 变量Variance, 方差Variation, 变异Varimax orthogonal rotation, 方差最大正交旋转Volume of distribution, 容积W test, W检验Weibull distribution, 威布尔分布Weight, 权数Weighted Chi-square test, 加权卡方检验/Cochran检验Weighted linear regression method, 加权直线回归Weighted mean, 加权平均数Weighted mean square, 加权平均方差Weighted sum of square, 加权平方和Weighting coefficient, 权重系数Weighting method, 加权法W-estimation, W估计量W-estimation of location, 位置W估计量Width, 宽度Wilcoxon paired test, 威斯康星配对法/配对符号秩和检验Wild point, 野点/狂点Wild value, 野值/狂值Winsorized mean, 缩尾均值Withdraw, 失访Youden's index, 尤登指数Z test, Z检验Zero correlation, 零相关Z-transformation, Z变换Z-transformation, Z变换。
计量经济学。 中文翻译
附录 A审查的数学本质学习目标：基于材料,在这个appdenix,你一定能做到1、工作总结与单、双操作。
2、解释的指数函数关系和自然对数3、解释和运用科学的符号4、定义一个线性关系,而不是一种非线性关系5、计算上的点弹性线性函数或其他任何功能表a . 26、解释的主要特点log-linear的函数形式7、解释的主要特点log-log的函数形式8、解释的主要特点linear-log的函数形式关键词绝对值不平等偏导数反对数整数百分比变化渐进截距菲利普斯曲线在其他条件不变的情况下无理数二次函数三次函数线性相关衍生对数实数双求和对数线性函数反函数 log-log函数相对变化弹性边际效应科学计数法指数函数自然对数坡指数线性不相关求和符号我们假设你已经学过基础数学的知识，希望你能明白分化与整合的微积分概念，虽然这些工具不是学好这门课所必须的。
在本附录中我们将复习一些你可能随时随地用到的基本的数学概念。
A．1 总结整本书我们都将使用一个源于希腊的求和符号∑，以至于精简代数表达。
比如，X代表一个经济变量，又如在特定的某一天一家商店出售一升量的减肥苏打饮料。
我们可能想获得前半个月出售的总瓶数，我们可以记每天出售瓶数为x1x2………x15。
我们所要求的总数即为这些数的加总，或者是x1+x2+……. x15。
而不是每次写出这个总数，我们将用∑=151i i x来表示，即为∑=151i ix =x1+x 2+……. x 15。
如果我们所要加总的数有n 个那么可以表示为∑nix i=x 1+x 2+…….x n关于这个式子： 1、 符号∑是一个希腊字母，意思是“求和”2、 字母i 表示求和指数，这个字母可以用任意字母表示如k 、j 或者是t3、∑n ix i这个式子表示从x 1一直加总到x n 、4、∑n ix i还可以写作∑=n1i ix，这两个式子的意思是一样的5、 式子中1表示加总的最低项n 表示加总的最高项。
下列计算就适用于求和运算1、x 1 x 2……. x n 相加就可以表达成：∑=n1i ix =x 1+x2+…….x n2、如果a 是个常量那么：∑=n 1i iax=a ∑=n1i ix3、如果a 是个常量那么：∑=n1i a =a+a+……a=na4、如果X 和Y 都是变量，那么：）（y x in1i i +∑==∑=n 1i ix +∑=n1i iy5、如果X 和Y 都是变量，那么：）（y x in 1i i b a +∑==a ∑=n1i ix+b ∑=n1i iy6、n 个数: x 1 x 2………x n 算术平均数是：x ---- =∑=n1i ixn=x 1+x 2+…….x nn7、离差和为：∑=n 1i 1X -x ）（=∑=n 1i ix--∑=n1i ix=∑=n 1i ix--n x ----=08、我们经常使用几个函数相加的简略形式，比如，几个关于X 的函数相加：）（∑=n1i i x f =f（x 1）+f （x 2）+……….f （x n ）=∑if （xi）=∑xx f ）（9、几个求和的迹象可以用一个表达式来表达，假设变量Y 有n 项、X 有m 项，使f(x ，y)=x+y 。
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附录B复习概率相关概念：学习目标：基于这个附录的材料，你应该能够：1、解释一个随机变量和它的值之间的不同，并给出一个例子。
2、解释离散型随机变量与连续型随机变量之间的不同，并分别给出一个例子。
3、描述离散型随机变量的概率密度函数的特征，并给出一个例子。
4、在给定的离散型概率函数中计算事件的概率。
5、解释下面语句的涵义：在离散型随机变量中取值2时所对应的概率为0.3。
6、解释连续型随机变量的概率密度函数与离散型随机变量的密度函数之间的不同。
7、怎样用代数的方法计算给定的连续型随机变量的概率。
8、直观的解释一个随机变量的均值或者期望值的概念9、结合离散型随机变量的期望值概念，在B.9给定的概率密度函数f(x)和函数g（x）来计算期望。
10、理解离散随机变量的方差的定义，并解释当方差值越大时随机变量取值更分散的意义。
11、运用一个联合概率密度函数（表格）表示两个离散型随机变量并且计算联合事件的概率，并且找到每个单独随机变量的边缘概率密度函数。
12、在给定另外一个离散型随机变量取值和他们的联合密度函数的情况下会找出一个离散型随机变量的条件概率密度函数。
13、给出一个关于两个随机变量相互独立的直观的解释，并且给出两个随机变量独立的条件。
举出两个随机变量相互独立和不独立的实例。
14、定义两个随机变量的协方差和相关性，并且在给定两个离散型随机变量的联合概率函数的情况下计算协方差和相关性。
15、找出随机变量和的均值和方差。
16、结合表1和电脑软件计算正态分布的概率。
关键词：二进制变量自由度众数二进制随机变量离散型随机变量正态分布连续型概分布试验概率条件概率密度函数 F分率分布函数期望值概率密度函数2布概率密度函数条件概率联合概率密度随机变量连续随机变量函数标准差相关性边缘分布标准正态分布协方差均值独立累积分布中数方差我们假定你已经学过一些基本概率统计的课程，在这章附录中我们将复习一些关于概率统计的基本概念，B.1部分我们回顾离散和连续型随机变量；在B.2部分复习概率分布；B.3部分介绍联合概率分布、定义了条件概率和独立的概念；在B.4部分我们将复习概率分布的一些特性，重点复习期望和方差；在B.5部分总结一些重我们常用的概率分布的重要特征：正态分布、t分布、F分布。
B.1 随机变量俗话说世界上只有死亡和纳税是确定的。
虽然不是这句话的本意，但这个观点还是指出我们在生活中遇到的大部分事情是不确定的。
我们不知道我们球队在下一个赛季会赢多少场，你肯定不知道在第一次考试中会得多少分，我们不知道明天的股指是多少。
这些事情或是结果都是不确定的或者说是随机的。
概率给了我们一个讨论可能性结果的方法。
一个随机变量是在观察前取值未知的量，换句话说就是它是不能准确预测的变化量。
每一个随机变量都有一组可能取的值。
如果用W 代表我们球队下赛季赢球的场数，如果最多只有13场比赛的话,那么W 可以取0、1、2、……13。
这是个离散型随机变量，因为它只可取有些可数的实数值。
另外关于离散型随机变量的实例有随机挑选的家庭中拥有电脑的数量以及下一年你看医生的次数。
如果一个试验只有两个结果发生，比如，在电话问卷中，别人问你你是否有大学学历，你的回答只能“是”或者“不是”这样的事件我就说它符合二项分布。
用“1”代表“是”用“0”代表“不是”。
二项分布是离散型的，用来代替性别（男或女）、种族（白人，非白人）等性质、特征。
美国的ＧＮＰ是另一例随机变量，因为它的数值在观察到之前是不确定的。
在2007年的第二季度，它的值是$138394亿 美元(季度调整的年增长率)。
诚然，ＧＮＰ是用美元来衡量的，并且可以整美元来计算，但是这个值太过巨大以至于计算个人的美元收入变得毫无意义。
从实际角度看，ＧＮＰ可以取从零至无限间的任意值，它是一个连续性随机变量。
其他一般的宏观经济随机变量如利率、投资、消费，也看被认作连续性随机变量。
在经济学中，股市指数，像道—琼斯指数一样，也认为是连续的。
使这些变量得以连续的关键特性是它们可以取区间内的任意值。
B.2 概率分布概率通常用试验来定义。
转骰子是一个试验，我们可以得到六种结果。
如果骰子是均匀的，那么每种可能将以1/6的概率出现，假设试验进行无数次的话。
1/6这个概率的得出是因为有六种等可能性的结果。
然而，如果骰子不是均匀的。
设Ｘ是当掷骰子时出现的值，那么说Ｘ＝1的概率就是当大量掷骰子时“一”出现的次数占总数的比重。
总之，一个事件的概率就是“限制性的相对频率”，或说在长期中它发生的比重。
在收集调查数据时，人员的学历常常是感兴趣的项目。
令Ｘ＝１表示随机被调查者有大学或更高层次学历；令Ｘ＝０表示相反情况。
在2002年，美国25岁及以上人口中，有27%至少有大学的学历。
因而，在总人口中，Ｘ＝１的概率为0.27, 写作Ｐ（Ｘ＝１）＝0.27。
概率一定是正的并且总和是１，所以Ｐ（Ｘ＝０）＝１—Ｐ（Ｘ＝１）＝0.73。
在这个例子中随机变量是离散的，因此谈论取某个具体值的概率是有意义的。
我们可以用概率密度函数（pdf ）来总和所有概率结果。
离散型随机变量的概率密度函数是指每个可能结果的概率值。
对离散型随机变量Ｘ，概率密度f(x)是随机变量Ｘ取值x 的概率，f(x)=Ｐ（Ｘ＝x ）。
因为f(x)是概率，因此一定有０≤f(x)≤1, 如果Ｘ可以取n 个值1x ....，n x ，那它们的总和一定是1。
f(Ｘ1)+f(Ｘ2)+ +f(Ｘn)＝１.对于离散性随机变量，pdf 可能以表格、公式、或者图表的形式表现，以指明一个人是否拥有大学学历的二项分布，我们可以用像表Ｂ.1中的列表来表示。
概率同样可以等式的形式来表示，如：f(x)=x x -1)73.0()27.0（ 这样得出f(1)=111)73.0()27.0-（-1 = 0.27, f(0)=010)73.0()27.0-（ = 0.73Table B.1 Probabilities of a College DegreeCollege x f(x) DegreeNo 0 0.73Yes 1 0.27如另一个例子，令Ｘ表示一年中大学生找到工作的那个季度。
Ｘ五个取值的概率是Ｘ＝0,1,2,3,4, f(x)=0.05, 0.50, 0.10, 0.10, 0.25. 我们可以用柱状图来表示这个离散型随机变量的pdf, 这样我们可以直观地看到各种可能的结果，如表Ｂ.1概率分布函数（cdf ）是另一种表示概率的方法。
随机变量Ｘ的cdf,用Ｆ(x)表示，表示Ｘ小于或者等于某个特定的值x 。
即：Ｆ(x) = Ｐ(X ≤x)Ｘ的值，pdf, cdf, 如表Ｂ.2利用pdf 我们可以计算一个学生工作超过两个季度的概率，Ｐ（Ｘ＞2）=1-Ｐ（Ｘ≤2）=1- Ｆ（2）＝1-0.65＝0.35对于标准概率分布，统计学软件已经整合cdf 函数，这样计算概率时较为省力。
例如，二项随机变量Ｘ是n 次独立试验中成功概率为p 的成功次数。
给定总事件次数n 与成功概率p 的数值，二项分布概率就可以表示如下x n x p p x n x x X P --⎪⎪⎭⎫ ⎝⎛===)1()(f )( 表B-2 概率分布函数和累积分布函数⎪⎪⎭⎫ ⎝⎛x n =）！！（！x -n x n 上式的意思是“n 个联合的数字一次取x 个”，n ！读作n 的阶乘，用公式表示即n ！=n （n-1）…（2）（1）。
假设有13场比赛，LSU 老虎队比赛相互独立而且每场比赛他们获胜的概率p=0.7。
那么他们一个赛季至少赢8场的概率是多少？答案是P （X ≥8）=∑=138x x f ）（=1-p （X ≤7）=1-F （7） 我们可以用表B1强力估计这个概率，但是这太单调。
用Eviews 命令@cbinom 求二项随机分布的累积分布函数，将会非常容易。
1-@cbinom （7，13,0.7）=0.8346别的一些软件也有相似的强有力的功能。
连续随机分布可以取任意一个值，并且可以取无数的数值。
结果任何一个特定值的概率都是0.对于连续随机变量，我们讨论一个某一特定区间的结果。
图B.2描述了连续随机分布X 的概率分布函数f （x ）从0取到无穷大。
曲线下边的区域达标X 落在一个区间时的概率。
对于这个分布，P （X ≤20）=0.294以及P （X ≤40）=0.649.然后我们可以估算p （20≤X ≤40）=0.355这些区域是如何获得的？积分给出了曲线下面的区域的表示方法，因此P （20≤X ≤40）=dx x f 4020⎰）（=0.355分布函数是P （X ≤x ）=dt t f x -）（⎰∞=F （x ）图B.2 一个连续型随机变量的概率密度函数F(x)是X 的累积分布函数。
概率计算结果是P （20≤X ≤40）＝ F(40)－F(20) ＝ 0.649－0.294＝0.355我们不再这本书中计算积分。
我们将用电脑和简单的软件命令来计算累积分布函数值。
B.3 联合，边缘和条件概率分布处理超过一个随机变量需要一个联合概率密度函数。
一个联合概率密度函数描述了变量取值的组合的概率值。
在2002年的美国，有185183000人至少25岁。
假定我们对从这些人中随机选择上过四年大学和在2002年已经有收入的人的概率有兴趣。
定义两个随机变量：X,描述一个人的所获学历，和Y,他们在2002年是否有收入。
1 高中文凭或更低X ＝ 2 一些专科学校3 大学学位4 更高的学位表 B.3 联合概率函数 f （x,y ）0 如果在2002年没有收入Y ＝1 如果在2002年有正向的收入随机选择有这些特征的某人的概率已经由X 和Y 的联合概率密度函数给出了，记作f(x,y),它们由表B.3给出。
随机选择的某个人，他有4年大学学历和在2002年有收入的概率是0.14，即P(X ＝3，Y ＝1)＝f （3,1）＝0.14 和一元随机变量的概率密度函数一样，联合概率的总和是1. ∑∑x y f （x,y ）＝1.B.3.1 边际分布给定一个联合概率密度函数，我们可以获得各个随机变量的概率分布，也被称为边际分布。
如果X 和Y 是两个离散随机变量，∑=yX y x f x ),()(f对任意的X （B.2） ∑=x),()(f y x f y Y 对任意的Y注意到在（B.2）的和不含另一个随机变量—我们从联合概率密度函数里消除的那个。
这种运算有时叫做在联合概率表里加除不需要的变量。
例如，运用表B.3，(y)f Y ＝∑=41),(x y x f y ＝0,1(0)f Y ＝0.19＋0.06＋0.04＋0.02＝0.31联合和边际分布被记述就像在表B.4.如果随机变量是连续的，（B.2）的概念也生效，但是积分号代替了求和符号。
B.3.2 条件概率表 B.4 X 和Y 的边缘分布随机选择一个人，考虑到他有一个四年的本科学历，他有收入的概率是多少呢？这个问题就是求已知X=3时，Y=1的条件概率是多少。