|
|
Absolute deviation, 绝对离差) ^/ D2 O2 A/ k _6 \
Absolute number, 绝对数
( K7 n; W$ a5 qAbsolute residuals, 绝对残差
- K" q. {! Q7 u" VAcceleration array, 加速度立体阵6 ^3 Y- b+ c) U' F# l4 w+ k
Acceleration in an arbitrary direction, 任意方向上的加速度6 {* H+ f3 R Z+ H
Acceleration normal, 法向加速度
- G' E# f. X- \# b5 e) F: _Acceleration space dimension, 加速度空间的维数+ `- l5 N; E+ m" Y
Acceleration tangential, 切向加速度8 Q7 h6 I5 i6 m3 a
Acceleration vector, 加速度向量6 \1 a+ @/ @1 s
Acceptable hypothesis, 可接受假设
9 r5 \) x: I5 \0 A$ rAccumulation, 累积
4 B% @/ ] T) m! c% k4 oAccuracy, 准确度6 q2 }0 |; A/ q$ U4 j
Actual frequency, 实际频数, k3 l6 |* [: @* q, z# @7 }
Adaptive estimator, 自适应估计量
& ^# r/ [/ m5 WAddition, 相加
- ^; N. l$ f+ z2 ~% ~' n9 L2 V6 n0 @6 lAddition theorem, 加法定理
: O6 U. Q6 S( d* [Additivity, 可加性
" [- a/ ~& I6 z, oAdjusted rate, 调整率+ [; s1 p9 q' C" B
Adjusted value, 校正值! I2 h7 M" j- e
Admissible error, 容许误差% P/ j y6 G# q# w/ w9 S
Aggregation, 聚集性
5 ?* }, e, M; R' kAlternative hypothesis, 备择假设
. T' |# X" V- U$ u' d8 NAmong groups, 组间
1 c' r9 n0 k R; ]Amounts, 总量
4 p7 Z9 T9 [9 U$ t/ R$ K' F, R) UAnalysis of correlation, 相关分析3 [+ v0 Z+ J0 f L
Analysis of covariance, 协方差分析* a$ Y5 K6 d. r* G
Analysis of regression, 回归分析
8 y* M/ O r9 P+ O4 RAnalysis of time series, 时间序列分析' b- W8 {9 Y+ f. ~+ s9 K* s
Analysis of variance, 方差分析
8 B0 T! I% s! \1 _2 g( L: @* CAngular transformation, 角转换, f8 J. @0 }9 k) Z0 j1 Y
ANOVA （analysis of variance）, 方差分析7 T4 p7 J2 A# N8 U0 X( O; W
ANOVA Models, 方差分析模型$ d% N# v' G4 t. o5 _3 ` s# p! @
Arcing, 弧/弧旋
$ e* Y; u; R4 a4 Y4 m% FArcsine transformation, 反正弦变换
8 r& O3 Z! e q! `/ cArea under the curve, 曲线面积
6 X! B! \/ k+ F. `: QAREG , 评估从一个时间点到下一个时间点回归相关时的误差 ~2 Z" A7 b6 I0 R
ARIMA, 季节和非季节性单变量模型的极大似然估计
: W/ d% |$ L: J0 eArithmetic grid paper, 算术格纸5 h" R" g9 B4 Z& Z
Arithmetic mean, 算术平均数
! D/ S! ?/ R4 w4 ZArrhenius relation, 艾恩尼斯关系
& T% ]& ?* S) [- ]+ |& y# e1 NAssessing fit, 拟合的评估- j- S! x! t# p- p: u
Associative laws, 结合律" u5 l9 \' n. c# N( J) J
Asymmetric distribution, 非对称分布
9 T. Z# e9 a1 _# v$ bAsymptotic bias, 渐近偏倚; e! e2 E7 p5 E+ \# Q8 h: ^0 I
Asymptotic efficiency, 渐近效率8 }; j$ F! L4 H% k/ h
Asymptotic variance, 渐近方差
: h: @0 ]/ d* d4 k4 D& f* AAttributable risk, 归因危险度% g% g; _. j& {2 H. G' m, w k
Attribute data, 属性资料
. `; U& U; K4 n0 M1 l: }- CAttribution, 属性
& |! \- Z' I- aAutocorrelation, 自相关. G' k7 ]- v* B, i5 p) Q
Autocorrelation of residuals, 残差的自相关
1 p4 h! W# s% J7 u6 D+ eAverage, 平均数
0 w& W" i4 m1 o- w7 Z1 L0 c: ?Average confidence interval length, 平均置信区间长度
' k0 ]: f. W+ K! V1 vAverage growth rate, 平均增长率
& _+ Y% R. r. JBar chart, 条形图
8 ~ ]6 |6 S% _; S$ W1 e" ~Bar graph, 条形图
& z2 r; U. x0 [% K) W* O0 wBase period, 基期* z/ e9 [3 i) c8 B
Bayes' theorem , Bayes定理
& g0 ^* T& a5 B( H( C1 p+ WBell-shaped curve, 钟形曲线2 J4 ^0 f4 X& \* L
Bernoulli distribution, 伯努力分布9 a# b+ M0 Q- C
Best-trim estimator, 最好切尾估计量; k/ G0 l+ d {2 ~8 U- Y
Bias, 偏性) \" \) g) U. r+ D* G! D8 x
Binary logistic regression, 二元逻辑斯蒂回归
! b3 [$ a0 J' m: vBinomial distribution, 二项分布0 c1 ?7 e+ c# m5 Q/ e1 n4 @
Bisquare, 双平方
^# c4 [1 H/ a R4 q" c6 DBivariate Correlate, 二变量相关
1 Q5 S7 l; @$ a/ B. c8 z, R8 \Bivariate normal distribution, 双变量正态分布- k3 p t* \7 e+ Q
Bivariate normal population, 双变量正态总体) V( b, |5 h8 y3 ?* ^
Biweight interval, 双权区间
2 k4 L! t9 E+ |$ g: a$ Z/ UBiweight M-estimator, 双权M估计量
6 {& C- ^7 q3 ] G9 c/ LBlock, 区组/配伍组4 z( a; L+ n2 v- ?* @5 t9 H# g) a, h
BMDP(Biomedical computer programs), BMDP统计软件包
0 P) x7 l5 f/ A2 P( ?" sBoxplots, 箱线图/箱尾图
( e- `! U/ O3 _7 `, f( j+ {Breakdown bound, 崩溃界/崩溃点
3 s- ?- m& Z; ]% b# V( ^3 KCanonical correlation, 典型相关7 A" _/ P0 s z! a" i9 d
Caption, 纵标目0 ?* t1 ?9 i5 e# m
Case-control study, 病例对照研究. ?5 j: F V3 O! |# e6 c
Categorical variable, 分类变量
, R0 p0 g/ _9 H7 w7 l( i" v% _Catenary, 悬链线
1 ]& _, x h' [, } T3 P qCauchy distribution, 柯西分布7 P* ]5 @; n6 y0 x1 Y7 t6 m
Cause-and-effect relationship, 因果关系
% K( z, o+ ^ }2 Q# ?# sCell, 单元
! E( {0 q) v4 U7 r/ qCensoring, 终检
( l' L. v) K K( D! s# FCenter of symmetry, 对称中心8 n( R( \* }" n% s( {- Y2 X: w% s
Centering and scaling, 中心化和定标
4 m9 s7 w2 R# @0 ~+ N' w' m1 v [Central tendency, 集中趋势! B' z8 ?" q. a/ M
Central value, 中心值6 f! s. z- E6 W# V: u3 E Y8 k
CHAID -χ2 Automatic Interaction Detector, 卡方自动交互检测
, z5 s# u5 B" { {9 m$ fChance, 机遇( K3 }5 f$ R" _* \- j) D' X, }
Chance error, 随机误差
. P2 ?* k' B6 M7 e; X$ q! x5 z |Chance variable, 随机变量$ k0 R; I+ g# Q, t# l) d
Characteristic equation, 特征方程1 A( Q4 l+ r& C0 s
Characteristic root, 特征根
' B% ^0 P4 K/ ?6 h: x& GCharacteristic vector, 特征向量) F/ Q; {8 m# m+ n4 A9 W @; |! C
Chebshev criterion of fit, 拟合的切比雪夫准则) U+ H. C5 o6 W- r0 q
Chernoff faces, 切尔诺夫脸谱图
" F$ H. X% Q: p8 z% x( S7 dChi-square test, 卡方检验/χ2检验: |5 O6 i1 P. ~6 b! N
Choleskey decomposition, 乔洛斯基分解# B* {' B! N% c7 y3 i- {
Circle chart, 圆图
2 H1 R# ~" ~5 X+ j+ O2 j( `5 pClass interval, 组距
2 B: }7 R. k Y) ~2 X. @Class mid-value, 组中值$ M3 Z, q$ C3 N3 {9 D
Class upper limit, 组上限
3 r4 Q% ^) M8 l6 {) M/ @. u6 a4 m! cClassified variable, 分类变量5 r6 _0 Z% E- L9 D+ Z1 W
Cluster analysis, 聚类分析
0 Y/ N1 v6 v! F, R5 E* ?( ICluster sampling, 整群抽样
6 e- d( u/ D; ?; W( ]Code, 代码
: B# W' E K* Q; C: [Coded data, 编码数据
5 Q+ G4 o& g% O. VCoding, 编码
4 J4 V2 J% j ]3 e! U+ pCoefficient of contingency, 列联系数! {4 ~" o3 L/ i7 g6 _
Coefficient of determination, 决定系数
+ `$ i6 Q& [; I; ZCoefficient of multiple correlation, 多重相关系数
5 q4 M, W1 I$ d3 L+ F, J( ECoefficient of partial correlation, 偏相关系数
, O( }+ M" h8 N9 N6 y' x# b! y$ qCoefficient of production-moment correlation, 积差相关系数" k! u& Y; p' G- r9 A+ r q
Coefficient of rank correlation, 等级相关系数
; f" `0 a4 t0 ? ]; {; K& W: ICoefficient of regression, 回归系数: ^6 F+ G6 D& U, e- l
Coefficient of skewness, 偏度系数
1 p0 ~" b& U4 m, uCoefficient of variation, 变异系数5 c9 w, [* Z: k, x
Cohort study, 队列研究6 m( l/ i& m! C9 ~! W4 E
Column, 列
" s( {+ f- `3 N" ]Column effect, 列效应
5 c1 e0 m- V, E/ b( X5 N0 I7 JColumn factor, 列因素7 p1 U) }! f' M- b0 w
Combination pool, 合并 Y) ]7 _4 O o9 A0 a) _. j
Combinative table, 组合表
1 q2 ~. j% L& G9 p# ACommon factor, 共性因子, N5 O7 F5 Y9 h3 O
Common regression coefficient, 公共回归系数
; q% _- Z( v. T5 k. NCommon value, 共同值
- L) ?+ V; W7 w2 k9 W4 m! G, DCommon variance, 公共方差
) I5 k! M; c, k' b, m& o! `Common variation, 公共变异
* v1 q; J C# V" V ^8 }Communality variance, 共性方差, \: G s0 _ V; b8 P
Comparability, 可比性
' g& m4 ^% R, X5 r# \0 KComparison of bathes, 批比较
# H- L9 K4 j3 o# @; o2 YComparison value, 比较值: U1 K, A8 O( h
Compartment model, 分部模型
. b/ Y; [0 T* I3 U8 z5 i7 P( ]Compassion, 伸缩
3 C) n; z( B: Q% `Complement of an event, 补事件
3 e4 Q. d v% ?+ E+ }. jComplete association, 完全正相关* z8 J* B4 F% s6 b! e
Complete dissociation, 完全不相关
5 l) }2 F% Y* C( L2 a8 tComplete statistics, 完备统计量
# I" K2 y" n5 b/ D3 j' j- V# f SCompletely randomized design, 完全随机化设计9 f! ~* e z5 G- J
Composite event, 联合事件
. f4 X3 g1 \" ZComposite events, 复合事件
0 l8 E9 M6 p3 fConcavity, 凹性
4 d- `6 J5 H3 C9 p8 y& }Conditional expectation, 条件期望
8 w2 l! {% I' s, e2 \9 p2 i& jConditional likelihood, 条件似然% C) \& N7 |: p7 ]5 g2 o
Conditional probability, 条件概率3 F, c5 X1 b9 A/ F; {9 b& }
Conditionally linear, 依条件线性6 H- r; G, [1 y. o' e: W
Confidence interval, 置信区间! L( I! J' g. `( s6 r0 Z& X
Confidence limit, 置信限
1 o4 X* h6 m( M! {Confidence lower limit, 置信下限
2 B7 t( {1 U; r, L: A, sConfidence upper limit, 置信上限: C! G+ V$ |, R5 C8 e: w3 G* z0 k
Confirmatory Factor Analysis , 验证性因子分析
4 N6 p/ i D9 K, A9 D+ \$ OConfirmatory research, 证实性实验研究
# [; @; t/ C$ z: E3 wConfounding factor, 混杂因素
3 J0 M2 w. s# s6 p2 JConjoint, 联合分析
5 U* K+ D+ g) u% ~( {- WConsistency, 相合性
& l4 u- G( M0 R# j Z/ N6 qConsistency check, 一致性检验5 d4 f, p, k m. d# }
Consistent asymptotically normal estimate, 相合渐近正态估计6 Z6 \3 f6 i9 v# O( t$ {0 A. U
Consistent estimate, 相合估计
, ~! H* B) [2 W0 ^Constrained nonlinear regression, 受约束非线性回归& P, q0 b _9 z4 `0 P
Constraint, 约束
) v3 P4 T4 H R2 [Contaminated distribution, 污染分布
- A& T: k& T2 k; \ B0 OContaminated Gausssian, 污染高斯分布
" \9 r5 v+ S+ C0 F, C0 ]Contaminated normal distribution, 污染正态分布, j" t/ |, z% [6 ~
Contamination, 污染
3 ^( _- M8 q5 EContamination model, 污染模型, |3 c6 B8 [" E- @
Contingency table, 列联表
. `3 Q4 \& O3 Z- bContour, 边界线
. V. k$ H3 z! V# J1 Q* {Contribution rate, 贡献率
* s. I1 t. Q4 V. EControl, 对照
; @( v) b) D6 M, H. t$ O' {2 PControlled experiments, 对照实验
a1 S2 r4 O% C# _& N4 u6 RConventional depth, 常规深度! `4 y/ k( t0 v% h- z
Convolution, 卷积7 G5 Y! k; i. |% q/ g# d" \! M
Corrected factor, 校正因子
4 P2 H9 L. C* n) j, UCorrected mean, 校正均值! _* O/ w$ O) n$ @
Correction coefficient, 校正系数
( W- o7 ^( `2 @$ t5 K& rCorrectness, 正确性
: y+ x& K8 G. t RCorrelation coefficient, 相关系数
# K9 ~. W4 n9 `2 N6 q) Y. Z2 kCorrelation index, 相关指数
9 t0 k4 t& W9 y9 YCorrespondence, 对应
' F2 `( H* J' |% \& @6 L( JCounting, 计数
9 l2 U+ d& f) Q. w8 e- VCounts, 计数/频数* Y2 x7 L5 t0 c& r$ A9 r6 k9 n: [
Covariance, 协方差
9 ]6 u0 M* J% r6 vCovariant, 共变
9 q/ ~6 V1 z* ]$ C9 ^; t6 J' DCox Regression, Cox回归5 S% v; d$ x2 w, M, L$ r
Criteria for fitting, 拟合准则' Y [2 s7 A6 Z& @! ]
Criteria of least squares, 最小二乘准则
, }. B. |% g0 P: kCritical ratio, 临界比
, @6 @- e& t$ b7 `5 T {Critical region, 拒绝域! ~+ q; w, H. S2 g- k/ \
Critical value, 临界值
( J4 k; \2 C) }Cross-over design, 交叉设计9 k: _0 x3 x7 \" F4 m% e) `
Cross-section analysis, 横断面分析" ]: |& ^0 Q$ |3 C
Cross-section survey, 横断面调查
0 `: d3 T7 Z- L# X' f4 fCrosstabs , 交叉表
! A! i; C5 n `! F0 Y S( t1 m0 rCross-tabulation table, 复合表8 o- k) P; _' [7 m8 ~7 z- K- c
Cube root, 立方根
+ L j y \7 ?0 L# gCumulative distribution function, 分布函数
" D6 q+ ]( v5 j- dCumulative probability, 累计概率0 y {$ X( Y9 H2 C( E( S
Curvature, 曲率/弯曲3 h% j3 |! j7 Z& ^% Q P" |8 n, j
Curvature, 曲率
/ `* o8 y8 M$ P3 c$ N. m4 r* yCurve fit , 曲线拟和 9 V7 p1 a* s1 _
Curve fitting, 曲线拟合) Y; R7 Y" G7 L4 _% u
Curvilinear regression, 曲线回归
% c- S: c& M! k& D& {% m, W& @/ fCurvilinear relation, 曲线关系
; q# ^6 G5 s$ T8 C5 S1 G5 e& ECut-and-try method, 尝试法
* I3 B/ }2 ^; O0 m7 PCycle, 周期
{7 x* d7 W) dCyclist, 周期性: @* D$ ^3 Q# S
D test, D检验
) ]" ~/ h" p4 D" F- J6 FData acquisition, 资料收集
. A6 p" F* Q5 W( RData bank, 数据库
$ P/ t* T/ d# O, R2 m3 }Data capacity, 数据容量0 W G+ I& Z/ {! k8 G$ u: A6 b8 L
Data deficiencies, 数据缺乏. f. ]1 j, [7 g u1 i3 P$ O
Data handling, 数据处理
* O& o9 ~7 r: l; T8 X' mData manipulation, 数据处理3 T m' v/ c4 g7 l* h9 ^5 B0 Q- h
Data processing, 数据处理
. B# r& H! s4 \1 |6 ^, B- F+ D8 |Data reduction, 数据缩减+ m$ V+ ~6 o0 i) v
Data set, 数据集- w. `+ F% b: X5 z
Data sources, 数据来源' F% l/ B0 n; x( s( K$ N
Data transformation, 数据变换: r' F: k' D0 v* q
Data validity, 数据有效性' `% e3 W) X: p1 v; `; p. M% P
Data-in, 数据输入
+ P" q6 V4 d# j. ^0 [- EData-out, 数据输出3 E; l0 z1 x3 [$ U
Dead time, 停滞期+ l' I8 P T; v' U
Degree of freedom, 自由度
; r- P1 P' E8 hDegree of precision, 精密度
( s: `8 n: H; \9 `# LDegree of reliability, 可靠性程度
( X; s M$ k% x" E' Y/ s/ u; w7 GDegression, 递减6 p1 f( e# u! e. [* o
Density function, 密度函数
" M* i" a* N/ GDensity of data points, 数据点的密度/ I+ F+ Z& _/ m8 P
Dependent variable, 应变量/依变量/因变量3 ^9 E' V9 K0 o# k
Dependent variable, 因变量
7 N& N1 ]; u: t6 P/ yDepth, 深度
# n7 _9 p7 |, A& w" |Derivative matrix, 导数矩阵6 M( W! c- s& b
Derivative-free methods, 无导数方法
7 `- G5 I% w1 E1 h) h7 r% DDesign, 设计9 v! H5 ^8 \9 B0 {
Determinacy, 确定性
: u; q/ [( B/ o& F2 Z: O2 JDeterminant, 行列式
0 f N( [' I; y8 q7 ADeterminant, 决定因素
' c$ i# d: T( W' P; [" j( H+ n* KDeviation, 离差' y$ T# X* a. n, D
Deviation from average, 离均差; ?2 P4 } M% q, Q! D
Diagnostic plot, 诊断图' l8 K1 C. L [* q
Dichotomous variable, 二分变量
+ ~0 H4 p( p# s& SDifferential equation, 微分方程
! t& J/ H" P8 w" z6 yDirect standardization, 直接标准化法
! Q% M8 d9 ~: PDiscrete variable, 离散型变量* R0 t9 T9 C2 H1 v. G
DISCRIMINANT, 判断
2 ~8 _/ l0 A$ i; w$ _9 q' bDiscriminant analysis, 判别分析7 i% U. J; ^9 k6 v' x* w D
Discriminant coefficient, 判别系数% V6 H0 O9 e/ c& C* N) O' Y
Discriminant function, 判别值; k/ V' u# n j0 c. X: k. h
Dispersion, 散布/分散度% \2 I; K! r) M" [# I- p1 f/ ~( q
Disproportional, 不成比例的
1 R. O; r9 W G O6 ^* ^Disproportionate sub-class numbers, 不成比例次级组含量% g! ]3 j5 h9 [4 T$ f9 Q p
Distribution free, 分布无关性/免分布. J& B5 R, }9 b8 l* F
Distribution shape, 分布形状
$ d# F. i! G' F( tDistribution-free method, 任意分布法; S. j% n# c3 d% u* g2 r
Distributive laws, 分配律
: s/ A$ y5 F# _' J, T! jDisturbance, 随机扰动项
7 a! c( {- Q( rDose response curve, 剂量反应曲线
% o) a% K; c+ S/ K/ I2 p% eDouble blind method, 双盲法# F. y/ O* W/ s' j: e9 b
Double blind trial, 双盲试验$ i5 \2 U- i' |2 V+ W
Double exponential distribution, 双指数分布
" {" t+ o& G' J. H; X! N" ?Double logarithmic, 双对数
" K; {2 V; O/ pDownward rank, 降秩4 h& ]- w. l& U
Dual-space plot, 对偶空间图# C6 f, Z, Y! u/ w
DUD, 无导数方法
7 S2 V- `4 T6 ZDuncan's new multiple range method, 新复极差法/Duncan新法
* U3 O( q; t" \9 Q% m+ lEffect, 实验效应" X$ l" ~+ Y% y
Eigenvalue, 特征值* L- d3 F2 i1 d% ]7 ]7 I, y
Eigenvector, 特征向量
n% g7 d' g* k+ @" e3 ]! PEllipse, 椭圆7 U+ u) Z/ y2 f1 k
Empirical distribution, 经验分布; T5 t" V: f& q2 _3 G
Empirical probability, 经验概率单位2 y/ ` k' F J2 D7 s/ X' ?
Enumeration data, 计数资料
- {4 W" `3 J/ M; cEqual sun-class number, 相等次级组含量
4 J$ B' }$ F8 D4 \Equally likely, 等可能
$ X+ m W6 H( B- r$ O& }. N' `, tEquivariance, 同变性
7 V: M0 e# f- |Error, 误差/错误. U/ c) M0 N* l# y
Error of estimate, 估计误差1 S. S# }* Y; {5 E$ |
Error type I, 第一类错误, ]7 X6 B* ]. a, z: i G$ O
Error type II, 第二类错误- F! \* v2 Q+ E/ [1 F8 C
Estimand, 被估量
7 _8 i& c( }* b U- `Estimated error mean squares, 估计误差均方7 l4 W6 i9 o$ h3 r! `/ D2 a
Estimated error sum of squares, 估计误差平方和
$ e& C" T' R# G% ?# l' I* qEuclidean distance, 欧式距离
( Q6 ~3 n8 Z" p4 w3 L* [Event, 事件8 z0 H" Z) B" {
Event, 事件( z! D' E% @1 {% @) e
Exceptional data point, 异常数据点
: N! k. U1 C/ Y: V# T7 U& ]Expectation plane, 期望平面! F5 s, h! f' B) e& ~ g
Expectation surface, 期望曲面
2 U: V% X& M7 a5 U# dExpected values, 期望值7 H( y! L/ r/ R/ u
Experiment, 实验+ Y7 M. ^- B3 p4 E
Experimental sampling, 试验抽样( ]' q6 e% Y3 n" R+ ]
Experimental unit, 试验单位4 h+ K# X3 R2 y% t" s
Explanatory variable, 说明变量
; y7 N) c/ c6 q( n# d+ rExploratory data analysis, 探索性数据分析0 W" c. H6 y1 x& \
Explore Summarize, 探索-摘要
' ]3 V; K( Z/ h# o. NExponential curve, 指数曲线
2 e: Y! [4 f0 Z3 O- xExponential growth, 指数式增长
; P4 E, I+ ^' \0 Q9 e2 D" p3 d5 @EXSMOOTH, 指数平滑方法
% K; V2 {/ ^& F6 x4 Z0 iExtended fit, 扩充拟合7 \+ e; U8 E) x' u0 ?7 a: o, X
Extra parameter, 附加参数
2 M' _& l: c: D6 jExtrapolation, 外推法7 u* y3 F% `+ u' @7 l6 S
Extreme observation, 末端观测值
F! P% {3 A, O m6 v% B3 ?! @Extremes, 极端值/极值0 C+ K2 Z1 e2 t8 [- P4 U5 z
F distribution, F分布. A8 f3 j6 L: E; V) e& V/ T' U
F test, F检验4 y: y0 c0 X+ V- o
Factor, 因素/因子8 \0 a6 x2 k* J b- c! e
Factor analysis, 因子分析
; X: [' c! N; L+ f/ N+ `Factor Analysis, 因子分析
1 v& h1 L# b$ T/ G, dFactor score, 因子得分 ! H( w& k0 L" k( _: {
Factorial, 阶乘
& }! z4 o( z( O* KFactorial design, 析因试验设计7 G& D0 ?7 k3 _0 ]8 H: i
False negative, 假阴性5 u1 Y7 w8 A2 j: w
False negative error, 假阴性错误
" t' L. R' x* Q0 ^; u1 AFamily of distributions, 分布族% A9 V" P& `0 y" e# V" a
Family of estimators, 估计量族
4 d' g/ H" L* L' D2 cFanning, 扇面
, k4 D2 s" U M7 OFatality rate, 病死率
$ G, z7 X; N1 hField investigation, 现场调查
/ D1 a' h) v/ ^& e7 i# @Field survey, 现场调查9 M) [ f3 [+ c
Finite population, 有限总体
/ _7 K8 U% x( E6 |% c) vFinite-sample, 有限样本: s2 B' }( ]1 M) B% Y
First derivative, 一阶导数
+ j+ w9 l* Y. ^: I& l6 z' x2 Y6 }& V# xFirst principal component, 第一主成分+ s8 i ]7 M" k, D5 @
First quartile, 第一四分位数
# Y" _2 s4 K- ?: S9 \4 d$ d& E) uFisher information, 费雪信息量+ ~* \. |! S. i+ U1 D3 |) \/ A0 ]% k; B
Fitted value, 拟合值' c7 p6 T8 \+ {; i6 p. r
Fitting a curve, 曲线拟合
$ t8 e9 \" m# [- [Fixed base, 定基( g9 j6 N9 M: I% V/ \+ m
Fluctuation, 随机起伏; p( P& {% z' V0 B- s% h6 A
Forecast, 预测) ?5 O3 Y7 u# N) m: i, ?- {6 ?
Four fold table, 四格表
, i! r2 L; z+ }3 pFourth, 四分点
& S+ k/ R/ Q: t8 SFraction blow, 左侧比率
: W+ Y3 V5 ]$ c! IFractional error, 相对误差
* C4 Y0 P3 u! x0 |, `Frequency, 频率& v$ @ c- B( X& i9 o0 P0 g+ Z
Frequency polygon, 频数多边图
+ L; r6 x6 ~% E, _& QFrontier point, 界限点
1 L: ~7 e' F- oFunction relationship, 泛函关系
/ N$ h1 y% ^ T6 F( u @4 p& CGamma distribution, 伽玛分布
$ w+ `% i9 K& c; Z8 A$ L J2 kGauss increment, 高斯增量* C l# N% ?( P" m
Gaussian distribution, 高斯分布/正态分布
4 o0 T& [5 a% OGauss-Newton increment, 高斯-牛顿增量
: C5 C2 m( k2 T' K& ~. j! o- HGeneral census, 全面普查
' c) _7 `$ E" Y7 lGENLOG (Generalized liner models), 广义线性模型
6 ?* K" c1 F9 ^7 w2 gGeometric mean, 几何平均数
" l: n% N- y% }7 ~Gini's mean difference, 基尼均差
# L: i* |# t* ]4 k% S& F2 v4 SGLM (General liner models), 一般线性模型 7 y+ Y# i; g4 ]+ T
Goodness of fit, 拟和优度/配合度 | Q) n+ A, Z* h. G1 w, p9 e, R
Gradient of determinant, 行列式的梯度) e$ ]0 x+ o" ]. F I; r9 [
Graeco-Latin square, 希腊拉丁方
6 M( m% `5 ]- IGrand mean, 总均值5 a# I9 X* H5 y4 `0 `2 _3 S
Gross errors, 重大错误
2 Z5 {$ I, {- m. |" M3 MGross-error sensitivity, 大错敏感度
8 G& D. ~' U! z! }; K4 f! fGroup averages, 分组平均, G% w$ z7 V1 P5 X6 }6 M
Grouped data, 分组资料
4 Z8 e- W1 @0 e6 tGuessed mean, 假定平均数
0 K" ^( I% S& NHalf-life, 半衰期0 O; |4 A; U2 {; ~. Y6 c: y5 f# w
Hampel M-estimators, 汉佩尔M估计量
9 U$ ~6 o" k0 H3 W6 Z1 L+ jHappenstance, 偶然事件1 Z' G9 Q7 S0 j2 l6 f# m. ~6 i* H
Harmonic mean, 调和均数( F; T7 i& a7 S& K' d
Hazard function, 风险均数
) m+ X4 H2 F1 v O3 d$ y& u7 xHazard rate, 风险率
, O9 ~+ h* \3 {0 V& iHeading, 标目
0 [, P; |1 k# `: A2 gHeavy-tailed distribution, 重尾分布
" n6 |/ \, J$ B( bHessian array, 海森立体阵4 F: S" V% q' i
Heterogeneity, 不同质
' {5 G' K& p& j: ?( o/ tHeterogeneity of variance, 方差不齐
7 V! y) @, q( X) FHierarchical classification, 组内分组+ T# R l# y/ f7 B% G1 }3 x
Hierarchical clustering method, 系统聚类法
, s- v; r' g$ t! dHigh-leverage point, 高杠杆率点. D" X7 i) w8 S
HILOGLINEAR, 多维列联表的层次对数线性模型: w/ \1 i$ }5 w3 Q
Hinge, 折叶点
R8 |3 v2 X# O/ YHistogram, 直方图! A! \/ f( M+ s
Historical cohort study, 历史性队列研究
. K$ F5 J8 D, y- a/ O* R* ?0 KHoles, 空洞
/ o" ]9 a" e* O K0 RHOMALS, 多重响应分析$ {/ v3 L7 \2 s- g) P
Homogeneity of variance, 方差齐性$ E5 P7 u) c: { K
Homogeneity test, 齐性检验" {/ J/ g- Q* t6 R7 c8 D% r
Huber M-estimators, 休伯M估计量
- o, M. A) n k- ZHyperbola, 双曲线
: F# X! y; l* a8 H. [Hypothesis testing, 假设检验
" N' H6 A @* jHypothetical universe, 假设总体
0 _( M# J- X+ ~4 J& S0 X% T5 T2 m5 f+ VImpossible event, 不可能事件: p0 ` O ]" n5 C
Independence, 独立性$ P$ q, B& }* _2 p0 V7 C
Independent variable, 自变量
( I2 t. }( D1 |, i/ sIndex, 指标/指数* G4 d0 c5 Q" |
Indirect standardization, 间接标准化法 [& @' M! L& A( {* l" x
Individual, 个体
( K3 K1 L, T4 k5 B( ?: nInference band, 推断带: @! P: }8 I ~* X0 U5 X
Infinite population, 无限总体
; ^ a; S; p: V; ?8 N+ E# P aInfinitely great, 无穷大. g8 E' l: m& J/ L
Infinitely small, 无穷小
) P. |% {7 k+ O6 BInfluence curve, 影响曲线
( {, d: [- |# Q; R2 ~Information capacity, 信息容量6 D- U! Z9 u. r2 J7 g* m
Initial condition, 初始条件* w! U6 T3 q0 F! C7 ?4 C9 y
Initial estimate, 初始估计值
, B6 X% e% ]. f+ H1 o" Y9 yInitial level, 最初水平
( b) x4 a3 K; G( s1 X2 `( zInteraction, 交互作用: G8 \7 {7 n3 a" j4 \# }. l/ `* I
Interaction terms, 交互作用项+ q' o) H4 G8 ?( u' V0 Q% q
Intercept, 截距
3 f& K$ j& |/ l5 Q: a. WInterpolation, 内插法& l% M/ r3 I$ C2 a1 Z7 g
Interquartile range, 四分位距( \ l+ \6 E5 i% b0 u* x% c( Q4 j
Interval estimation, 区间估计$ _, {$ v$ y: n) K
Intervals of equal probability, 等概率区间
/ ?3 ]6 A2 h5 jIntrinsic curvature, 固有曲率
, k, v% P& g2 Z( D+ G+ |+ I: pInvariance, 不变性
/ h! T0 Z7 Y! _/ OInverse matrix, 逆矩阵( |- G; K5 q3 f8 g' O
Inverse probability, 逆概率0 T4 E2 z% e& ?. }2 r% p4 Q; t1 _
Inverse sine transformation, 反正弦变换" d# @8 X s( S
Iteration, 迭代 ( K9 U9 C- _0 u- O$ W
Jacobian determinant, 雅可比行列式) k+ F( [! G. s( g
Joint distribution function, 分布函数$ x" p( p( `6 g- k
Joint probability, 联合概率
' e+ j* B7 z W! e/ u0 S4 U8 sJoint probability distribution, 联合概率分布9 c' t% G5 ~; n" j
K means method, 逐步聚类法
$ ~0 i% D# H- G/ G% m4 ]2 ~Kaplan-Meier, 评估事件的时间长度 5 E/ U3 Q# a5 l; I0 W( t0 `: \
Kaplan-Merier chart, Kaplan-Merier图
. n. N3 Z* `% i( {) t7 ?5 lKendall's rank correlation, Kendall等级相关
5 ^$ B4 Q- G: E8 N* x1 MKinetic, 动力学6 p" c* Z0 x' k1 O
Kolmogorov-Smirnove test, 柯尔莫哥洛夫-斯米尔诺夫检验) J- O2 u+ x7 n5 }) _$ |- w
Kruskal and Wallis test, Kruskal及Wallis检验/多样本的秩和检验/H检验/ S. s) D6 p! Y7 z4 O- B5 E8 Q" f
Kurtosis, 峰度! ?) k& i( o. Q9 N+ I
Lack of fit, 失拟
6 e) w8 L8 }; d7 Q$ VLadder of powers, 幂阶梯9 T0 X% x- p' U; C
Lag, 滞后
' D1 k2 g5 B$ r5 p! u7 p KLarge sample, 大样本
1 W; L9 l3 x: F7 |1 N0 DLarge sample test, 大样本检验
1 h& B- J1 ]8 i) lLatin square, 拉丁方5 w! n# v f- M( T+ c2 J6 z) w0 Y$ [
Latin square design, 拉丁方设计
6 G$ ~$ H. E8 NLeakage, 泄漏3 O! Y$ T. F; `! t* E+ |' }$ m1 ^" w
Least favorable configuration, 最不利构形- F3 u m% F, u' ?
Least favorable distribution, 最不利分布) i& T6 m, C7 @3 O! N
Least significant difference, 最小显著差法
8 b9 @% ?" ~4 A$ m! J- M9 jLeast square method, 最小二乘法
+ |/ z5 R! k* dLeast-absolute-residuals estimates, 最小绝对残差估计
2 u ^& O1 j3 [. aLeast-absolute-residuals fit, 最小绝对残差拟合
' `9 F3 t% I# z% x F% M& MLeast-absolute-residuals line, 最小绝对残差线$ W/ E$ r2 p/ f( E
Legend, 图例6 k: U0 r+ y2 W; [
L-estimator, L估计量. w: }& V3 i4 B+ m8 ^3 T- @
L-estimator of location, 位置L估计量
& D, u* e) | A+ }2 NL-estimator of scale, 尺度L估计量
) j+ B/ f/ p& f" l& n* ~Level, 水平& G+ F8 B9 Q: {0 q% x
Life expectance, 预期期望寿命8 s! O. g1 I- q: ]
Life table, 寿命表
, Q1 t& t* C0 G3 ?9 H' Z+ WLife table method, 生命表法2 F$ p! f# y- d) O% \$ E5 T
Light-tailed distribution, 轻尾分布
7 I% O% h/ e* \1 B1 ]Likelihood function, 似然函数" Y0 D1 B3 u& {/ `1 [" r
Likelihood ratio, 似然比; {8 B7 U% j) T2 `
line graph, 线图
) W# F# s1 o& T) ~) @6 { D& Z! wLinear correlation, 直线相关
- \$ F, C+ {: s8 T- u0 MLinear equation, 线性方程# J/ L* A* C7 T0 B- \6 b
Linear programming, 线性规划! ?+ _ y4 c1 d6 U. h
Linear regression, 直线回归
% [0 D# u% p2 m6 p" c, ^, Z( F9 HLinear Regression, 线性回归
/ A; O$ @6 l+ S0 W( D/ p1 I8 ^Linear trend, 线性趋势
) T+ w- p; Y5 M ]/ u8 u @Loading, 载荷
8 _) L0 L& H P% xLocation and scale equivariance, 位置尺度同变性
; F8 ?( v9 [1 }' fLocation equivariance, 位置同变性
\0 t( f) Q# V7 _) lLocation invariance, 位置不变性+ C& L \- |5 O2 v
Location scale family, 位置尺度族
* u, E& |. T' j' yLog rank test, 时序检验
6 a: ?' ?. M% w2 U# d$ V7 ~Logarithmic curve, 对数曲线 S w3 z0 \! E0 m/ g7 r8 l
Logarithmic normal distribution, 对数正态分布* N, z. \6 T5 D3 o+ `* l: A8 S. ], X2 J; J# i
Logarithmic scale, 对数尺度
8 b! F& [0 L& b) B9 A; B6 i* zLogarithmic transformation, 对数变换2 p' m* R: e& k% P
Logic check, 逻辑检查
( d7 |8 l) Y& X7 lLogistic distribution, 逻辑斯特分布
g/ ~2 m5 ~0 u2 s) x$ A0 [Logit transformation, Logit转换5 `, k" p& T* ~8 W
LOGLINEAR, 多维列联表通用模型
/ v$ ^9 Q. @- _& W% o. u# K+ }Lognormal distribution, 对数正态分布
3 W0 G* Y; c# q/ w, c O7 SLost function, 损失函数5 ^5 Y; a. {: O" X! W
Low correlation, 低度相关
# E. M( @8 y' i6 SLower limit, 下限. _# L$ d5 \/ L. i
Lowest-attained variance, 最小可达方差
3 x" ?* f% v" m) W2 J7 {6 ILSD, 最小显著差法的简称
( m, h9 B, y3 }' Q# l& U8 X) \Lurking variable, 潜在变量
8 B" w r3 P! L/ FMain effect, 主效应
6 P8 n( o% v) w7 C3 \Major heading, 主辞标目
# `1 K" Z7 q% Z: E7 {+ O3 X4 f' wMarginal density function, 边缘密度函数
+ K; U8 P# r) pMarginal probability, 边缘概率
R i/ F: i; V1 b- v8 Q8 CMarginal probability distribution, 边缘概率分布 h7 m( [$ I, z/ y, G
Matched data, 配对资料
' K D1 W- U$ A8 n* J% `Matched distribution, 匹配过分布
3 ?( S" \2 b4 w9 k9 j* ?0 EMatching of distribution, 分布的匹配' H6 r7 W: `7 Q6 b- L5 _ N
Matching of transformation, 变换的匹配7 C8 g3 Y- I" O' W; K4 |: `
Mathematical expectation, 数学期望) ~# w( ~/ h: Z9 x
Mathematical model, 数学模型4 l! Y7 v( A* ]$ Y
Maximum L-estimator, 极大极小L 估计量# v1 {" W. ^& t. V
Maximum likelihood method, 最大似然法
4 \8 t' \+ n( b. o; S EMean, 均数
% R; {. G. |- N6 M( ]( Z `Mean squares between groups, 组间均方
# _5 q7 ~3 o' O8 y& t; @Mean squares within group, 组内均方6 q9 q" d) R+ ] d' R9 I
Means (Compare means), 均值-均值比较
. a# [$ W# h3 [- i! a6 Y( AMedian, 中位数
# b0 d* A/ r% T- ]Median effective dose, 半数效量9 d; n" m6 j: K) ^$ u
Median lethal dose, 半数致死量( a+ Q/ J4 _* Y0 g# P% ]: P9 D
Median polish, 中位数平滑
4 N9 r" X' G2 _1 C. D5 ^$ DMedian test, 中位数检验* A0 R& U9 F! F
Minimal sufficient statistic, 最小充分统计量+ V( h( q( A; p) I0 U/ U
Minimum distance estimation, 最小距离估计
8 N$ o# Q6 K) K( `8 w( H* Q% ZMinimum effective dose, 最小有效量
" U6 S6 g2 R* C8 \# y3 @2 eMinimum lethal dose, 最小致死量4 [% [! T( |0 J, H$ _) L+ R& n
Minimum variance estimator, 最小方差估计量
9 L5 X8 U6 j HMINITAB, 统计软件包
; y# \7 B z6 v0 PMinor heading, 宾词标目; s% Q- T% L% K/ c. p
Missing data, 缺失值; {6 g; |5 I! H% k
Model specification, 模型的确定
8 O* ]0 n- X- s1 f% _Modeling Statistics , 模型统计2 w) r6 {& I1 a, ^, J
Models for outliers, 离群值模型4 N4 ?1 g7 K) X
Modifying the model, 模型的修正0 C$ E! W! L- w% M
Modulus of continuity, 连续性模
! U7 O' X9 g+ r& O! W6 G7 ]Morbidity, 发病率
/ S& H# Q! I* L: J$ m' a/ AMost favorable configuration, 最有利构形
/ F* A# _. B# ~Multidimensional Scaling (ASCAL), 多维尺度/多维标度$ c2 m# H O/ u: N: X- L4 H; u) E
Multinomial Logistic Regression , 多项逻辑斯蒂回归+ p1 p! X& w/ `3 M$ P6 g O$ \8 i
Multiple comparison, 多重比较
+ |6 e" Z7 S/ q' a* a! UMultiple correlation , 复相关
+ f4 `1 I8 u- |* }Multiple covariance, 多元协方差3 S+ e; f6 ?9 z
Multiple linear regression, 多元线性回归
: B' Q c) B- [, x* J4 Z0 VMultiple response , 多重选项' ?8 `1 s2 V f' G0 n( K/ F" U! W2 ]
Multiple solutions, 多解
/ L' E* ^9 O) V7 \; F/ rMultiplication theorem, 乘法定理
3 y4 H1 O3 i6 @- z$ M0 |' ~% oMultiresponse, 多元响应/ e. U* C ?" \5 ~
Multi-stage sampling, 多阶段抽样 a5 D# t' [8 d, O1 c6 {
Multivariate T distribution, 多元T分布: d, y# N% O1 U; ]. N
Mutual exclusive, 互不相容$ ]! s3 C3 A9 U4 B
Mutual independence, 互相独立
, a" n8 N9 G4 G2 H! WNatural boundary, 自然边界
# b, V9 B6 _, ~Natural dead, 自然死亡 k+ L5 G; | m- {- H2 [0 V1 p' T T8 U. q
Natural zero, 自然零
6 j8 j+ Y) q" R& C) E7 [Negative correlation, 负相关/ \/ g" c" e& V2 J1 h
Negative linear correlation, 负线性相关
. C' o# D' Z V6 bNegatively skewed, 负偏
4 S1 l/ Z, z: V- CNewman-Keuls method, q检验
9 T8 B- Q# [/ m6 @NK method, q检验
1 t% a( w' J" I! C& g0 P* @, S) aNo statistical significance, 无统计意义
5 E- T: Z2 W8 B3 x* GNominal variable, 名义变量, }: m, Z, D' A, n- q+ H
Nonconstancy of variability, 变异的非定常性- C1 r, Z2 Z& O2 [' Z7 u
Nonlinear regression, 非线性相关5 {/ U" E8 V* ^/ z, Q+ W% M/ e
Nonparametric statistics, 非参数统计& Z: t3 L- j7 R! h0 R# p( _1 L
Nonparametric test, 非参数检验
8 }# p/ V# j) Y$ u2 p: k0 HNonparametric tests, 非参数检验
5 Q" L# p" f; L5 S. r) A' }Normal deviate, 正态离差
/ b5 n7 V- |. U+ ?( dNormal distribution, 正态分布5 @: K4 R0 [/ C
Normal equation, 正规方程组
& b$ k2 {0 P4 m. o4 [Normal ranges, 正常范围
* s9 o# z8 @# C7 D6 N8 I4 w- YNormal value, 正常值
6 n) m5 U6 W1 O% m5 N3 H; f! nNuisance parameter, 多余参数/讨厌参数" Y) T* D1 k+ Q" c7 O
Null hypothesis, 无效假设
' R, o/ I. m% [$ z. A LNumerical variable, 数值变量 ?4 V% p! \, j$ k
Objective function, 目标函数7 K& q+ n- e; `% S
Observation unit, 观察单位# m! ]+ S9 X% q6 f+ e+ d
Observed value, 观察值
) E2 w+ H4 _# TOne sided test, 单侧检验4 o/ {# V9 q v/ t( p% v% t! z1 J
One-way analysis of variance, 单因素方差分析
! w+ _2 `+ d' V+ X/ HOneway ANOVA , 单因素方差分析
% x/ J5 l: n/ N; a! L/ S' q0 z: ?3 g/ WOpen sequential trial, 开放型序贯设计
" i: o, D1 |3 T3 ^4 H9 bOptrim, 优切尾1 N6 E P D$ e% m/ N) n! v
Optrim efficiency, 优切尾效率
* u ?% b% E0 W, u0 X; o& ]4 sOrder statistics, 顺序统计量
7 U% ~0 y: u0 l$ N/ O% SOrdered categories, 有序分类9 w- O- @0 G3 X& S4 L7 M1 E
Ordinal logistic regression , 序数逻辑斯蒂回归7 @: K# F' a* u. l; H- M4 Y
Ordinal variable, 有序变量
: x+ ^- s: P9 d* HOrthogonal basis, 正交基
3 c. Y' u- b. GOrthogonal design, 正交试验设计
b* X8 K- B# L$ @/ Z& W2 e: a! `Orthogonality conditions, 正交条件
M" S& f5 u4 @4 S; g2 j; c2 }ORTHOPLAN, 正交设计
/ D- f- F; x; y( K: wOutlier cutoffs, 离群值截断点
! I) @/ O" m# K1 N# ~Outliers, 极端值% h0 C1 _% V$ o$ D1 Q
OVERALS , 多组变量的非线性正规相关
* Q4 Y9 V& ^$ XOvershoot, 迭代过度
; P8 ]' ~! F# x9 x3 Y+ A, EPaired design, 配对设计* w& s: o0 ~" r6 g# A* y, j! {& k2 t
Paired sample, 配对样本$ w2 F2 r$ ^7 K
Pairwise slopes, 成对斜率
' L( m/ C, I FParabola, 抛物线
8 Z' f+ v4 U& L, JParallel tests, 平行试验
$ j/ O( d( ^# C& rParameter, 参数* c4 q6 S( P, j7 x8 {9 z
Parametric statistics, 参数统计/ T/ ^+ c( U% R; x
Parametric test, 参数检验* e1 R4 t, V* ~# T- b' d
Partial correlation, 偏相关7 Y, w6 j( r/ @4 r3 a
Partial regression, 偏回归
' u, W* k# _& {+ iPartial sorting, 偏排序
0 Z9 e ]0 D( \. L2 K& bPartials residuals, 偏残差
( y! i" Y9 _" p ?1 [' y; \Pattern, 模式
0 k% F# ?; X: D4 YPearson curves, 皮尔逊曲线
: P' K n2 |9 `' M$ lPeeling, 退层
V0 N4 \+ T+ TPercent bar graph, 百分条形图. S, k) x/ |) g% O5 w+ H- c
Percentage, 百分比
1 f, j; J, {# z9 gPercentile, 百分位数
% [, C/ N% O4 E p/ `( u# BPercentile curves, 百分位曲线
. h6 v: R+ }7 M5 S3 y' ePeriodicity, 周期性" g2 b% Q0 c' \) E; [; @$ Y
Permutation, 排列4 k( e' l; t- g4 T
P-estimator, P估计量& |+ e8 W: l& Z8 ?7 A- ?9 X
Pie graph, 饼图
% b9 M- d. z( D( i) Z% [Pitman estimator, 皮特曼估计量
& W: r, ^' V, A. n9 r6 l9 N% L% _4 [Pivot, 枢轴量9 O; O% d5 e& T) b9 L* j% v
Planar, 平坦& m( ]( i3 W/ z$ ]0 |$ y4 b& K
Planar assumption, 平面的假设. Z, a& p+ z6 D& ]
PLANCARDS, 生成试验的计划卡
) {. c# V& h$ x- G/ ^Point estimation, 点估计7 h. Y( q7 v$ L( O, {. B7 J5 ?+ k
Poisson distribution, 泊松分布
, D0 F! c* d( l2 G. O# S" s$ fPolishing, 平滑/ o( ]5 s" b% }5 S
Polled standard deviation, 合并标准差
- r$ N% A& u( J* y3 M( PPolled variance, 合并方差
8 i% ^* v3 h) J) s [# XPolygon, 多边图
: E( k5 p9 `6 K6 e* t8 vPolynomial, 多项式
s5 m- V; x/ e: J1 k: ?Polynomial curve, 多项式曲线9 I4 e, V+ \/ l3 S
Population, 总体
% R" J9 j, u5 o; A3 h6 u% D* M5 VPopulation attributable risk, 人群归因危险度- b1 J1 Y+ ]/ s& p F5 B/ ~( H
Positive correlation, 正相关
0 Z; f4 g; H9 n& r! x, @! m1 xPositively skewed, 正偏7 U! w! ?# ]" h2 j$ F1 @6 g
Posterior distribution, 后验分布
; x+ G9 }2 T. O2 tPower of a test, 检验效能, ^# G# e) h$ M( J3 a
Precision, 精密度
2 Q5 O6 Z: J2 N1 F' m8 l% WPredicted value, 预测值7 j3 X* R) ~! V) n2 Q$ A5 ]
Preliminary analysis, 预备性分析
" f/ b, k+ U; B9 ^Principal component analysis, 主成分分析
- K5 @6 N6 ~; l' HPrior distribution, 先验分布
2 }3 T9 i8 G, @, ~" aPrior probability, 先验概率
9 e) y0 S$ a5 M( B( U1 `" S, TProbabilistic model, 概率模型
; }! G _6 z M) R/ B8 y2 x& z9 kprobability, 概率3 H/ A/ D3 k. U- c
Probability density, 概率密度
+ E8 }- N0 v& _/ \' F1 HProduct moment, 乘积矩/协方差
' f9 ?9 s8 X$ q* \Profile trace, 截面迹图( V% x' T2 y- ^1 i% e
Proportion, 比/构成比; D8 b9 ~" a7 z6 I( \" d# Y
Proportion allocation in stratified random sampling, 按比例分层随机抽样
; {9 E. c" p. ZProportionate, 成比例- D) B$ L* e: ?2 h& C1 x+ C
Proportionate sub-class numbers, 成比例次级组含量! R5 H0 V# ]# K) O% K
Prospective study, 前瞻性调查
5 |) l" j! C% Z% Z# z3 VProximities, 亲近性
2 p7 ^0 \( x5 q' i3 R( ~3 R1 _Pseudo F test, 近似F检验
9 j* ^4 B) W1 |0 ^/ y; i8 CPseudo model, 近似模型
9 G3 I; [+ X: S( T( aPseudosigma, 伪标准差
& @/ n: Z. g5 Y4 t" cPurposive sampling, 有目的抽样
S) e) n! v! ~# n. uQR decomposition, QR分解5 ]2 q9 _5 j1 t/ }" \* Q
Quadratic approximation, 二次近似
5 j" `6 Z4 S0 X) Y O' fQualitative classification, 属性分类! o& |! m8 i N* l0 y0 j% Z: c
Qualitative method, 定性方法
" E% y. O7 n9 p S* \# XQuantile-quantile plot, 分位数-分位数图/Q-Q图
! \4 x Z4 M' Q% ^8 eQuantitative analysis, 定量分析1 ^0 _' y3 W3 J% D, N; z
Quartile, 四分位数4 ^; z4 |3 @' H6 W
Quick Cluster, 快速聚类! J$ b5 s$ W& c
Radix sort, 基数排序
3 O/ D: _* T, N6 X5 hRandom allocation, 随机化分组
! ?8 d h' K# {Random blocks design, 随机区组设计& E2 r' z0 f6 u5 e
Random event, 随机事件# G0 U) P( x2 u& M% p) H
Randomization, 随机化" L$ I- g" F9 L) V3 c
Range, 极差/全距1 d+ q! ^; N: E$ _6 W: A: u
Rank correlation, 等级相关 } ?) T( C' C8 R
Rank sum test, 秩和检验# u, o( o% z& T% F
Rank test, 秩检验6 z) F8 f- Q8 R. Q
Ranked data, 等级资料( a' W- ~! M7 Y7 |5 U) ]" h: V
Rate, 比率
9 ^. R, Y0 Z+ z0 Z/ F0 s1 jRatio, 比例" c( z5 V. L: Q2 _
Raw data, 原始资料
! v* `7 \6 L0 IRaw residual, 原始残差
0 i+ O) W, p5 X8 E8 u) ?% \Rayleigh's test, 雷氏检验
( _) K/ t4 {: c. T& ARayleigh's Z, 雷氏Z值
1 m! Y+ H% E/ F$ z4 XReciprocal, 倒数
( A g3 D. b7 s* V9 ~$ ^' P: FReciprocal transformation, 倒数变换+ j6 {+ t! @5 U' @% x
Recording, 记录3 T1 Z' X/ r' I r, F! o: J
Redescending estimators, 回降估计量5 m0 k5 {, R B7 G8 k
Reducing dimensions, 降维: }1 E' I5 b# w1 }7 u: J4 U
Re-expression, 重新表达
% [5 E& y4 y8 nReference set, 标准组
0 N1 P: H% J9 r4 V O& v f DRegion of acceptance, 接受域' H; r) x3 O& q; I+ c1 ]
Regression coefficient, 回归系数
! J6 d( V1 F a, M oRegression sum of square, 回归平方和
6 {, I( z% z1 K4 @0 { B: j- V# DRejection point, 拒绝点2 `. U, n" g9 U$ @+ L. a7 L, P
Relative dispersion, 相对离散度- h- ?" x$ T( P- H
Relative number, 相对数
n( l2 z$ E# N+ N! A* }" A4 IReliability, 可靠性
: r; T7 c. m0 ]; s# BReparametrization, 重新设置参数
" H8 x% N4 M- gReplication, 重复, B& u. Z3 q0 E6 x7 d
Report Summaries, 报告摘要
) s& V7 v& O) x7 O6 n1 pResidual sum of square, 剩余平方和
4 k5 ^. I& x V$ W0 QResistance, 耐抗性
9 w3 e! X6 x, `Resistant line, 耐抗线
" n( b Q* G7 t$ V% vResistant technique, 耐抗技术. G* A4 ~7 S: @6 q9 I7 F
R-estimator of location, 位置R估计量
: ]$ G$ U' M1 \" J: F4 P ?& I1 i vR-estimator of scale, 尺度R估计量" @9 |4 y' A3 R# V
Retrospective study, 回顾性调查
! Q4 m* C; N+ |" N6 |Ridge trace, 岭迹( `( t5 ?% Q# _. l& b3 p+ S
Ridit analysis, Ridit分析
8 d! M; T8 p. x; l" ARotation, 旋转. i9 |) s5 X+ m
Rounding, 舍入
! C. j) Q- o) v+ W( ]5 ?Row, 行
$ ?. ^8 x; _2 i! W. }+ @% G) `! ORow effects, 行效应9 T' h/ q6 p$ X2 \
Row factor, 行因素9 M; B# N. t* j* ^6 k" L0 N
RXC table, RXC表/ |9 H3 u5 r y8 U. h! O6 B! f7 Z
Sample, 样本& M _$ I0 P5 Z4 `4 \! u
Sample regression coefficient, 样本回归系数" l$ e6 w$ w4 V/ ` _
Sample size, 样本量2 q v! x1 x: f: ?) Z" C
Sample standard deviation, 样本标准差' L8 K1 o6 R- b9 J) K
Sampling error, 抽样误差( k0 k7 b. W# }( P+ z
SAS(Statistical analysis system ), SAS统计软件包
; `* `9 }' q8 G' ~& i; J0 ?* s: g8 [Scale, 尺度/量表
& x8 o4 ?' N& k! |Scatter diagram, 散点图
* z: O2 g9 q5 o8 ^) t( k- ^Schematic plot, 示意图/简图5 D8 P. g: y$ C4 q
Score test, 计分检验 B5 N/ W: [+ \6 a2 ^" C1 b4 C9 m% Z% \
Screening, 筛检
1 d. [5 @, V. L' [- Q6 S7 ?SEASON, 季节分析
6 S, Z" Y! w$ K4 [) K4 V+ r( OSecond derivative, 二阶导数5 W( @% y x7 c# g4 m$ {
Second principal component, 第二主成分
( h5 h. E# I! Z/ FSEM (Structural equation modeling), 结构化方程模型
) Q/ ?1 Y7 R' m, |8 [0 c7 ^: ?; ASemi-logarithmic graph, 半对数图& S, B$ y d/ s! x9 R$ g; |
Semi-logarithmic paper, 半对数格纸0 Z% F8 }! d! C( x) t7 z& g
Sensitivity curve, 敏感度曲线* D2 ~" d+ Z4 D* D. @9 \6 U- C
Sequential analysis, 贯序分析
1 @- K; N' f! d- d2 _$ sSequential data set, 顺序数据集
& g; v0 O- r: XSequential design, 贯序设计+ b% Q& U) {4 P+ g9 f- Z l) N6 a
Sequential method, 贯序法
# w: [6 l8 J/ m1 Z! v! z+ s0 V& GSequential test, 贯序检验法
]8 A' L% n0 G2 \Serial tests, 系列试验
7 {7 [5 H- j4 i8 e# `# UShort-cut method, 简捷法
' E6 {6 {) R+ s5 P) T5 _8 z( kSigmoid curve, S形曲线
! v; s2 q2 q- U+ V; [! BSign function, 正负号函数7 p5 W( Y4 e/ J
Sign test, 符号检验
' ?+ r d1 U& B; n7 ^! GSigned rank, 符号秩5 F& m' c1 I3 l4 z
Significance test, 显著性检验
|" p1 M9 ^7 c) Y" `: r5 bSignificant figure, 有效数字
M: c, r' u2 N1 a" U/ nSimple cluster sampling, 简单整群抽样+ G& `+ ?6 d, t/ \
Simple correlation, 简单相关( ^% K, ~* R- j2 C( k- D& i
Simple random sampling, 简单随机抽样
* }2 x- j/ [+ U9 P, [Simple regression, 简单回归; ?! Z& |2 U2 i
simple table, 简单表3 r" \( M- m* b+ ^: _9 S+ \& F
Sine estimator, 正弦估计量
; R1 N8 y2 I) q H: P7 v: ?0 aSingle-valued estimate, 单值估计6 {, y5 X* \+ W, g! ]/ a* M
Singular matrix, 奇异矩阵
9 d5 D D" t! _0 Y) C7 Q: ESkewed distribution, 偏斜分布! X' S; O; p8 r% d
Skewness, 偏度1 w! I5 \% }2 F$ l
Slash distribution, 斜线分布% x9 y2 E3 U% d( ?- {6 z% X: A; H
Slope, 斜率" E5 O2 @! z& _
Smirnov test, 斯米尔诺夫检验+ V- x; `9 q# b, G7 ]
Source of variation, 变异来源$ ~( i6 k! v7 v* ^6 i8 F
Spearman rank correlation, 斯皮尔曼等级相关
) c+ s' @' @& G! w# o( R1 USpecific factor, 特殊因子
4 Z4 E2 N+ _0 D6 L" A6 fSpecific factor variance, 特殊因子方差
& ?+ \: s' K+ l6 F7 t0 ~Spectra , 频谱6 Y7 ]# m6 N5 _& U5 |. N9 g
Spherical distribution, 球型正态分布
. x- ?; `* P8 aSpread, 展布( X+ R7 r" d. G
SPSS(Statistical package for the social science), SPSS统计软件包
( X7 X3 W& W& x. w GSpurious correlation, 假性相关/ u9 R% R$ a' T+ k/ y3 k5 ?5 U9 A
Square root transformation, 平方根变换9 X, H5 l3 `; i4 Y$ o( R R. A4 _9 v; D
Stabilizing variance, 稳定方差3 x; T6 n. Y n+ }3 H" b( u
Standard deviation, 标准差! T& m- N5 I" g$ H* ]$ r6 @
Standard error, 标准误
; V$ i( O' R3 t, \$ {4 V/ ~Standard error of difference, 差别的标准误
& Q5 @0 e, n" `6 ~Standard error of estimate, 标准估计误差. ~; J8 T& O9 t0 ~3 [
Standard error of rate, 率的标准误) H; M$ ~& Z3 ^1 q' T
Standard normal distribution, 标准正态分布6 M7 t$ ~, p8 ]8 }* f% \. B9 J' |
Standardization, 标准化
4 d/ L1 ?3 Z% ~$ m' jStarting value, 起始值% b* C# Y3 J* v' S; {+ \: t8 T
Statistic, 统计量
2 d o" U* p+ XStatistical control, 统计控制9 B8 J! b% n/ n) S& I- o
Statistical graph, 统计图0 Q! ]6 f; ?9 P7 l5 z
Statistical inference, 统计推断$ Y8 ~2 E# z" l( P* l2 N
Statistical table, 统计表/ ~5 J1 B0 p, X
Steepest descent, 最速下降法
# g3 W7 `9 O4 }Stem and leaf display, 茎叶图5 L$ P; x( s( R# J6 f% `' T
Step factor, 步长因子- m& L# b5 e) R
Stepwise regression, 逐步回归; a$ `, q# \, }' v' F) k
Storage, 存
1 S# h& L# K- T' gStrata, 层（复数）0 X `2 s4 z' w9 g. p5 k. l, A. b
Stratified sampling, 分层抽样
+ Z5 `( `: g7 X, P5 w/ n$ yStratified sampling, 分层抽样; A' V: @+ I* F- d+ L
Strength, 强度& g9 v' \5 D2 B9 a0 h1 o: `4 Q4 k0 \
Stringency, 严密性
6 S* {; X3 y* w- ?Structural relationship, 结构关系
" A: I+ ~; z% x5 HStudentized residual, 学生化残差/t化残差6 c2 Q0 N K$ B, q) r0 U
Sub-class numbers, 次级组含量" J$ z% e( t; S0 A! T
Subdividing, 分割
" a2 ^9 ]7 `" S7 k/ ^: Q: cSufficient statistic, 充分统计量
" A9 N: a/ u/ KSum of products, 积和+ c1 b4 s$ k. ~7 G- f( {7 R9 B h
Sum of squares, 离差平方和
6 c3 ~ N: m. @5 ~4 mSum of squares about regression, 回归平方和! }, x- E; F8 G
Sum of squares between groups, 组间平方和+ S5 [) H$ ]6 Y7 q. G+ e$ F
Sum of squares of partial regression, 偏回归平方和
% [2 i+ m' x% \( r. {1 vSure event, 必然事件9 \# d3 B& E; q+ {* S$ y2 b) ^7 ]
Survey, 调查4 ~; f/ Z9 N4 u+ Q' Y
Survival, 生存分析, [$ w" r [7 U! y& R
Survival rate, 生存率
$ ~3 ^2 }2 {/ c- ^) k- U2 pSuspended root gram, 悬吊根图
! @( @: ^; T2 T9 i+ R2 N) R$ B/ o& WSymmetry, 对称
( E, U6 z b5 z' j7 x1 w7 p% bSystematic error, 系统误差$ Z. D7 g1 q5 B8 ?0 \- Y/ E
Systematic sampling, 系统抽样
3 @1 t/ |1 X" ]- YTags, 标签
, e/ {% {2 u* w1 c2 \% O& C, MTail area, 尾部面积, [9 N; X- O! X- L
Tail length, 尾长
4 w6 ~) w+ z- R! a2 J0 x6 NTail weight, 尾重
5 z$ F, M, X! U. ]Tangent line, 切线
( Z# ^( |# l9 ~$ i3 Q3 wTarget distribution, 目标分布2 `, ^% E/ Y# r! t" v
Taylor series, 泰勒级数1 A1 Z8 y8 [2 M8 H* p5 `
Tendency of dispersion, 离散趋势
0 g$ h: ~0 D( p3 M7 c' T" ?Testing of hypotheses, 假设检验* S' X% f" I+ l) n; C
Theoretical frequency, 理论频数' A6 X2 x6 r! p) g: c5 ~7 }
Time series, 时间序列3 E' `+ B2 L) V& L7 Y
Tolerance interval, 容忍区间, X+ q7 t& x+ n8 a/ _
Tolerance lower limit, 容忍下限
3 }0 T) Y6 ~+ H0 ~& C7 M/ |$ ITolerance upper limit, 容忍上限
E1 E: y: P- w/ P7 z+ }4 Z- |; K6 lTorsion, 扰率
9 |% z0 F3 o% O5 s0 zTotal sum of square, 总平方和, C* B+ v* M9 Z j6 O- b
Total variation, 总变异
, `; u! S; ]+ L( s; u/ h9 A; v) gTransformation, 转换3 y- w; T. L0 @& S( p8 i
Treatment, 处理" E3 I5 A6 X3 L
Trend, 趋势
& w, H7 |) n* ? }Trend of percentage, 百分比趋势
& R* X9 a( p6 V" ]6 D! |/ qTrial, 试验0 c* g/ S. Y3 x' y3 G; J
Trial and error method, 试错法
* K; w8 r' W; a5 X/ B# [Tuning constant, 细调常数
/ q* I& X, X& K5 v. TTwo sided test, 双向检验& k0 r" M: A& Q1 T& w
Two-stage least squares, 二阶最小平方& S3 e3 s4 q( [8 M M1 u3 {( i
Two-stage sampling, 二阶段抽样
) a9 l- L N# T& j" q/ bTwo-tailed test, 双侧检验0 c6 N: Z9 A; |& u
Two-way analysis of variance, 双因素方差分析
' Y, s' O7 ?/ _8 t* m$ ]" r0 Q' GTwo-way table, 双向表/ n0 z! C) ]8 R8 [& @* p2 \
Type I error, 一类错误/α错误
0 k. H% ]6 N9 w* M! J0 m {# Y) NType II error, 二类错误/β错误
) Y( A- |# W$ e6 l" \* kUMVU, 方差一致最小无偏估计简称( f9 [, H$ m0 F% F! C5 @
Unbiased estimate, 无偏估计
, ~/ E' s C% x, W5 EUnconstrained nonlinear regression , 无约束非线性回归
; q& i' b8 s2 X2 t2 |; u: m+ h$ pUnequal subclass number, 不等次级组含量" L9 @/ Y& r/ f: l
Ungrouped data, 不分组资料' C5 h, G# ^- u2 r
Uniform coordinate, 均匀坐标
+ {/ e/ j0 B# sUniform distribution, 均匀分布! t% g$ l+ `( ]6 P
Uniformly minimum variance unbiased estimate, 方差一致最小无偏估计
9 O3 p0 Y4 _ B/ F% H; e* @6 }. \Unit, 单元
5 Z! d2 O" G9 g! @) NUnordered categories, 无序分类
. ?2 x$ |3 f5 ?3 C( ^1 J6 c, R2 [Upper limit, 上限& b L" r* T& Z* n
Upward rank, 升秩
$ ?$ y; X+ P6 I+ x9 U& V* ^- ^Vague concept, 模糊概念
- J6 ~" n+ S/ O- o; OValidity, 有效性5 t* N: ]2 f* L7 h% c
VARCOMP (Variance component estimation), 方差元素估计1 _7 b( f; ^$ E$ _, r7 v
Variability, 变异性
9 Q# G$ {* |; G/ \: P7 D6 y4 S eVariable, 变量
( c& h1 n2 G, D2 I' l+ `: AVariance, 方差+ Q) A; ]% k( R @; `
Variation, 变异
+ V3 I' {& h1 Y: y- L3 m/ xVarimax orthogonal rotation, 方差最大正交旋转
! b* j2 j8 W: A! ?1 F( {Volume of distribution, 容积
+ n8 R8 R# q- W yW test, W检验
C2 Z p* |' m5 cWeibull distribution, 威布尔分布) {) e, {) T4 G1 q3 X6 Y9 [
Weight, 权数 }& q: X2 j W( f
Weighted Chi-square test, 加权卡方检验/Cochran检验5 G5 J( }- e( D* ^7 i
Weighted linear regression method, 加权直线回归
+ `8 o& A- a: u; [Weighted mean, 加权平均数% a! f' `% Q; I: S
Weighted mean square, 加权平均方差
, w( f4 a3 X6 E, U- L( BWeighted sum of square, 加权平方和
% l1 J7 v! q1 C7 h+ L) HWeighting coefficient, 权重系数4 t/ i, U2 ?; x: S
Weighting method, 加权法
- d [9 f }% v. D7 W" C4 v* b2 UW-estimation, W估计量( i# Q: x0 L, ?9 C
W-estimation of location, 位置W估计量
7 z+ ~. t8 q! u! t% p- l5 fWidth, 宽度
/ v1 h' h8 a' KWilcoxon paired test, 威斯康星配对法/配对符号秩和检验* s3 Q4 c! j- _
Wild point, 野点/狂点$ U9 o& L" T8 h+ Z' n C d2 o! n8 C
Wild value, 野值/狂值* j: B# Y" _3 j& P# k+ s3 @
Winsorized mean, 缩尾均值# [( T9 n6 e% ?6 @ \% C6 J* a
Withdraw, 失访
" _0 ^( K O% dYouden's index, 尤登指数- ]- r" C8 s: J! E
Z test, Z检验
) L7 @ L( z( \$ r( DZero correlation, 零相关6 z# ] Y& n$ l( Z
Z-transformation, Z变换 |
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发表于 2009-1-6 22:05
