|
|
Absolute deviation, 绝对离差
+ Z# x$ S1 t* ?% RAbsolute number, 绝对数/ M% S3 e& K: Z, e
Absolute residuals, 绝对残差
4 |& ~' W4 v9 u: F0 }Acceleration array, 加速度立体阵
* s: {2 ]. K0 j( y1 _" |Acceleration in an arbitrary direction, 任意方向上的加速度
' U( U2 J- c, CAcceleration normal, 法向加速度
: \$ {: v# l, ]' u+ \" e# Z/ RAcceleration space dimension, 加速度空间的维数
" I- _1 Z1 z7 O1 K9 `1 aAcceleration tangential, 切向加速度% S z) N6 Z" |3 O d5 w
Acceleration vector, 加速度向量
" T$ G" T" d- e$ }* R' dAcceptable hypothesis, 可接受假设
+ [3 g% I2 E; @- T0 Y$ TAccumulation, 累积$ B9 V8 k7 h {% P" H( X. Q* A
Accuracy, 准确度- @: o8 T. m) A' ]2 B% I
Actual frequency, 实际频数3 X! c- O, F% t$ d
Adaptive estimator, 自适应估计量: _; X+ x6 g- d6 F
Addition, 相加
4 ]0 O5 j- w3 d# b& uAddition theorem, 加法定理( z9 m# q( q# j. c) o Y) E
Additivity, 可加性
4 h, O' f# I, X7 FAdjusted rate, 调整率
1 ^. q7 g$ Q6 ^) M- P0 z( G8 PAdjusted value, 校正值. S4 N' n4 _* j/ {$ T- r
Admissible error, 容许误差1 E+ b& H/ t- N0 x1 J8 E$ `
Aggregation, 聚集性" \3 a. N( _# u. j
Alternative hypothesis, 备择假设" u: E+ _# _" M* ^
Among groups, 组间
6 V9 S$ L+ _$ x2 RAmounts, 总量, @: ]4 F9 D% O: e- x$ E
Analysis of correlation, 相关分析
! r/ G7 l j( F; H" D2 Y/ [Analysis of covariance, 协方差分析
6 Z: g/ t! B6 b: aAnalysis of regression, 回归分析* Z& C3 W; [. P) s# T2 p. Y
Analysis of time series, 时间序列分析
* a' T K4 [2 [. z& m% \Analysis of variance, 方差分析; R% H0 E& B9 h9 O
Angular transformation, 角转换7 [0 t" M9 l: j3 E' i
ANOVA （analysis of variance）, 方差分析: u# _6 W6 c0 Z: h. {
ANOVA Models, 方差分析模型
( X8 X5 J% }9 ~& OArcing, 弧/弧旋! ~6 g- p5 B) t4 E' M
Arcsine transformation, 反正弦变换0 H# ~$ p$ o$ ]/ F
Area under the curve, 曲线面积
' B; Y( A" T5 P& hAREG , 评估从一个时间点到下一个时间点回归相关时的误差 4 a6 S0 u! L' L' }8 g" R8 ^
ARIMA, 季节和非季节性单变量模型的极大似然估计
/ B2 H. F/ d- c) |& [Arithmetic grid paper, 算术格纸& z- `& `$ D5 L1 e* }5 X/ k
Arithmetic mean, 算术平均数6 t& a6 a- z4 p' l6 h( t; ~
Arrhenius relation, 艾恩尼斯关系
' D! L7 O: r+ `/ \4 A7 d; [8 e. q, O' fAssessing fit, 拟合的评估
3 G F; }* n: R* W; N0 I* JAssociative laws, 结合律
- s! f' N! q2 a- VAsymmetric distribution, 非对称分布
6 y& |$ K$ O1 ~' `Asymptotic bias, 渐近偏倚
3 ]- n8 h4 q! c; Y) sAsymptotic efficiency, 渐近效率; L7 W1 N T3 m0 m: N
Asymptotic variance, 渐近方差- n- u) K2 ?0 g0 a, e: h
Attributable risk, 归因危险度
: F' `6 S; T- rAttribute data, 属性资料0 N. A( |4 j6 I: S5 |1 ~9 j
Attribution, 属性. J5 }# _& b5 U w& Z7 @. Z
Autocorrelation, 自相关# T3 C& `7 y* `3 Y6 ?; Y: c
Autocorrelation of residuals, 残差的自相关! F9 c' p3 D1 b( k5 Z) ?
Average, 平均数; G, ~9 _5 C8 K4 G( h {' ^
Average confidence interval length, 平均置信区间长度
6 U0 X6 M1 i, R+ e6 H, {9 OAverage growth rate, 平均增长率
! |+ j9 X3 J6 J& C6 T' p9 aBar chart, 条形图% S9 p, E5 }& v5 N( {
Bar graph, 条形图
/ f' v+ ^* y7 W$ g0 P# y6 {+ }4 _Base period, 基期) |8 j/ Y9 W7 q& C% r5 P2 e
Bayes' theorem , Bayes定理+ A) p; \/ J- X X5 L
Bell-shaped curve, 钟形曲线5 e8 A7 y. ?/ ^" j4 j4 u. W3 n) e
Bernoulli distribution, 伯努力分布; T+ V# ^0 O% W% }3 m5 N$ Q# Y
Best-trim estimator, 最好切尾估计量: a5 e% D3 R$ B3 L% O: U! E
Bias, 偏性
# r4 f' ^% B* L+ M! T! C: mBinary logistic regression, 二元逻辑斯蒂回归
+ |, V- t9 z5 I R7 h# @; f/ h8 VBinomial distribution, 二项分布
( q& Z6 [. C6 q4 ~. NBisquare, 双平方
/ J* A( Q* L! s9 C1 _Bivariate Correlate, 二变量相关. E2 V) Q5 T; v
Bivariate normal distribution, 双变量正态分布
# g( ]2 D5 K* SBivariate normal population, 双变量正态总体6 m4 X* k% c/ `4 k: a I
Biweight interval, 双权区间 F$ W# t: D$ Y
Biweight M-estimator, 双权M估计量* N; h: @! L, I6 L1 p9 D
Block, 区组/配伍组
: I# c4 @ {& r+ A( rBMDP(Biomedical computer programs), BMDP统计软件包3 s! B$ f% _2 D4 x
Boxplots, 箱线图/箱尾图
$ A/ ^' G; ^; T! L) P. QBreakdown bound, 崩溃界/崩溃点0 F; U$ c G; b
Canonical correlation, 典型相关
6 z! K f( E2 V5 g G+ r' s2 eCaption, 纵标目, K `; F8 h! _# E! c" S
Case-control study, 病例对照研究% T2 |. @5 w [7 v2 ^0 G" K8 c
Categorical variable, 分类变量
s( Y4 _% Z' I: h$ nCatenary, 悬链线4 J F7 H: n4 |6 g* G/ b
Cauchy distribution, 柯西分布9 F/ m$ i. a1 Z
Cause-and-effect relationship, 因果关系* Y( L( J/ P' C' q. p( z
Cell, 单元
" J: @) T9 R% c# G9 c2 ?Censoring, 终检# s* B4 ?" p: t2 w/ c1 n! ~
Center of symmetry, 对称中心: \7 A' ~; F; c, y) K
Centering and scaling, 中心化和定标8 E' S S9 ?. _8 t% W- ]# G
Central tendency, 集中趋势
9 {7 {9 k5 i4 A7 r' `Central value, 中心值
, w; u$ c U$ V- ^. t7 b& V9 L: h1 ~CHAID -χ2 Automatic Interaction Detector, 卡方自动交互检测
! z! \- K4 H( ~$ f/ W3 |$ TChance, 机遇
5 N5 f, h3 Y, a: ]+ hChance error, 随机误差
5 x5 B5 g( s( o; x+ _8 AChance variable, 随机变量% I+ V2 i( _1 l
Characteristic equation, 特征方程1 U8 Y: R9 Y6 ^1 _
Characteristic root, 特征根6 L4 v1 ~4 u! D) T5 f
Characteristic vector, 特征向量
2 f! J$ b" T% S5 eChebshev criterion of fit, 拟合的切比雪夫准则
3 s( C9 a2 {3 S' j! U ?) r+ kChernoff faces, 切尔诺夫脸谱图# ^# H" e" D* X+ F! ^5 ~
Chi-square test, 卡方检验/χ2检验
3 W8 _# R5 F: m% C( p8 |' TCholeskey decomposition, 乔洛斯基分解
1 b# C/ U5 P1 _Circle chart, 圆图 # \5 q' x6 T- S5 ~
Class interval, 组距 q% n" @1 _2 q) G8 X2 T& `
Class mid-value, 组中值! k" }# I7 w$ a$ P6 R' A$ y/ D9 c% A
Class upper limit, 组上限
" @( x0 L! a" MClassified variable, 分类变量
# s9 a+ ]% u( ]Cluster analysis, 聚类分析
1 b* M3 O! U" f6 iCluster sampling, 整群抽样, T0 R' X: Q* F( f7 l) x
Code, 代码3 q% V4 m+ `2 Y+ {# W9 L8 R% x$ t
Coded data, 编码数据
& q p5 t* ^0 w* ?: S% ^Coding, 编码
+ e) p, ~0 B! q% B( HCoefficient of contingency, 列联系数
$ W: k' c7 H2 B; U+ V0 ~/ i3 Y5 OCoefficient of determination, 决定系数9 i& B: o {9 w; N7 ~7 N8 Q
Coefficient of multiple correlation, 多重相关系数( ~6 q7 Z f7 k' Y6 O& C
Coefficient of partial correlation, 偏相关系数
( a1 h" y0 G% |Coefficient of production-moment correlation, 积差相关系数' S4 b# ~/ _1 [' @
Coefficient of rank correlation, 等级相关系数
6 Q3 m/ w0 r+ C& \Coefficient of regression, 回归系数. H9 `) o1 }. \. U
Coefficient of skewness, 偏度系数
U% ^2 T5 g+ d5 W/ _8 s. l! NCoefficient of variation, 变异系数2 N- e1 P2 [. H) h2 w
Cohort study, 队列研究
& r: Y. o+ e, n4 m6 Y: TColumn, 列
0 V- C! Y G0 d, C1 u: \ CColumn effect, 列效应
8 f% z' s/ d" d, |1 Z8 P7 tColumn factor, 列因素
5 o: ]6 J4 x5 f% xCombination pool, 合并
2 a( m$ M8 t. s# y( Y: `3 G; m. z, @Combinative table, 组合表8 I( {1 p- Y' m5 j X; e: a
Common factor, 共性因子* R2 [& C% b0 C
Common regression coefficient, 公共回归系数
. x1 |* m9 ?; ?# k4 C4 fCommon value, 共同值
0 o$ T5 d7 S5 ?" V. a- TCommon variance, 公共方差
. g" y5 p m6 ]( W' R- pCommon variation, 公共变异- q4 D# i, _) V3 h- Z: @
Communality variance, 共性方差
: Y6 g9 K8 D( E, p& FComparability, 可比性) D- y, ~8 N* q6 [& P
Comparison of bathes, 批比较
% O( t3 j/ n3 [! |; t5 v! kComparison value, 比较值
7 [7 s2 s* d; t1 `: N7 RCompartment model, 分部模型9 s3 b* R- A6 A' Q0 j4 V
Compassion, 伸缩* u) o4 [. R; ~$ A8 g. a+ U
Complement of an event, 补事件 m5 X5 N6 Y9 Y. M1 X
Complete association, 完全正相关) t1 f' z1 \5 c0 ]
Complete dissociation, 完全不相关
5 d0 {$ H% w$ d% lComplete statistics, 完备统计量" `$ t$ J2 ~5 G! }. r) C
Completely randomized design, 完全随机化设计
/ B& {0 y* j7 dComposite event, 联合事件* {& J+ d4 E" O- `; T
Composite events, 复合事件: o a+ s# t; ^5 N6 c! l
Concavity, 凹性
" N7 c* v" X3 S/ o! Z' X. `Conditional expectation, 条件期望( k9 Y/ e- |. I D
Conditional likelihood, 条件似然; t- y3 q2 B I$ L. J, {! C( F
Conditional probability, 条件概率
; ] E7 b& ]" D4 j, bConditionally linear, 依条件线性7 b/ s- J8 m. q3 v! K/ j |0 q
Confidence interval, 置信区间& O7 | ]& v( P. g& a9 w
Confidence limit, 置信限
( j6 j% X, O; k8 Z, _+ Z# [Confidence lower limit, 置信下限
7 R( z# H0 P9 d1 B% d; @/ A% UConfidence upper limit, 置信上限
# P2 i o: O% d& fConfirmatory Factor Analysis , 验证性因子分析' o2 d$ Z1 ]5 S$ p+ B
Confirmatory research, 证实性实验研究
* h1 O$ ^. U# q$ ^Confounding factor, 混杂因素 U- K6 x( K# _( e5 X
Conjoint, 联合分析. J% {8 x- p8 j0 D' u& a, S6 h- Z+ S
Consistency, 相合性
) s$ a, Q# o2 ]& {Consistency check, 一致性检验
6 i: y! m3 Q+ b+ i9 GConsistent asymptotically normal estimate, 相合渐近正态估计4 ~% h# ]6 G3 x
Consistent estimate, 相合估计3 M! z6 {* U: K& w3 ^; ^
Constrained nonlinear regression, 受约束非线性回归
- P$ g' ^0 _- c, F" a3 T5 ?Constraint, 约束
' P( M/ L4 r4 t0 R# @1 GContaminated distribution, 污染分布+ y- n. b8 G9 ^4 u' ]: L( H
Contaminated Gausssian, 污染高斯分布2 g, y4 a9 u0 n) l0 l \8 b, _% G
Contaminated normal distribution, 污染正态分布9 {9 C& p0 Z7 L2 {5 x ^
Contamination, 污染0 }% B0 s% P7 V0 J8 ~, b' {
Contamination model, 污染模型
5 R6 A M x+ e6 xContingency table, 列联表
& }* U% @; G" w4 QContour, 边界线
" H" n4 A% a# G3 a6 L& WContribution rate, 贡献率. g7 c+ D0 W( W% E. A7 j
Control, 对照
3 x* m- f* A$ ^9 ]* T6 YControlled experiments, 对照实验
8 r/ o: n) w, U% l0 O: a5 jConventional depth, 常规深度: |7 X6 D+ ~6 G/ q9 d0 G
Convolution, 卷积1 a8 l5 U! L2 Q- }9 A# `4 c
Corrected factor, 校正因子
& k$ g. t2 O: ?- O( d5 H) ZCorrected mean, 校正均值$ p! a- }1 w+ w4 P: t7 g3 Q2 |7 a
Correction coefficient, 校正系数
\; q) n& d" O5 _: K' V7 PCorrectness, 正确性
+ A+ E, E. S! t/ DCorrelation coefficient, 相关系数
/ u0 f- q) j% ]# ICorrelation index, 相关指数
) f+ J$ @+ B/ ACorrespondence, 对应, N2 i5 ^; M3 {: @) a
Counting, 计数& a S1 I- i7 O( `. }% {) T
Counts, 计数/频数
7 E% p) |, y% x* W% t) dCovariance, 协方差! A" V1 h% v+ Q. Q1 s, ?1 s; e
Covariant, 共变 ; `1 a W3 J7 A8 {* Q+ X
Cox Regression, Cox回归4 s6 A* b1 R* ?" d
Criteria for fitting, 拟合准则# E4 s$ E/ q- z/ r5 u
Criteria of least squares, 最小二乘准则
$ a) f b/ e3 dCritical ratio, 临界比
7 n$ }2 s e. B, k! JCritical region, 拒绝域5 j0 n% p! b3 H7 z2 {7 `
Critical value, 临界值
; ]+ ^6 `& R3 \! J, d# ^Cross-over design, 交叉设计
- H2 C; T: e* y5 QCross-section analysis, 横断面分析
3 T% G1 C( T% B- J* }! ~! ~$ ~Cross-section survey, 横断面调查
; O3 D$ B' B3 L' u, @7 rCrosstabs , 交叉表 & m9 E5 _2 t8 N. \6 [0 f/ U
Cross-tabulation table, 复合表1 v0 K; Z. C A5 h1 j
Cube root, 立方根
9 {$ w/ i- J- M7 ?- aCumulative distribution function, 分布函数( C6 E5 Q) v1 Q G2 V
Cumulative probability, 累计概率
9 c, D) X$ }$ k! D! t% kCurvature, 曲率/弯曲# D) b* F, q6 [- }% X
Curvature, 曲率
* L; }' z* J3 f" pCurve fit , 曲线拟和 ! K! @' Z8 Y6 Q' z
Curve fitting, 曲线拟合
2 H2 G5 ?) l5 y) x/ q6 R7 ^7 Z, uCurvilinear regression, 曲线回归 T* k1 Q1 z. W: P* S
Curvilinear relation, 曲线关系9 n* P" T8 l7 B4 N* j5 }; C# a. `6 o8 \
Cut-and-try method, 尝试法
" Y, A1 ?9 X8 a; O- K, L* p! ICycle, 周期
- x J% U; x6 C: @$ y8 WCyclist, 周期性
7 ], z P& B" g; `' b. F8 j" A- l2 c1 ?D test, D检验2 k7 }( W( k4 j1 D7 e7 k# @) B5 K
Data acquisition, 资料收集
|( V- _& C y# y' }8 y- CData bank, 数据库6 w; [% q# ?- t0 i$ P
Data capacity, 数据容量
3 _8 D. E1 W; N( m0 y1 z7 \& }Data deficiencies, 数据缺乏' f; y8 L! x2 H4 P" }+ J5 a
Data handling, 数据处理! W0 ?# c$ x- u8 p1 T9 ~
Data manipulation, 数据处理, S" r3 c" ^ A) L
Data processing, 数据处理
8 T$ n8 {3 H1 w1 _Data reduction, 数据缩减0 O: E* t9 @0 J# S4 o3 k
Data set, 数据集. F1 `. D5 h+ |3 L( `$ l
Data sources, 数据来源, C! [" T# ]" ~- E( w J6 L5 F3 a R
Data transformation, 数据变换
( j! F: w, V, O- b8 z7 {Data validity, 数据有效性9 R6 m2 H$ t* `0 t1 F& ^* g/ j
Data-in, 数据输入
3 r7 p$ o! l T7 m+ uData-out, 数据输出6 v+ ` b. d1 L T. A+ a4 P; l0 k
Dead time, 停滞期7 G4 w8 w8 ]$ E9 L5 T. L
Degree of freedom, 自由度3 U% d. g3 h, c4 j1 ^( s$ x
Degree of precision, 精密度* s( I8 n7 s$ W$ C4 I$ t
Degree of reliability, 可靠性程度* j7 v, i5 k- Y {& w# M5 d
Degression, 递减 Q$ m. a* U. J; A
Density function, 密度函数
+ D0 Y$ y8 [! ^: FDensity of data points, 数据点的密度
; o; n5 v7 k5 VDependent variable, 应变量/依变量/因变量
3 V2 y+ c- r E3 WDependent variable, 因变量
) i1 n0 L7 H: h, M6 {& eDepth, 深度- z+ b. a! ?5 u* d' ?
Derivative matrix, 导数矩阵4 C" Z1 [" B& p/ M8 A$ z
Derivative-free methods, 无导数方法
$ C% ^6 g+ a- @Design, 设计
5 R4 B8 ]6 o( h; ADeterminacy, 确定性) i- ]' X g+ a: {! d" I1 B3 Z
Determinant, 行列式
& h: f0 M3 Z9 D% t- I4 c* TDeterminant, 决定因素9 x |" z7 I* }# ]0 _
Deviation, 离差
- D. J: p. U) n1 j3 w8 L2 NDeviation from average, 离均差
+ g8 k3 |" m5 x: ?( iDiagnostic plot, 诊断图# J6 s: [5 j% e: i
Dichotomous variable, 二分变量
9 _ j$ |0 v( i' w7 LDifferential equation, 微分方程
; V/ L/ J. ~0 T8 |/ JDirect standardization, 直接标准化法# }0 C$ |9 _: ~) \! k3 G) _
Discrete variable, 离散型变量
5 S; ~1 p' V5 h! @" e$ f" zDISCRIMINANT, 判断
9 d) f4 @8 F- yDiscriminant analysis, 判别分析
1 I5 j6 D. z% ?- T1 UDiscriminant coefficient, 判别系数
, V1 R( j. ~$ T5 YDiscriminant function, 判别值$ N! l) j3 X# n
Dispersion, 散布/分散度- b9 K f9 n9 }0 P* f+ C3 @
Disproportional, 不成比例的
. r7 R& x, N& i q$ ?4 GDisproportionate sub-class numbers, 不成比例次级组含量
$ f( G2 P; q1 I) g8 bDistribution free, 分布无关性/免分布2 e. I" O8 }$ V: f
Distribution shape, 分布形状
+ i9 g* Y) M' u- e$ u6 \4 FDistribution-free method, 任意分布法& m7 B4 z9 J5 q# N- Y) Q2 \
Distributive laws, 分配律
9 ^! p! g& ]+ V: aDisturbance, 随机扰动项
: ~2 B S* P6 @ u* @8 IDose response curve, 剂量反应曲线
, j. J/ X+ R' Q. TDouble blind method, 双盲法6 j7 R% k- N" b3 |) U$ j
Double blind trial, 双盲试验
: x' t/ F$ R7 W! y% fDouble exponential distribution, 双指数分布
; C) o. r2 ]' \' e; ^Double logarithmic, 双对数) [( S! j/ W! t) Y
Downward rank, 降秩& N# d1 f1 R+ @3 O% [3 i0 `! m
Dual-space plot, 对偶空间图
: y3 o6 p3 @+ H4 f8 ^& bDUD, 无导数方法
2 F3 m) U1 ?% C! b0 J4 F) SDuncan's new multiple range method, 新复极差法/Duncan新法6 `% p T* |; A. @
Effect, 实验效应
# @2 o, E. u: MEigenvalue, 特征值8 W2 V5 F* C, }; U( R
Eigenvector, 特征向量' ?8 p0 }7 G$ v) n/ Z
Ellipse, 椭圆
8 B; q* X# Y% FEmpirical distribution, 经验分布
- {! V. n* ^- l- Y3 @! W2 GEmpirical probability, 经验概率单位
& Z0 |# ]6 z) ^7 T! U% WEnumeration data, 计数资料1 x9 j) S! [ x9 d
Equal sun-class number, 相等次级组含量- y; y. w: G: ?' B8 h# T; Q& c. f
Equally likely, 等可能0 ]3 }4 V3 t h1 G
Equivariance, 同变性9 m' G. I; _6 r1 ]6 I& g
Error, 误差/错误- W$ Z4 c6 ^+ t
Error of estimate, 估计误差' X* P: j' Z2 y4 c, ^
Error type I, 第一类错误( U S# Y4 z! U( T1 d9 g
Error type II, 第二类错误
6 R$ H0 x! j/ tEstimand, 被估量
0 Z* y# g. c# H2 D2 sEstimated error mean squares, 估计误差均方
) a% i9 m. o/ y7 CEstimated error sum of squares, 估计误差平方和
# @$ g8 H/ _9 |1 h6 z7 m( AEuclidean distance, 欧式距离; v, i( P' @! ^) H8 F- Z
Event, 事件
! O& k1 p8 k3 f; J7 oEvent, 事件
& G6 j) w' U) ?( DExceptional data point, 异常数据点
- T2 @ S/ T& V# V1 AExpectation plane, 期望平面
2 [1 d1 m9 P8 W# Y1 J" K. qExpectation surface, 期望曲面$ ?: e* N8 o8 \. @% }8 I0 p* Q& O
Expected values, 期望值
. j5 D* a3 S; f. k. @9 nExperiment, 实验
9 K1 X5 B+ l. t( f. `2 Q# NExperimental sampling, 试验抽样
2 L+ U: k3 }8 \! R6 [: z- TExperimental unit, 试验单位9 w& h9 ~5 ^$ a* R6 T' ?
Explanatory variable, 说明变量$ x- X( f: k% x4 A9 N: I
Exploratory data analysis, 探索性数据分析+ X6 s8 o4 i# w# p9 n9 y
Explore Summarize, 探索-摘要
; V$ u9 t! x, W JExponential curve, 指数曲线& c, A3 Y' f% |- ~' M5 J$ A) v7 K3 v' J
Exponential growth, 指数式增长
7 g( g/ C' A. w& L4 r+ IEXSMOOTH, 指数平滑方法
7 t" U3 u. J4 U) u& ^Extended fit, 扩充拟合# d+ N% ?6 n Y, H& _9 b U6 p* L _
Extra parameter, 附加参数1 O) k6 Y. p, y5 L+ [5 U) _! f
Extrapolation, 外推法; R2 Q" h- @7 S2 d7 M
Extreme observation, 末端观测值3 i- x: `- m8 T# G% q# X9 S2 [
Extremes, 极端值/极值0 S b$ f5 H6 r; W6 X% a
F distribution, F分布
* `: F0 l4 Z: _F test, F检验$ e& v7 z/ R# K
Factor, 因素/因子! n+ }# z8 U) Y* k
Factor analysis, 因子分析
6 S4 { R& l& E7 T. o- bFactor Analysis, 因子分析# \$ n* e* ?% G* d, B$ U$ [: I
Factor score, 因子得分 4 _8 X0 \9 `9 I+ O5 Q6 s: T
Factorial, 阶乘& n; s3 ?0 g. Z8 K- a
Factorial design, 析因试验设计
) p! Z0 w9 i9 Q. ]$ }8 KFalse negative, 假阴性 f1 q' e6 `+ s( j. b0 x
False negative error, 假阴性错误6 ]+ f) D: I1 E/ A$ ]8 O
Family of distributions, 分布族" N! U: j) r+ D8 n( d V
Family of estimators, 估计量族
8 W) Q, |8 `! s% y/ @Fanning, 扇面
. U! e3 h3 N& v( d3 \3 yFatality rate, 病死率
) w* E" e: o# bField investigation, 现场调查 I H% O1 w; [/ D, ~
Field survey, 现场调查
+ K( b! U6 { IFinite population, 有限总体 |, w. z4 \1 x; t& h
Finite-sample, 有限样本
: N' x$ Y* Q3 }6 Y% H+ g$ BFirst derivative, 一阶导数% ~; I$ I8 `. U" f0 B
First principal component, 第一主成分7 x4 g* j) ?( x4 B
First quartile, 第一四分位数. h4 y4 d" P: n& J/ I* C6 v @
Fisher information, 费雪信息量( V+ t& H( B _7 y; B
Fitted value, 拟合值
& d8 R. Q3 S$ ^9 z+ WFitting a curve, 曲线拟合/ w( G( P* q$ m9 U' E2 }3 P; D
Fixed base, 定基
2 u& [ l( T5 a# k3 R# _0 IFluctuation, 随机起伏0 e( A5 q8 R' Y+ N* T* i
Forecast, 预测
# ~5 s/ z T( m/ K4 d' L; Y! W! F! zFour fold table, 四格表
* i3 r9 a/ S0 S# z0 QFourth, 四分点
; `: p- ]) y% K" uFraction blow, 左侧比率7 m' ~. o( r* _# `! G& s
Fractional error, 相对误差
+ q. I5 Y7 f( d0 dFrequency, 频率; R6 z. a r; A* q4 m" X. a @
Frequency polygon, 频数多边图+ J! a" Q' A8 I
Frontier point, 界限点
$ d) p' t% P7 f* V( d1 TFunction relationship, 泛函关系4 f/ L" l+ {5 D; O. ^7 r$ M0 U
Gamma distribution, 伽玛分布
8 Z( f5 s. m+ K/ a- [% v9 r/ GGauss increment, 高斯增量
3 n9 T- l- z3 _, xGaussian distribution, 高斯分布/正态分布$ ]9 k8 Z" ?5 H4 |: r9 {: S: w0 j
Gauss-Newton increment, 高斯-牛顿增量
( L5 U* }- {4 D5 o5 ^General census, 全面普查, V6 v( f3 p# Q; [
GENLOG (Generalized liner models), 广义线性模型
$ u" ~9 H& I8 R5 z: a( ZGeometric mean, 几何平均数8 F4 `5 K! D7 q) X* e
Gini's mean difference, 基尼均差
$ ~/ o" ?/ s: GGLM (General liner models), 一般线性模型 5 R" T( B' _7 |5 I' F
Goodness of fit, 拟和优度/配合度
% b& S. a3 t D4 g; h mGradient of determinant, 行列式的梯度! O4 c( @. i( ^
Graeco-Latin square, 希腊拉丁方
1 k- O" C/ P( m" U" E1 EGrand mean, 总均值
8 G3 C$ D9 W) U! C' i/ b( n2 e/ QGross errors, 重大错误
* w* C' }. C8 ?8 R) ?6 ZGross-error sensitivity, 大错敏感度* N; x- {2 u& B" x2 y
Group averages, 分组平均' y! E p3 R" H! d* K+ k: j. N' j# \
Grouped data, 分组资料2 I d5 E) `% @* Z W! z' C! a1 S
Guessed mean, 假定平均数
$ X& |6 ^ `8 f4 k+ J* E/ oHalf-life, 半衰期; o0 V4 z* g0 Z8 b4 k
Hampel M-estimators, 汉佩尔M估计量
8 J3 J4 {7 A; VHappenstance, 偶然事件( m; k7 K3 j* y6 ?# s
Harmonic mean, 调和均数! a3 e1 F6 b8 N3 X o; g) w
Hazard function, 风险均数
. Q1 U* W9 P0 [5 i5 Q# ]/ UHazard rate, 风险率0 Z+ _7 @, k; {9 y
Heading, 标目
+ @# z$ j' s4 ]% l4 T; ZHeavy-tailed distribution, 重尾分布$ t7 X/ u, I/ S3 {4 C
Hessian array, 海森立体阵' V$ R8 l' }6 v8 A! s& F
Heterogeneity, 不同质- E9 V. T( b# H' @- e* i7 l
Heterogeneity of variance, 方差不齐 $ k- @6 ` \" ^% E; i
Hierarchical classification, 组内分组
' Y Z% f2 S; D* @- H( BHierarchical clustering method, 系统聚类法
! w! T6 U4 d1 ]) NHigh-leverage point, 高杠杆率点8 x3 i+ o4 {# B$ D5 [! a
HILOGLINEAR, 多维列联表的层次对数线性模型- b( _7 c1 R% m- ~
Hinge, 折叶点# h ]! ]0 w: u1 U ~. b8 h6 c9 v
Histogram, 直方图
- t8 E" T U0 ^. t6 p2 LHistorical cohort study, 历史性队列研究
! W: ?8 S9 C& p% BHoles, 空洞
2 a5 b% ^ e3 G6 Y5 HHOMALS, 多重响应分析
, o" a2 D7 d- R6 g3 w+ U9 kHomogeneity of variance, 方差齐性
' _: `; J9 l+ \; ~Homogeneity test, 齐性检验1 y% I" B( N: K2 F$ s, U6 N: O
Huber M-estimators, 休伯M估计量2 c3 t* n n: v/ I3 y0 _2 D
Hyperbola, 双曲线5 Y$ R, Q2 G+ c+ k
Hypothesis testing, 假设检验: p6 i" [! Y' C+ K/ v! Q
Hypothetical universe, 假设总体9 Z! L, a( b& ~, ~$ w" V
Impossible event, 不可能事件
7 T. y; h1 P* S/ g0 L5 e- N6 @- LIndependence, 独立性
. \6 s" Y( s3 y+ Y4 L0 {! g9 EIndependent variable, 自变量
! w- u% {/ v7 _( M+ I: `Index, 指标/指数$ }# }& x3 s# r. E0 l% w3 T, D
Indirect standardization, 间接标准化法
2 o. S+ X- @6 b" r+ n9 UIndividual, 个体% Y6 v/ w7 Z$ j% @" Z+ S+ q
Inference band, 推断带' N3 o/ l- T k; G8 x2 f
Infinite population, 无限总体
- w3 X" o4 h" n VInfinitely great, 无穷大
3 U' h, ]" U; p3 V& ~6 |Infinitely small, 无穷小
4 P$ m' k2 W8 m; LInfluence curve, 影响曲线
4 z' j j% r& N- tInformation capacity, 信息容量
4 U7 @/ U7 j% eInitial condition, 初始条件
' k9 C8 ]* J+ A0 a! \Initial estimate, 初始估计值1 {1 ?: o7 p! q5 l
Initial level, 最初水平
$ h* A& U* s7 [ \1 C4 bInteraction, 交互作用
6 F6 h# S4 K0 G% V; b4 [Interaction terms, 交互作用项: n% Q: Q0 x8 ]3 P& O
Intercept, 截距1 Y) R& o* X. T. N2 ]/ V
Interpolation, 内插法% P C6 Z0 F( L5 m
Interquartile range, 四分位距
) C0 e3 c6 E6 t, uInterval estimation, 区间估计
8 ]" D7 {1 \$ Z2 ]4 eIntervals of equal probability, 等概率区间1 V& B3 N: k+ r' a& o' ?
Intrinsic curvature, 固有曲率% [9 {2 i( x( y! B: x
Invariance, 不变性
' S9 u' Z" x0 w: r5 qInverse matrix, 逆矩阵2 q2 D9 E. h2 Z, w6 g# {
Inverse probability, 逆概率4 |7 C. B7 S- y
Inverse sine transformation, 反正弦变换, F7 ~8 b$ f3 T S8 A1 B" p' C
Iteration, 迭代 ' \; q1 o( n9 x% T9 O) X4 L" A8 B& G
Jacobian determinant, 雅可比行列式6 _' i* G4 }0 W0 Y" t o" _) w- N
Joint distribution function, 分布函数
0 e6 M2 E. g; Y' J, eJoint probability, 联合概率+ I3 ^9 F# X4 r& m1 s% i
Joint probability distribution, 联合概率分布' D- _9 D* q; R1 v& {3 C B9 y
K means method, 逐步聚类法
l. H6 D, G, a9 j! @ D+ V/ G9 XKaplan-Meier, 评估事件的时间长度 , B$ o. Z7 u1 @8 ^% p0 |
Kaplan-Merier chart, Kaplan-Merier图
9 D, h1 m- |: m* t" h' A9 L$ X1 [+ iKendall's rank correlation, Kendall等级相关- E! Y5 u* A* G4 B# j/ w& d
Kinetic, 动力学. O. N( F" P0 H" Z, R5 ~# ^
Kolmogorov-Smirnove test, 柯尔莫哥洛夫-斯米尔诺夫检验* N1 ?: r3 a# |' H7 H. b
Kruskal and Wallis test, Kruskal及Wallis检验/多样本的秩和检验/H检验
" w( j6 C. S8 v- G6 v0 K _) | `Kurtosis, 峰度. Z6 a8 o* @6 M" E7 i, i
Lack of fit, 失拟
, a4 w: A( c1 E2 ^% C. | p% F! gLadder of powers, 幂阶梯8 H, A% t, |: @( X5 s* K
Lag, 滞后0 ~* b+ u1 Q6 L* C
Large sample, 大样本
% L, z$ t! |9 a2 S. S( Z% ?1 w- N3 RLarge sample test, 大样本检验1 P# P3 j- C9 P6 k8 l7 i {, [$ l
Latin square, 拉丁方& N# O4 E3 x4 a7 ~ \. M$ q
Latin square design, 拉丁方设计# V/ S/ W4 w7 _1 ~; f! x
Leakage, 泄漏
7 W. Y7 C* n F1 {Least favorable configuration, 最不利构形
3 d5 i4 c* A# E7 H, G4 a* {# ~Least favorable distribution, 最不利分布
7 q' V/ w* H# eLeast significant difference, 最小显著差法
( D# [. l0 u* X2 wLeast square method, 最小二乘法
2 A F) y# T; ~' ^5 s, Y) m+ P. sLeast-absolute-residuals estimates, 最小绝对残差估计
' T9 x+ f4 K, R& ]' FLeast-absolute-residuals fit, 最小绝对残差拟合
* G9 l d/ D$ r' {- `% kLeast-absolute-residuals line, 最小绝对残差线1 E, ?4 x+ [: u* B/ ~, \& n; l- M
Legend, 图例# T# q2 ]+ _* p, J
L-estimator, L估计量
- \* R4 ]' Y& s7 \. s' [L-estimator of location, 位置L估计量1 j- y& s0 r# [- W9 v/ g1 X
L-estimator of scale, 尺度L估计量. S$ ^5 \ X& I7 a5 T2 R6 b
Level, 水平' O! @4 L( n" b* |# _
Life expectance, 预期期望寿命
' ~/ y4 K7 t1 s. q$ V' HLife table, 寿命表
5 `! ~9 h, o+ s. g% b* {Life table method, 生命表法/ w: ^# z1 }, F
Light-tailed distribution, 轻尾分布( i. O( c/ S a }; t0 ^
Likelihood function, 似然函数
) l* U1 D& J$ W5 D$ y( f0 tLikelihood ratio, 似然比# V9 W/ C+ P4 H* e
line graph, 线图
Z, ^; \6 r5 ~* ^Linear correlation, 直线相关7 m8 B2 [* g9 Y1 v" b( Y( n6 e2 B
Linear equation, 线性方程
5 r# r1 y: `2 O( \Linear programming, 线性规划! [ i( E0 ?$ B
Linear regression, 直线回归, N9 d0 t% |0 y* g$ \) V
Linear Regression, 线性回归
$ W9 W' [* j& {/ h% U. N: }Linear trend, 线性趋势
* }5 U4 N0 D4 z. d2 y. Y: JLoading, 载荷 4 [3 k2 B5 J+ w1 q% N
Location and scale equivariance, 位置尺度同变性
+ V& ^# R% `. F Z5 v6 ]! ^! E7 l8 jLocation equivariance, 位置同变性
; O4 H7 l* ?1 b/ iLocation invariance, 位置不变性
z( n- W1 q8 w3 P+ s1 k5 W) eLocation scale family, 位置尺度族
0 W0 n( r& Z9 e$ ?0 a, mLog rank test, 时序检验
6 g( o& H7 R) B( O7 t$ _( T" KLogarithmic curve, 对数曲线
, i. d* L# T5 _& sLogarithmic normal distribution, 对数正态分布
, s, b/ {) V9 E% x: O0 F' T1 qLogarithmic scale, 对数尺度) R, P5 I) k" ` l$ ]
Logarithmic transformation, 对数变换
9 i0 h: [7 R" lLogic check, 逻辑检查
3 G/ ?4 J2 R. i1 t+ r3 _! YLogistic distribution, 逻辑斯特分布
. q* @3 M& s+ d. G1 x0 n- C0 zLogit transformation, Logit转换% b' E& w, d: w0 R. F' B9 D7 S! a
LOGLINEAR, 多维列联表通用模型 + k! E# I% E1 s# k
Lognormal distribution, 对数正态分布
( `1 S* Y. e- f- q' fLost function, 损失函数
! R/ \' W9 ^4 ]( \4 R! RLow correlation, 低度相关
, ~: m" y* P; vLower limit, 下限
9 p6 y$ P, M( N% ~: ILowest-attained variance, 最小可达方差, E5 i* r4 p$ ^) |2 R
LSD, 最小显著差法的简称
! s5 R( L) r3 m) A# n. v9 JLurking variable, 潜在变量" x* |3 M( P, L
Main effect, 主效应$ ^: z, `9 S, T, t- a- ^2 X* W
Major heading, 主辞标目
' c; Y% U7 s9 ^, L+ JMarginal density function, 边缘密度函数
6 H, J1 _% s3 y, c/ hMarginal probability, 边缘概率7 P( ^ ]! S8 x& Y4 {' \* J
Marginal probability distribution, 边缘概率分布
+ E8 a; {+ X) c! U9 c. I" ^Matched data, 配对资料' x8 E; }+ ? L& {! Q1 O. F
Matched distribution, 匹配过分布, ?! m. E4 v7 h" |/ Q
Matching of distribution, 分布的匹配7 A5 _* W! L1 n A0 l* A: b5 V
Matching of transformation, 变换的匹配
- Y/ ]7 D! N: o/ B' D4 Y1 K0 v* xMathematical expectation, 数学期望- W' o; ^$ L+ c& l# p
Mathematical model, 数学模型 _+ `& [( ^9 H4 k" a+ R
Maximum L-estimator, 极大极小L 估计量
4 \1 f! M$ R# r VMaximum likelihood method, 最大似然法+ @, e, P" n. @- r% t
Mean, 均数' L7 }: p$ U$ X/ B1 z9 Z, T K
Mean squares between groups, 组间均方' E1 F! E: r; W6 Y2 Q
Mean squares within group, 组内均方2 t# G% m: ~. x) b* L6 U' \2 h$ c
Means (Compare means), 均值-均值比较) n) y/ y' S- G( f" {: F
Median, 中位数' J: X# Q& x* w+ b9 M3 i% V$ p
Median effective dose, 半数效量( u w' G- L. L' q
Median lethal dose, 半数致死量* }3 j# R6 h/ z* T9 J1 b
Median polish, 中位数平滑- I2 U; F+ V& g8 H# E( V7 P T
Median test, 中位数检验
/ x/ ?7 K' o/ t2 u0 ^ L# Q9 yMinimal sufficient statistic, 最小充分统计量' F2 o3 J' h* \; v& }/ m
Minimum distance estimation, 最小距离估计# ?0 X( b, N( z: ], N7 \- G: ?
Minimum effective dose, 最小有效量$ [, p# L: [) E: H; N$ j3 u
Minimum lethal dose, 最小致死量, ^* h( o3 t$ r5 d# G
Minimum variance estimator, 最小方差估计量
. }2 T& ?% J4 Z! g9 ?7 ?# NMINITAB, 统计软件包
! B! x, f7 c3 Q- V1 M8 wMinor heading, 宾词标目
) j; W9 |1 l% g( UMissing data, 缺失值: a1 h) g+ H9 W: i) M9 a2 i, l
Model specification, 模型的确定) ~* I; b1 W4 \! |9 d4 g4 {
Modeling Statistics , 模型统计8 \& t: |# H4 n F2 `
Models for outliers, 离群值模型: t7 z" _: v3 j3 ~7 X
Modifying the model, 模型的修正
5 ]" S" p8 G' l2 VModulus of continuity, 连续性模( F6 u- r- y, G+ X/ b C
Morbidity, 发病率
) b. j/ V! N0 X" T% V6 L- `9 [: i7 YMost favorable configuration, 最有利构形
( e4 ~' \8 r! T' ]+ k8 xMultidimensional Scaling (ASCAL), 多维尺度/多维标度7 F; S) F: L* s o- K( U
Multinomial Logistic Regression , 多项逻辑斯蒂回归% L9 {/ l) z$ K4 m+ r i
Multiple comparison, 多重比较8 m+ d' t/ O' b2 X$ ~
Multiple correlation , 复相关) K0 A$ G7 }, o, e7 m( Z5 o& y
Multiple covariance, 多元协方差
( S, f& H0 E$ ]% I9 CMultiple linear regression, 多元线性回归
. _( f6 }! \# ?0 W8 w" L$ ]: g dMultiple response , 多重选项
+ E$ W1 I8 ]( H. mMultiple solutions, 多解
" @! r: r* e+ C6 q3 j! q/ sMultiplication theorem, 乘法定理/ C" Q8 x7 Y8 a% J- n
Multiresponse, 多元响应
5 [/ u7 t( ]& C" {Multi-stage sampling, 多阶段抽样
: M0 _+ s) F0 T/ I! L/ ZMultivariate T distribution, 多元T分布
5 y$ m; O) M* Z1 j& }8 C% hMutual exclusive, 互不相容2 f% M5 D+ U F* t9 e
Mutual independence, 互相独立' M4 M( P9 ~ ?1 e8 J: }
Natural boundary, 自然边界. A. F- [- Q5 L: m3 {5 ]- g3 U2 W u1 d
Natural dead, 自然死亡9 R& f3 b, b/ M; l* t
Natural zero, 自然零
' E. U- t8 G& {7 c) `Negative correlation, 负相关
2 d. x$ w9 Z" m$ l6 o: iNegative linear correlation, 负线性相关/ G% R+ Y: M8 |0 g n
Negatively skewed, 负偏
" Y! R6 h, K% p7 k& w0 C* bNewman-Keuls method, q检验5 D( {8 g1 e1 N; X0 ?1 `
NK method, q检验
5 ~3 ~0 ?& w! V/ c% I$ `& rNo statistical significance, 无统计意义
8 ^; c* k' R+ s2 V8 T5 ]9 H/ qNominal variable, 名义变量: v7 r3 @) Q# r- L c) [
Nonconstancy of variability, 变异的非定常性
) \; p' C: R, N- L3 G9 ^Nonlinear regression, 非线性相关
- ~ r% d, k# a- yNonparametric statistics, 非参数统计
$ f# `' _9 R" X. T0 J* r7 ONonparametric test, 非参数检验! q% z* Z% R9 I* h; v5 e# L
Nonparametric tests, 非参数检验 B, S7 e9 E. I0 ^
Normal deviate, 正态离差
R9 B; ]% I8 c0 O2 @+ \, }) {Normal distribution, 正态分布2 e+ h w5 h6 G
Normal equation, 正规方程组* }- M! w0 A6 Q; k/ x
Normal ranges, 正常范围
6 k: M l0 o, x% ONormal value, 正常值
, T/ R' y. Y2 X8 X9 |5 e5 XNuisance parameter, 多余参数/讨厌参数
9 g9 P- }- Z- x' oNull hypothesis, 无效假设
. R, {: E6 k7 u$ I# ~Numerical variable, 数值变量- u; Z" c3 l' i: _' @9 @
Objective function, 目标函数
" }$ |, s/ {1 m5 V3 C- y. jObservation unit, 观察单位
' z; w: e1 R* D6 nObserved value, 观察值& \( o# _7 e) H3 V
One sided test, 单侧检验
3 B" G9 E" |7 J @4 zOne-way analysis of variance, 单因素方差分析! C& [* l8 p9 d% R( O" G. @
Oneway ANOVA , 单因素方差分析+ B& ^( O7 {0 N/ z
Open sequential trial, 开放型序贯设计
5 n$ w% d0 J0 s1 S6 D7 OOptrim, 优切尾% e b0 [7 O& i" D2 J' ~" d
Optrim efficiency, 优切尾效率& {6 m0 B2 w' d% Q# ?' y
Order statistics, 顺序统计量
3 z. f. N& I8 B) A( j) `; j8 vOrdered categories, 有序分类
4 H5 |4 ~! r) V2 a2 T i- Q$ {5 VOrdinal logistic regression , 序数逻辑斯蒂回归& N! t* \! H! I# O( C! I3 R& E; r
Ordinal variable, 有序变量
1 f* r9 l4 L4 Q* i% _6 H, e ROrthogonal basis, 正交基 @0 X) ?% b, t! _) B, P
Orthogonal design, 正交试验设计
& k/ O5 ?; m; b4 `) X4 [+ ^; [Orthogonality conditions, 正交条件7 _5 @" P& x+ M/ A' z$ P
ORTHOPLAN, 正交设计
( Q0 ?8 T( ] q, q" w: {3 ~Outlier cutoffs, 离群值截断点' O/ o* b/ @' c$ q
Outliers, 极端值
2 H( d0 q# ~! fOVERALS , 多组变量的非线性正规相关 1 S; J, }, |) W. |
Overshoot, 迭代过度
$ n; B) S+ ~6 s0 O" X3 @Paired design, 配对设计! A" B6 s F) r- z
Paired sample, 配对样本) b* r1 A! R* ]- Y
Pairwise slopes, 成对斜率
: ~: o' g! q' Z% E" GParabola, 抛物线
! j& S! k+ }2 _" A! dParallel tests, 平行试验
1 _& O# X6 B6 T, n4 wParameter, 参数
: L+ V9 k2 E! V+ r. @- `Parametric statistics, 参数统计& P0 o9 {+ b% f. [
Parametric test, 参数检验
2 i5 x: s$ Y% `9 J5 rPartial correlation, 偏相关
( L# ~5 ]9 `0 }& A9 WPartial regression, 偏回归! v+ w$ k# a8 l
Partial sorting, 偏排序- c3 j$ @8 C+ E% T0 B8 Q
Partials residuals, 偏残差
% g. K; i$ |) u: N* A2 j0 ~Pattern, 模式% U/ C* J+ U' d0 z/ ~
Pearson curves, 皮尔逊曲线
& K, C" }; e5 d9 R+ JPeeling, 退层4 }2 ?9 u. F- x# c: a6 ?3 L
Percent bar graph, 百分条形图
F# m& ? N3 N9 Q& yPercentage, 百分比
) d! E, S8 V4 {Percentile, 百分位数
* p; T- ~0 s9 o( F$ xPercentile curves, 百分位曲线
) V% m7 E4 ]& I) BPeriodicity, 周期性
1 R6 e$ A! ]" z4 D( t( [' r5 JPermutation, 排列
" d; N2 k3 ]8 {P-estimator, P估计量
' ]7 ]" c9 B x. h4 k" _Pie graph, 饼图
; }- S$ O5 c' M0 y0 c( i, o' r9 MPitman estimator, 皮特曼估计量
4 q3 p$ C# U8 MPivot, 枢轴量) K% i% S/ W: B& D3 ~- }
Planar, 平坦/ A4 [; e A$ i0 g. \- V4 O
Planar assumption, 平面的假设
5 n0 E; s: M! m6 t* ^PLANCARDS, 生成试验的计划卡9 X n% o' U, J
Point estimation, 点估计
% y9 ^) P, ^# r4 @# EPoisson distribution, 泊松分布3 a8 h! e* `! C8 u3 L+ {
Polishing, 平滑9 N6 y3 U0 M+ C! {
Polled standard deviation, 合并标准差
/ _9 b. U0 g- [% SPolled variance, 合并方差
- W- C( h5 R+ e3 ^0 i* J. O2 S7 GPolygon, 多边图
5 a. V( o: J9 z! G6 p/ K+ \4 GPolynomial, 多项式
0 ? d3 m5 g7 @# d! r. ^Polynomial curve, 多项式曲线5 i+ G: n/ `/ O+ w, u
Population, 总体
. ^! F- u& V/ j( f; O' k# A: c# CPopulation attributable risk, 人群归因危险度
- K, }( [$ E m8 e! L* ?/ g. PPositive correlation, 正相关
g5 `9 m( ]) T& v4 Q7 |1 _# N* i5 ?Positively skewed, 正偏
" e2 V2 M, g. x( B ZPosterior distribution, 后验分布
1 g9 }5 d8 Y: [' g9 ~0 G7 ePower of a test, 检验效能
# {! V Y1 m/ W; z1 FPrecision, 精密度4 W0 \$ \& Z- d, a7 ], R6 q
Predicted value, 预测值! y- G/ i% O0 E. t
Preliminary analysis, 预备性分析
& W/ d5 s+ K5 I; P: u* Z/ IPrincipal component analysis, 主成分分析
) \/ d j7 S& bPrior distribution, 先验分布8 X6 g9 O2 M; m( Q6 B" e, z
Prior probability, 先验概率
, \" B" H. R/ x" e7 v! |Probabilistic model, 概率模型
: S; f/ k$ R/ q7 o( T6 g* vprobability, 概率
% ?; B+ y' z. X+ ]Probability density, 概率密度
; t* S1 Y J" HProduct moment, 乘积矩/协方差. |6 \- [" x. Y0 e7 q. P
Profile trace, 截面迹图
' c" ?8 |0 Y, ~/ \+ E( s8 pProportion, 比/构成比8 t, n" a7 I! L! [" s0 G) e) A
Proportion allocation in stratified random sampling, 按比例分层随机抽样
8 S3 t) m! Y4 a" z' D, C2 c) zProportionate, 成比例! i' O& P4 ?: P; _1 e
Proportionate sub-class numbers, 成比例次级组含量
# k) o. g3 e7 d9 _# ?- k" d0 y4 FProspective study, 前瞻性调查
8 {$ @6 M/ `0 q- oProximities, 亲近性
0 n: Z& O/ s% i4 `Pseudo F test, 近似F检验/ o9 A ?) v, c/ l' x
Pseudo model, 近似模型
2 p/ T6 X1 f$ e' L& Z: j* b% JPseudosigma, 伪标准差
& B3 B. q q% V% f. dPurposive sampling, 有目的抽样
. o6 U( T) f( n4 OQR decomposition, QR分解
- O0 i% u D8 F# h: CQuadratic approximation, 二次近似
' u$ i1 G8 E: fQualitative classification, 属性分类
9 @' J; { ?- u3 C3 U3 LQualitative method, 定性方法
_, V, V6 r/ I8 w- [Quantile-quantile plot, 分位数-分位数图/Q-Q图, Z" R+ i1 ~% E( h
Quantitative analysis, 定量分析, ?- k, ^% A8 h( p% I) P4 I) N' A1 n
Quartile, 四分位数$ o; c+ x4 V6 j( y G" e; \! B' V4 Q
Quick Cluster, 快速聚类8 v w& Z* G: |6 T$ z1 y* B
Radix sort, 基数排序8 a7 k& T: }- i& B- [
Random allocation, 随机化分组
- R2 p/ d5 d+ ]+ B; ORandom blocks design, 随机区组设计3 V0 g/ J7 W5 G, C; u+ l E* d
Random event, 随机事件9 E! ?; ^( R6 E' }4 C0 J
Randomization, 随机化: |, }( D3 S' m- F# m" N
Range, 极差/全距5 L, `$ t0 N1 M" a
Rank correlation, 等级相关% s8 y2 E1 B, ? o
Rank sum test, 秩和检验, z- T1 K7 V1 O: y3 e- s
Rank test, 秩检验
4 w) P1 b5 x7 P5 f1 V- F7 D2 g5 Y8 CRanked data, 等级资料3 [' j/ a* l! d5 v) z
Rate, 比率7 q( e8 }7 ^+ W+ ?! S& L
Ratio, 比例
0 l+ F6 W' S0 i3 D' ORaw data, 原始资料$ V& s- Q+ N" B& C
Raw residual, 原始残差: Y6 k; R% o' y! p) P3 W
Rayleigh's test, 雷氏检验, f$ Q! |# J( F( s$ m* t
Rayleigh's Z, 雷氏Z值
9 C- V( a" ]) k8 [! g# u9 oReciprocal, 倒数
3 z/ H) K: U6 c4 t) ^Reciprocal transformation, 倒数变换
+ u& X5 n ~' A- z) ^Recording, 记录1 I% ~6 d0 r9 I) z
Redescending estimators, 回降估计量
" Q* C7 B4 f% EReducing dimensions, 降维4 T2 N: ]+ K/ o8 H$ f: K
Re-expression, 重新表达$ ?* i" P' v) H" ^4 E% E! X; g
Reference set, 标准组. w1 X9 x4 j* O! k; i8 g- T4 G* d, P
Region of acceptance, 接受域, z( w9 N4 I$ g% @& F) @
Regression coefficient, 回归系数
% x0 ~$ w5 G# {Regression sum of square, 回归平方和# F: c& n- g8 U3 b- @ Q0 z
Rejection point, 拒绝点2 `- n# @! K8 z o0 ~
Relative dispersion, 相对离散度
3 W4 ~, Y8 l6 [4 l" FRelative number, 相对数" s, v) ~3 s% P, X/ f( V/ k6 o* o
Reliability, 可靠性$ e3 @( J6 _. ^( K3 \2 |
Reparametrization, 重新设置参数% H! N$ C, O7 N( }! i
Replication, 重复
& M+ k% u( ]2 _, UReport Summaries, 报告摘要* l3 W9 y# V, j
Residual sum of square, 剩余平方和& E. W7 z9 x1 P, c+ J; ~
Resistance, 耐抗性7 ^3 X' s) J3 q
Resistant line, 耐抗线
; G Y" Q" c$ t& N0 ]9 g4 @: f( P2 oResistant technique, 耐抗技术+ h0 n$ }! d; g( V
R-estimator of location, 位置R估计量
" u& Q& g/ D) @2 dR-estimator of scale, 尺度R估计量
( ^) {' _" ?. ]Retrospective study, 回顾性调查5 L. V n$ x3 d }4 |
Ridge trace, 岭迹0 Q# X3 l: ], Q
Ridit analysis, Ridit分析
% X5 s3 A/ F2 Z2 |9 c$ ~Rotation, 旋转
/ d" l. Z' d e. XRounding, 舍入
$ ?- o7 R+ O# D: J0 u' K: jRow, 行
! z' j c& ^& |+ C/ DRow effects, 行效应5 y3 w5 P# k% @( d
Row factor, 行因素4 R, }0 E c: t# n7 z
RXC table, RXC表
0 j. y+ o9 N2 p+ l- p* @5 ISample, 样本- k4 s: J) ^' {" S$ d" i& F: t
Sample regression coefficient, 样本回归系数! g+ j& [, l" Z" ?1 r5 M# P+ _
Sample size, 样本量" {7 D5 d# ^) v
Sample standard deviation, 样本标准差: l' [9 `8 K+ B
Sampling error, 抽样误差/ i$ n/ B7 d0 [& ] e6 y
SAS(Statistical analysis system ), SAS统计软件包' T' I+ X% @' n. m7 P9 }2 I5 m6 \9 B& b
Scale, 尺度/量表
$ E( Y$ g" q9 u% P/ \! ^% aScatter diagram, 散点图
% i. L3 F+ i uSchematic plot, 示意图/简图
5 @3 w( ?3 j6 f+ ]7 w$ F$ U7 W% MScore test, 计分检验
9 t9 ^' @( D% c) }- p- Z$ L2 oScreening, 筛检
$ q7 |" T& |& s' R: H8 HSEASON, 季节分析 7 e" x2 a: Y2 V: n b' k
Second derivative, 二阶导数" i. V% H( Y: L c
Second principal component, 第二主成分
R, c# a8 ~5 j) _SEM (Structural equation modeling), 结构化方程模型 # E, D1 Q$ a' J4 a& y9 Y* b
Semi-logarithmic graph, 半对数图" p9 {- c% a7 m: D6 H( r5 K# p
Semi-logarithmic paper, 半对数格纸4 [+ _: i9 x- M2 R( ~. P2 e
Sensitivity curve, 敏感度曲线# d, D( J& X, S* L5 R7 k& n
Sequential analysis, 贯序分析& |, c7 q4 J6 j+ P$ V% b4 ~$ f
Sequential data set, 顺序数据集
- B. \2 R; c5 b! NSequential design, 贯序设计
6 L4 r4 R9 k) F1 {: ]Sequential method, 贯序法
; D) z6 _, Y; {% |! O+ pSequential test, 贯序检验法
) S; b; X/ H1 h" N% fSerial tests, 系列试验
4 r8 L9 y7 k( ]/ m' `. T4 f6 yShort-cut method, 简捷法
+ f5 @6 q5 p2 ~/ E1 I8 ?: rSigmoid curve, S形曲线
6 L0 W0 Z$ g5 e/ ^- q! ?4 _$ ?5 h7 c! uSign function, 正负号函数: K+ B) @% j% F/ ~" v% k& s
Sign test, 符号检验
0 E! L# K8 U7 k" D5 S& CSigned rank, 符号秩
/ D# A: m4 W2 B* \' r/ N" y' G; DSignificance test, 显著性检验: l9 u6 i. u# }$ Y$ {
Significant figure, 有效数字1 D9 }$ U( s1 H4 G. j
Simple cluster sampling, 简单整群抽样
) ^2 S: A+ P' h7 ESimple correlation, 简单相关0 a$ N* s: ?+ a+ [ Y& t1 s
Simple random sampling, 简单随机抽样% I6 C* G7 S' e+ L8 J9 P$ S$ l5 k
Simple regression, 简单回归
; Q, C6 V( v3 [- X/ b, Ksimple table, 简单表
8 b, |; B! O4 K- F1 j5 cSine estimator, 正弦估计量
/ ^ }/ X7 z- p; |. GSingle-valued estimate, 单值估计$ |: D9 S% P3 X& ?5 y" {
Singular matrix, 奇异矩阵
% N" C) Q$ Z- u; QSkewed distribution, 偏斜分布
* V! f6 i; j2 a8 b: x( U! M: s. BSkewness, 偏度
) X& j/ K. w0 }2 Y" L- T- ]& u. CSlash distribution, 斜线分布
& ]" ^+ e ^4 f' B4 A2 q" o8 M7 a: A( BSlope, 斜率3 D& h/ }/ N5 c- `
Smirnov test, 斯米尔诺夫检验# |1 q, x" [( }. c* \6 q+ F" z
Source of variation, 变异来源' O! g2 _- m M: w: c* \% D+ X
Spearman rank correlation, 斯皮尔曼等级相关! B7 f9 _1 L6 U: H, D3 V z+ s
Specific factor, 特殊因子
% u5 L( t& o- e8 xSpecific factor variance, 特殊因子方差
8 ]( s1 q# L( S+ u- e, XSpectra , 频谱0 g# H; _- Y, X0 R" e
Spherical distribution, 球型正态分布
[/ i) j. C6 |0 f% ~Spread, 展布
8 G1 W, S E; c# J" lSPSS(Statistical package for the social science), SPSS统计软件包
+ @$ Y) @$ b. t _3 T9 H# U6 nSpurious correlation, 假性相关6 V( _2 z' O% M/ P
Square root transformation, 平方根变换
) T/ m# {6 i* J) U4 q- p; \& ~Stabilizing variance, 稳定方差
, R( T2 f% }; o5 bStandard deviation, 标准差
! b: B. L# }! s" r+ f' ]0 EStandard error, 标准误
5 Z4 Y: t- n" N RStandard error of difference, 差别的标准误4 y" C2 o% F; ], }8 R* U5 o8 o
Standard error of estimate, 标准估计误差/ s- M4 n) h1 a" o* _
Standard error of rate, 率的标准误
% R! g! d& Q4 E: ~Standard normal distribution, 标准正态分布# y0 {; S7 u& j2 b ^ r! c
Standardization, 标准化
) W: M" g R( m5 i5 T6 m& |Starting value, 起始值
. L, C" e% o8 [" Q' j1 BStatistic, 统计量6 z- F! `. H5 Z" s1 N
Statistical control, 统计控制( _9 x. h, g$ i v& V' r- F- {2 o- U5 q) M
Statistical graph, 统计图! B7 J3 s4 T1 b- e; Q. @, i/ |
Statistical inference, 统计推断( j# r6 e) V+ ?" \. s0 I/ M
Statistical table, 统计表
7 j7 D) O4 w* E6 H2 z% B: [Steepest descent, 最速下降法: V S( S& w3 y4 t/ ]" o& E
Stem and leaf display, 茎叶图# x+ k U/ ^& L4 j3 }# `
Step factor, 步长因子
; k' R& \) v( K- ?, AStepwise regression, 逐步回归2 R' z# b: P" O' {
Storage, 存
/ y- g8 X) b. D8 w" V9 EStrata, 层（复数）0 W7 v& e8 { _- r# _/ J R
Stratified sampling, 分层抽样( a8 E6 X( A6 Q& C
Stratified sampling, 分层抽样
: p) b: `. q3 M% \0 {0 L. `Strength, 强度
3 ~: u% w- M9 H3 ]- EStringency, 严密性6 g$ \# ]5 [0 Z' Y, H: V
Structural relationship, 结构关系& \: V9 ~3 C D
Studentized residual, 学生化残差/t化残差
' c8 _7 |, B$ }Sub-class numbers, 次级组含量
! _( K3 m( d, q: g/ wSubdividing, 分割/ R; H% k- j9 E$ h9 z, {; h1 f7 @
Sufficient statistic, 充分统计量2 C0 j; t. z* b7 j; q
Sum of products, 积和$ T! a& e) t8 a2 N, b
Sum of squares, 离差平方和3 B4 |# m, H) v: ]: v' E* d3 o
Sum of squares about regression, 回归平方和
' G3 Z1 X# }$ {5 {$ S4 g, h% SSum of squares between groups, 组间平方和 S' R2 {, t9 W% z& b" H
Sum of squares of partial regression, 偏回归平方和, c/ g* m" q2 w' p6 c9 P0 Z7 P
Sure event, 必然事件; f% n# e# L1 x/ O# P
Survey, 调查$ N1 Y' W: [& j
Survival, 生存分析5 ^+ r; v+ N9 O$ y& F& x3 E) X1 { N
Survival rate, 生存率
' m5 J) _: `: S2 c, c* vSuspended root gram, 悬吊根图
" B. j3 k/ M1 o) M$ O' J3 jSymmetry, 对称
q% L$ k/ K- a5 A5 G# CSystematic error, 系统误差
* o: _- v/ ^1 u0 \9 s% J8 ?" QSystematic sampling, 系统抽样
( v0 [. a# x( H) {3 ATags, 标签8 J5 S" ?" j% h4 K, E
Tail area, 尾部面积
7 |- k2 }( V5 kTail length, 尾长6 \* C6 R; v) S W: E5 g% v( B
Tail weight, 尾重' ?$ D! X- H* S1 @! n& [
Tangent line, 切线$ d5 ?& a% g! ]+ t i/ p3 Z
Target distribution, 目标分布! Y' i0 i, M8 L0 D- [# n% g: g
Taylor series, 泰勒级数% o7 ~* `# ]" o- i
Tendency of dispersion, 离散趋势
. O, ]/ \, p- C" d( n4 T# |Testing of hypotheses, 假设检验* [# Z6 a/ p# s- Y% B. ~4 A3 ?9 F7 J
Theoretical frequency, 理论频数/ }: j8 z2 X/ q0 T( V
Time series, 时间序列! z* k8 ~! b" \8 y+ v, j, s1 |
Tolerance interval, 容忍区间! }3 y5 @7 x+ v# S: D: V
Tolerance lower limit, 容忍下限
9 V- g! b$ U5 Y& qTolerance upper limit, 容忍上限
* p/ m* V H" ^0 ITorsion, 扰率. [) s! i& Z/ `
Total sum of square, 总平方和
% N$ @4 V$ F# |8 J4 d5 lTotal variation, 总变异8 c$ E' B' h3 g0 {$ b+ N
Transformation, 转换1 r1 M- K5 l6 p
Treatment, 处理
( S3 W8 h/ y; R' DTrend, 趋势
: y- M) s; i5 \8 \Trend of percentage, 百分比趋势
# O% v: Q' N/ Q% gTrial, 试验
1 D0 X4 y- V; r. t& s3 F& gTrial and error method, 试错法
1 P& u0 U0 ~- V+ p, W" [. iTuning constant, 细调常数6 D/ i5 n* w# |; d3 }
Two sided test, 双向检验" A$ b1 E& Y* ?
Two-stage least squares, 二阶最小平方
, W' `2 d* b+ L: ^" bTwo-stage sampling, 二阶段抽样
- ]# ^1 g4 v! p. k1 U+ G% [; p$ ETwo-tailed test, 双侧检验
, J) v) [1 E* p. K1 u# |- kTwo-way analysis of variance, 双因素方差分析
; }% H- U2 b2 M& L% O. Q& wTwo-way table, 双向表
. r( Z5 [) K# z) x/ aType I error, 一类错误/α错误
B) S/ H7 ?7 D: m4 {" F. xType II error, 二类错误/β错误; n$ m# d' h/ }* [$ H8 L/ n. S
UMVU, 方差一致最小无偏估计简称$ a% c& y* r. |* F* j' E7 H* J" R
Unbiased estimate, 无偏估计2 x$ x7 T% b/ b! g1 T' r
Unconstrained nonlinear regression , 无约束非线性回归. f2 E$ c% o- b+ R+ X
Unequal subclass number, 不等次级组含量0 |* H' n! J- T$ r' G
Ungrouped data, 不分组资料
3 ]. i+ O: ^ ~- F, S0 v0 h! FUniform coordinate, 均匀坐标0 `# l4 ^4 }( T+ Z- A" k& ~
Uniform distribution, 均匀分布
* B& A. F( B& MUniformly minimum variance unbiased estimate, 方差一致最小无偏估计
6 ^1 f' T' T _9 n* ]9 P9 k: S- kUnit, 单元% w0 c/ b6 N9 O+ w: Z0 h1 j
Unordered categories, 无序分类) f3 s7 }/ B# K7 `0 S) [
Upper limit, 上限& I, B9 u# C- }, Q
Upward rank, 升秩
A6 b3 [9 O& X9 `- I2 rVague concept, 模糊概念
" W6 F7 q5 F" l e3 Y$ @4 |Validity, 有效性
5 O u! T8 N; pVARCOMP (Variance component estimation), 方差元素估计
* T3 e! {$ z5 y% y) {( HVariability, 变异性
h8 q6 B. e/ |1 e6 |# Y' VVariable, 变量
/ @$ O) p+ j# a7 {' K* }; IVariance, 方差9 A( L+ b# x1 z4 ^' ]5 u b
Variation, 变异
5 X( K$ ]/ T+ x. y* N% xVarimax orthogonal rotation, 方差最大正交旋转0 ~! O- S+ d0 M% B, H- D8 K5 ]0 n/ j
Volume of distribution, 容积
2 ~1 V: `3 P0 R8 U2 ZW test, W检验7 t4 i% J0 a5 ^. X2 E8 ~7 n
Weibull distribution, 威布尔分布3 F6 q1 z# ^. Y" @7 |
Weight, 权数
5 G7 T# u: v7 o1 P4 h- DWeighted Chi-square test, 加权卡方检验/Cochran检验
5 f' K! U% B' V3 n7 mWeighted linear regression method, 加权直线回归) s7 o* `2 ?( Q |; f0 h/ E
Weighted mean, 加权平均数0 l: n3 `3 M7 }/ U8 V, p) t
Weighted mean square, 加权平均方差
6 p# a+ C# |+ z( N! _! v$ bWeighted sum of square, 加权平方和; Q. }% ^6 K9 g
Weighting coefficient, 权重系数
% o' A. r4 R) ?) ZWeighting method, 加权法 4 [- o" q" i3 E, n; u0 t5 v- O4 P7 w) b
W-estimation, W估计量
, P; U- O. c4 y+ `# e& _W-estimation of location, 位置W估计量
2 n* X+ I( ^& u/ k3 y1 B( @Width, 宽度6 z# l8 I5 f' Y) c3 W1 A
Wilcoxon paired test, 威斯康星配对法/配对符号秩和检验5 h5 ~& }" [: |! I
Wild point, 野点/狂点
) V3 r+ C0 T0 G. W; E+ Y/ hWild value, 野值/狂值8 ?# ~/ Q4 g; ~* O7 R
Winsorized mean, 缩尾均值" Y! v0 p* c% b
Withdraw, 失访
9 }* D6 G/ A8 M1 C0 eYouden's index, 尤登指数* |: I' B- Y* `- ~. w
Z test, Z检验: Q; ]9 u' H# q: A3 q5 S" q
Zero correlation, 零相关
! ~& Q. T1 t8 i7 w( P7 G- r! |Z-transformation, Z变换 |
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发表于 2009-1-6 22:05
