|
|
Absolute deviation, 绝对离差" ^1 w( x0 t: o' ]! K- x
Absolute number, 绝对数
& p& e" h- v# W; c( iAbsolute residuals, 绝对残差
1 R" p: K/ J* l l2 k1 O8 |: IAcceleration array, 加速度立体阵: p& F+ J. ~; a% |; T$ K9 B0 r8 T, H
Acceleration in an arbitrary direction, 任意方向上的加速度
, \! o( \5 [/ s3 Z! sAcceleration normal, 法向加速度/ C* Z9 V7 h0 Z; Q4 P
Acceleration space dimension, 加速度空间的维数: a6 ?2 X2 E" X* v
Acceleration tangential, 切向加速度
$ @, g# S8 `3 k' w1 Y( b* C' HAcceleration vector, 加速度向量
I! F# Y; r Z5 D5 Y+ SAcceptable hypothesis, 可接受假设
! y X/ o7 W `Accumulation, 累积
6 o3 k3 i7 V" U' IAccuracy, 准确度7 \2 B' b5 b; V' p$ \
Actual frequency, 实际频数
, `6 t2 s, N4 c3 \+ S4 qAdaptive estimator, 自适应估计量
+ N& k7 o5 v# k A# m5 m( w, mAddition, 相加: h8 ]- A# B: d# u$ @1 O$ ~9 R2 x
Addition theorem, 加法定理
; W9 u8 I$ n4 j: T! {% }9 Y( yAdditivity, 可加性/ M; Y5 W6 c* l E3 c* u7 X. i: t! n1 O
Adjusted rate, 调整率
3 W& Z9 Z4 v8 }- C- ^. ]7 F- BAdjusted value, 校正值
( r7 c H$ n* y9 G6 _Admissible error, 容许误差
5 B/ M6 d, D! E2 mAggregation, 聚集性
3 W+ v) B1 i7 f. m% S7 pAlternative hypothesis, 备择假设 R* B! ] c1 I. _
Among groups, 组间! O. v2 w2 z( C% E
Amounts, 总量
* X9 x, J1 [2 Y6 ^( JAnalysis of correlation, 相关分析
( p: O& Y0 T: Z3 e2 m( D. ?: JAnalysis of covariance, 协方差分析& [4 D. s" X. w6 g, j- C
Analysis of regression, 回归分析% `* H% `5 A& B, i' H5 o# T% c
Analysis of time series, 时间序列分析
7 L! O4 e3 B# L* |& ]8 [, K! YAnalysis of variance, 方差分析
9 X" ?2 y9 h( A7 dAngular transformation, 角转换
/ V0 n# R/ [9 S% [8 n1 YANOVA （analysis of variance）, 方差分析
! y( }1 }& r# f) W1 b* \! z+ L. ZANOVA Models, 方差分析模型) ~) |% n& r: o: S( `! O; s
Arcing, 弧/弧旋8 Z, n5 [) N6 ]( B! O' e
Arcsine transformation, 反正弦变换
9 a3 O$ @# ~+ @5 s/ q* {Area under the curve, 曲线面积2 H8 u( O% d @! b
AREG , 评估从一个时间点到下一个时间点回归相关时的误差
3 f( Z4 O9 t X1 UARIMA, 季节和非季节性单变量模型的极大似然估计
1 }# I" X0 X* Z6 z5 n1 T5 C2 pArithmetic grid paper, 算术格纸, }, A( u L' }9 ?: s- R3 r0 @/ S
Arithmetic mean, 算术平均数
7 J* w, o0 W, d- N1 iArrhenius relation, 艾恩尼斯关系9 ^" K. X; E+ W' a* _
Assessing fit, 拟合的评估
5 k1 O' _. w! y0 D9 l* f- H0 xAssociative laws, 结合律
* d0 j2 [2 c6 ?& r5 Z* s4 _% ]Asymmetric distribution, 非对称分布5 \4 A& D( \) `) f1 ?
Asymptotic bias, 渐近偏倚
* [& X" [. d W. v# @( mAsymptotic efficiency, 渐近效率
- B k [1 s3 [; o; A6 A pAsymptotic variance, 渐近方差
( J) J. d0 ~( _" p! A$ e6 yAttributable risk, 归因危险度
" T) c9 f5 q/ aAttribute data, 属性资料- [7 h" b/ F: _" w% l8 x
Attribution, 属性" s7 N4 W2 D. q2 N! Y
Autocorrelation, 自相关* F3 U# p: u3 U. _
Autocorrelation of residuals, 残差的自相关 R, o4 Q. Q J: ^: f
Average, 平均数
8 {) j% w% @ e7 E7 _Average confidence interval length, 平均置信区间长度
- H6 J0 U! p: ?# q1 k$ mAverage growth rate, 平均增长率9 U9 A7 F9 u/ I! _7 G! u
Bar chart, 条形图3 ^; q2 i1 H2 d& y; P& u5 s
Bar graph, 条形图
4 K. ^4 U) u3 d9 y m3 B- MBase period, 基期
3 I) ?# A* w. a$ z0 \; b1 X7 DBayes' theorem , Bayes定理6 M+ Y& ^6 F+ \) K; w H
Bell-shaped curve, 钟形曲线
0 f+ C, d; m v: H- P/ ~" KBernoulli distribution, 伯努力分布
, v& f0 D+ x- O$ m8 z7 b7 YBest-trim estimator, 最好切尾估计量
m: W6 S. @0 J% T& sBias, 偏性
$ I% w" @( }7 O d5 }9 n9 r0 YBinary logistic regression, 二元逻辑斯蒂回归3 h9 ^8 k4 U0 n5 ^/ r* e Q
Binomial distribution, 二项分布
. P1 V1 E" [- t& X L: Y0 I& NBisquare, 双平方& j2 k3 y6 p* B/ Q7 G
Bivariate Correlate, 二变量相关+ T7 H( J5 X+ A; f
Bivariate normal distribution, 双变量正态分布7 `$ i# W! @: ^1 }* L4 l
Bivariate normal population, 双变量正态总体
' F, C% k u7 @* G: t" ZBiweight interval, 双权区间
; m5 f8 O1 D" RBiweight M-estimator, 双权M估计量1 L4 d* t% o2 T5 l. D2 g4 n
Block, 区组/配伍组
1 W0 n$ _' {: l( H: l/ }BMDP(Biomedical computer programs), BMDP统计软件包
8 H; V' e1 J3 ~4 g( C b: SBoxplots, 箱线图/箱尾图- H' Z1 Q* s: V9 M/ z: Z
Breakdown bound, 崩溃界/崩溃点
4 T8 Y& o: q) ?( B; SCanonical correlation, 典型相关$ W3 W# P2 M+ ? R
Caption, 纵标目. m) ~- G" R% E L% J) A7 Q/ A
Case-control study, 病例对照研究
' ?$ {" i% |' V/ {' W- j& j" jCategorical variable, 分类变量
5 ]6 K: A. F4 ~+ c7 b5 E- J* }% `Catenary, 悬链线
( e" R$ [# f$ s, w! N7 sCauchy distribution, 柯西分布
" e- i- {; D2 s0 q+ ACause-and-effect relationship, 因果关系" q! ^3 C% G" B2 K8 _
Cell, 单元7 R8 Z' w) }' P7 ^4 K9 l+ l5 Q
Censoring, 终检! x( X( p. k& J* f* @& L; `
Center of symmetry, 对称中心/ Q- v' n! k; s! v7 U. N9 z! M" X
Centering and scaling, 中心化和定标1 n8 z# i& M( k: G$ K" K
Central tendency, 集中趋势, c. w" B2 k/ t8 ~0 K
Central value, 中心值2 x- D4 w' u: P: Q
CHAID -χ2 Automatic Interaction Detector, 卡方自动交互检测
# v) ]* F8 n5 ~/ P0 ^Chance, 机遇
1 `$ `2 y2 V6 CChance error, 随机误差* b0 w) r2 d: F/ ?
Chance variable, 随机变量
$ I% m j M( o, t2 C. n9 \! aCharacteristic equation, 特征方程2 ~: X; W' F! @; f& m
Characteristic root, 特征根4 }% ~9 @6 V! K$ O1 P- C
Characteristic vector, 特征向量$ i( n/ L. h5 b# t+ B8 i& g
Chebshev criterion of fit, 拟合的切比雪夫准则
/ B7 T$ F: a- B5 j! `" _Chernoff faces, 切尔诺夫脸谱图
) {: V4 p4 r" k" Q$ G1 m6 ]5 `Chi-square test, 卡方检验/χ2检验
( _; a, }5 B$ g2 n* o8 c3 E0 j; @Choleskey decomposition, 乔洛斯基分解* v; c0 J9 x$ e: a2 l! g. f
Circle chart, 圆图
0 G+ S5 N* q7 ~: BClass interval, 组距
$ V$ r6 p4 F! [' UClass mid-value, 组中值$ A' k$ G% C6 O$ m0 ~
Class upper limit, 组上限, j/ P# Q& M2 F* l% p
Classified variable, 分类变量
}. ~" l8 R5 u4 A+ wCluster analysis, 聚类分析4 R' j$ V( o E- F) o
Cluster sampling, 整群抽样
2 E2 |+ X/ @" I' X" i; oCode, 代码8 {7 g3 }( ~+ p1 x
Coded data, 编码数据
& w) i# U6 o' _( F. x, T3 b( N+ PCoding, 编码
$ b8 Z5 d; m8 OCoefficient of contingency, 列联系数
$ F" y* B6 J% y+ u$ ~- e4 g' Y5 FCoefficient of determination, 决定系数1 F4 D7 ~% k" g0 M
Coefficient of multiple correlation, 多重相关系数6 K7 d3 ?2 t8 _3 Y$ o8 @; z
Coefficient of partial correlation, 偏相关系数+ U5 E5 t( Q$ @. t+ Q
Coefficient of production-moment correlation, 积差相关系数
( V; c+ O) d* s7 y; ]9 y2 w8 d# nCoefficient of rank correlation, 等级相关系数
2 p/ l {! c0 U+ zCoefficient of regression, 回归系数. l0 L" R+ H6 X
Coefficient of skewness, 偏度系数4 m! Z& i1 G- O8 E# O P
Coefficient of variation, 变异系数- e, p0 D. u8 i4 Z+ T2 Y/ M4 M
Cohort study, 队列研究0 q8 H0 g: Z$ l2 V# e1 o! \
Column, 列 o* C& @) C& j( j
Column effect, 列效应
" A8 a0 |6 S" r4 e; G0 `& j, \Column factor, 列因素
# \! q5 R- R' p) sCombination pool, 合并
3 F) M/ j" M* E4 n. g$ ` \Combinative table, 组合表 I( \! k4 i" T% \/ n
Common factor, 共性因子
) }7 R, q1 Z- v/ ~. nCommon regression coefficient, 公共回归系数3 l3 [5 o h' m! A2 T: X
Common value, 共同值2 R# R5 }7 ^8 h- D9 G4 U3 g3 ^
Common variance, 公共方差
. g2 A% K7 h' i/ [' h0 kCommon variation, 公共变异) O9 ?7 Q9 H% t. l
Communality variance, 共性方差
" Z4 E& R" u1 k; uComparability, 可比性; q7 d- h; {) L9 w6 }
Comparison of bathes, 批比较8 T0 D2 N+ s9 y9 G1 R5 X9 p
Comparison value, 比较值; @9 Y, X6 @1 g8 ]
Compartment model, 分部模型
/ h& z V+ d/ m1 y# MCompassion, 伸缩
' o T) ^+ m) q, |& |2 k+ q& mComplement of an event, 补事件
' d( s) W" G5 J& G+ x- jComplete association, 完全正相关6 j( c+ L5 X/ m! P, V4 r
Complete dissociation, 完全不相关% W8 ? ?) G7 x
Complete statistics, 完备统计量
V' Y5 T6 I5 Q, Z) V. jCompletely randomized design, 完全随机化设计
& N3 b x# {: U1 xComposite event, 联合事件
2 G9 ^, P! J4 Y: N5 f0 }" C/ Z, a+ qComposite events, 复合事件* Z5 ^ f+ \7 i+ ^: o7 j
Concavity, 凹性
' s6 f J3 ]4 y0 l- e h' W1 j. eConditional expectation, 条件期望
5 o4 a8 @ y% K3 x# h) h* y. uConditional likelihood, 条件似然
+ o: r! X* @9 T& ~; ?9 LConditional probability, 条件概率! G1 r& n: E# m
Conditionally linear, 依条件线性) d& O9 r& L6 { D r# k; G! r
Confidence interval, 置信区间& d, P! E1 f* {4 T( c
Confidence limit, 置信限
( Y! q$ U, b$ E+ [Confidence lower limit, 置信下限
+ c% u4 B: `0 P5 ^: R" c6 g+ ]1 ^Confidence upper limit, 置信上限, h' f& z0 d: w+ s. w
Confirmatory Factor Analysis , 验证性因子分析2 L. y f. f' j: u9 W. E8 f
Confirmatory research, 证实性实验研究( D4 ?2 Q! o6 w' W5 I- u& t; @$ ^
Confounding factor, 混杂因素
7 u& E$ [2 W" P; s: CConjoint, 联合分析; ?6 j* ~) c9 a" ]+ {# A
Consistency, 相合性
3 U: c- s+ z$ R( G9 Z" A1 V l# E+ vConsistency check, 一致性检验0 {7 `9 }2 r* q2 k) a; K ^
Consistent asymptotically normal estimate, 相合渐近正态估计$ w3 E! i) z3 s6 I8 [, ]7 p$ Z
Consistent estimate, 相合估计, x% k7 ~4 k1 Q, @
Constrained nonlinear regression, 受约束非线性回归
; t$ J, V& `& L5 `4 r, t2 L$ w8 b" UConstraint, 约束, ~# _7 y! p- K+ H9 L/ S i
Contaminated distribution, 污染分布$ F" e+ ]) C9 c# _1 T
Contaminated Gausssian, 污染高斯分布
: s5 [8 V2 o ^& V2 S6 N2 o8 kContaminated normal distribution, 污染正态分布
" X& e" v+ q% M, t+ D% ^Contamination, 污染
- u" c) p. M+ k$ f! K' MContamination model, 污染模型+ p. q5 w) |* ~$ E! b" z
Contingency table, 列联表
* ^. y. i% Z4 M& g; u6 E% NContour, 边界线
" m' w3 n( N/ uContribution rate, 贡献率
( r- q; }$ e" h3 Q" M" h2 n) G0 O- PControl, 对照
3 K: ?1 L, H1 }$ x; w0 L- \Controlled experiments, 对照实验- r _" Q8 r# k7 \+ K: F# U9 T i
Conventional depth, 常规深度- }& X# o, z. |6 N
Convolution, 卷积* W: J( A& |6 M6 ? E% X
Corrected factor, 校正因子4 J9 |# [% ^1 Q6 M, X2 _9 r
Corrected mean, 校正均值1 L* U+ @% C3 [/ P
Correction coefficient, 校正系数7 A1 T; T4 C o! a/ G6 q" o
Correctness, 正确性
3 ~+ F9 O/ O( _Correlation coefficient, 相关系数
% g( }1 l( o) g% c( d& wCorrelation index, 相关指数
6 `" k% R& E9 ?6 gCorrespondence, 对应
; L1 E2 R# V, _3 WCounting, 计数
+ v2 d5 i! d" F; n6 y, S8 VCounts, 计数/频数
8 N, ?6 {6 a: i- N; c0 PCovariance, 协方差
. E+ H( O7 h Z) a- s/ M/ BCovariant, 共变 $ y3 x( G8 Y/ M# G
Cox Regression, Cox回归
# i) u9 O+ R* i+ E5 K ~6 Y2 xCriteria for fitting, 拟合准则! s+ J4 s9 s$ ?. u% ?; Y& z
Criteria of least squares, 最小二乘准则' ~$ P+ N& ], V" v; r# N- l
Critical ratio, 临界比
7 k: Q% a* R( g4 y8 d/ i+ iCritical region, 拒绝域/ p5 w: m1 I9 a/ o7 m
Critical value, 临界值" b" I# u% ~* c. J( [9 u; q
Cross-over design, 交叉设计 v+ p3 r X8 `* W8 f
Cross-section analysis, 横断面分析! b; Y2 Z" g5 E% Y
Cross-section survey, 横断面调查
5 U8 a% l6 f: i& N# g& MCrosstabs , 交叉表 7 n* E7 E- R H/ S/ l* ~9 [
Cross-tabulation table, 复合表7 e6 `+ a; U0 q
Cube root, 立方根2 l- ^5 t+ F0 [6 Y
Cumulative distribution function, 分布函数! q+ J+ V5 q7 l( V& p- ]; w4 k4 w
Cumulative probability, 累计概率
# x( o0 N( S$ v2 |' ?) y5 \7 b* jCurvature, 曲率/弯曲
$ _( @6 f7 x& L% jCurvature, 曲率1 ^& D* I7 F C- `. k {3 B- u( |$ F
Curve fit , 曲线拟和
5 r" @, X9 q! d" c3 XCurve fitting, 曲线拟合9 f) ]- {" q% E, R/ v
Curvilinear regression, 曲线回归4 {6 y$ Y1 v$ q3 B
Curvilinear relation, 曲线关系. x) }0 ?9 l4 k
Cut-and-try method, 尝试法& w) _! U, [; K; s0 [8 p S
Cycle, 周期( k" ]% [* Q- P) \
Cyclist, 周期性6 Y# ?, B6 q% v
D test, D检验# u7 K; @7 E; N! G/ r U! M# \
Data acquisition, 资料收集
5 I6 K$ I$ f2 g2 S# O7 d( d }Data bank, 数据库
T) K Q, `' o* X3 a4 s5 zData capacity, 数据容量- u/ t+ t8 v, R2 a$ Y
Data deficiencies, 数据缺乏# Y6 I/ Y' z! @2 z) a( }
Data handling, 数据处理
' Y4 J R# n2 h& A' Y8 K. X3 iData manipulation, 数据处理( ?3 l6 ?/ l: Q+ z6 S: Q
Data processing, 数据处理( c! e; h: S' d$ I A4 H+ Y
Data reduction, 数据缩减/ k k7 W) q1 X
Data set, 数据集
/ j6 K0 M) v# YData sources, 数据来源% ~. ^) q" {) {- |
Data transformation, 数据变换
% {' _. q! U) b' c/ @( HData validity, 数据有效性6 Q4 N& r+ w6 R/ m) J5 C* c
Data-in, 数据输入+ w# k0 e9 ^! ?/ l
Data-out, 数据输出
" R" }8 Z; I3 `$ u6 u9 ?Dead time, 停滞期
4 i I, c. F2 c- ^% }' S& M. XDegree of freedom, 自由度
# ~9 n. A0 j4 P1 b5 hDegree of precision, 精密度
5 l1 w# |% _7 D- L3 Y8 t$ f( oDegree of reliability, 可靠性程度3 b+ B" Q- V$ e
Degression, 递减. i4 ^, v8 a; K/ e( I
Density function, 密度函数
0 O/ K2 V# S+ z, VDensity of data points, 数据点的密度; j7 ^& V h* _5 c( |% Z, }- l
Dependent variable, 应变量/依变量/因变量6 r' Y. j X% g, R+ U
Dependent variable, 因变量8 m X! ?- R4 J$ E$ l
Depth, 深度
* ]2 n7 V y# D+ d" ]; I7 A# `Derivative matrix, 导数矩阵
8 D! u! K, H1 u+ V$ a+ _Derivative-free methods, 无导数方法
) r" A h7 D6 TDesign, 设计; I7 P) }, o; A2 M _8 ?
Determinacy, 确定性! T+ x6 {; k" m3 f3 g! O
Determinant, 行列式) s4 S4 e, y& n0 q
Determinant, 决定因素
$ Y' f' c6 ]# ^5 K; ]Deviation, 离差8 ?$ Y& A& U, G2 n( x
Deviation from average, 离均差5 @2 l( l! u0 g2 u
Diagnostic plot, 诊断图6 v+ g/ F+ |+ Z, T9 L
Dichotomous variable, 二分变量, F Y5 z6 e5 _ ^; m
Differential equation, 微分方程* U" c& N9 @, z0 X) {
Direct standardization, 直接标准化法
5 ~ w/ N$ v9 O: e2 ^ S2 rDiscrete variable, 离散型变量
5 s9 B3 S. [% B9 K; {1 uDISCRIMINANT, 判断 1 ~& S% T- k, n0 P2 i
Discriminant analysis, 判别分析
& ]$ | d' X+ C# Q/ nDiscriminant coefficient, 判别系数
. u# y7 [, [$ O1 s* z# `3 y# _Discriminant function, 判别值
7 ~: e) O: c4 g( d& xDispersion, 散布/分散度
8 v: ^* v5 n9 T- {Disproportional, 不成比例的
2 \- b! X6 A' ?$ J% F: RDisproportionate sub-class numbers, 不成比例次级组含量+ o3 ` h, M' }
Distribution free, 分布无关性/免分布/ X- ~7 D* n8 F3 x3 ^ [
Distribution shape, 分布形状/ V2 s J. q# T5 ^
Distribution-free method, 任意分布法
" E# S, n L( i2 g2 Q8 L% u* GDistributive laws, 分配律
4 F) U& h1 d1 O$ q( O; |# B, Z, TDisturbance, 随机扰动项' V4 E* w: @/ P* P, G5 v5 R: r/ G
Dose response curve, 剂量反应曲线; @& l) h# j/ K: `
Double blind method, 双盲法 D( g2 ]5 p# o/ p
Double blind trial, 双盲试验" x: f( l9 Z3 z" Z$ H8 m+ E$ n
Double exponential distribution, 双指数分布
( v" v3 J! l) E' eDouble logarithmic, 双对数& k: _; i6 }: K. F: u
Downward rank, 降秩
4 Z2 ~! `# E5 X) e! a! j2 cDual-space plot, 对偶空间图
# z% T) {2 U9 Q+ O$ BDUD, 无导数方法
* T& @. M% n: o0 WDuncan's new multiple range method, 新复极差法/Duncan新法8 F' U$ i' N& X" ^! C5 {/ p" K
Effect, 实验效应) H' i0 V2 X7 E
Eigenvalue, 特征值
: ^5 F' }- H9 H* b1 P5 }Eigenvector, 特征向量
5 i$ R2 ]3 z4 X* W4 Z% LEllipse, 椭圆
6 i* m( \- h6 h j% P( m8 s" I4 OEmpirical distribution, 经验分布/ [2 }: q6 h) I: u2 p
Empirical probability, 经验概率单位, s$ T$ J' Y N% H! Y
Enumeration data, 计数资料
. z- y8 r" c8 [% @Equal sun-class number, 相等次级组含量+ _# b, |$ H% c" p
Equally likely, 等可能
! X' N8 l4 B& V8 k' L7 M, @: U) NEquivariance, 同变性
, ?, j& Z4 V; h1 j, zError, 误差/错误
5 O6 p! t0 k0 e2 e0 XError of estimate, 估计误差8 l& |9 i$ G: x/ c
Error type I, 第一类错误
; K# M2 `1 M! ]5 K6 |- f8 C( w5 SError type II, 第二类错误7 p T/ a. H3 b
Estimand, 被估量
- Z9 K9 x5 P* s4 B0 ?Estimated error mean squares, 估计误差均方$ K7 q& t2 I4 u$ ?) ]7 M" I
Estimated error sum of squares, 估计误差平方和
( I. A4 L( `7 v. s/ pEuclidean distance, 欧式距离6 e8 B) I; e5 v5 J% p& H
Event, 事件
4 c; C- z8 m( p ?" P! B5 wEvent, 事件
3 w- ]. Q* S p2 vExceptional data point, 异常数据点
; }) D% X+ I& lExpectation plane, 期望平面& ^8 J3 `7 R, a( O
Expectation surface, 期望曲面
7 S' X/ c# |3 OExpected values, 期望值
* S# T# b1 Y! l3 ^, Y7 ZExperiment, 实验/ p) h' c+ p" Y2 }. b" ^5 R
Experimental sampling, 试验抽样
% A/ O1 b5 ], ^3 T! pExperimental unit, 试验单位' Q. P7 v% B$ C4 p
Explanatory variable, 说明变量
4 a& ?7 g" l( p% g& r' V0 oExploratory data analysis, 探索性数据分析: Y, ?1 O' D1 K8 m& j
Explore Summarize, 探索-摘要
. U1 ^' M6 s) [4 m5 F* d' FExponential curve, 指数曲线: D r( |( e& i( O+ E9 H! W$ a
Exponential growth, 指数式增长/ @# z7 \! \" ^" Q
EXSMOOTH, 指数平滑方法
/ D; ]8 Z" ?7 Y+ h, ]2 q7 iExtended fit, 扩充拟合2 @7 v2 J1 |3 p2 { h; H' V4 f) k
Extra parameter, 附加参数0 B) j& U) ]8 l
Extrapolation, 外推法- c8 a" O4 W- X# p( K# j
Extreme observation, 末端观测值7 f$ X! \7 q6 L! ?+ R* ^1 h
Extremes, 极端值/极值% i, R) y- x/ I0 ~3 v, E
F distribution, F分布
( m1 \% x$ [& B2 e: ^% B- }F test, F检验
& B: c ?1 e# R. bFactor, 因素/因子( |; M9 \) y# j% E3 z& |
Factor analysis, 因子分析$ b8 Y( @" Q, [/ R
Factor Analysis, 因子分析% p7 e* d! M+ |
Factor score, 因子得分 + t3 H) s: B$ m
Factorial, 阶乘
& |2 e: o1 c( f$ Y, Z& u3 dFactorial design, 析因试验设计
5 o3 z- j4 |. hFalse negative, 假阴性
2 y5 c# ^* S3 wFalse negative error, 假阴性错误! J8 \0 g* ?3 J0 A2 w) J* k6 R
Family of distributions, 分布族$ L; g v. s) m1 ~
Family of estimators, 估计量族
4 h* _3 D8 }2 D( i5 VFanning, 扇面
2 C) O4 [9 L$ |5 z) IFatality rate, 病死率
; A% K8 M, B- o* R& `1 A5 uField investigation, 现场调查
7 U- ], }" F( r$ @: U0 e+ g5 {Field survey, 现场调查% o! T/ |' A+ D+ b! V
Finite population, 有限总体$ ]( T: |5 j; d/ s J
Finite-sample, 有限样本
7 J. Y) c" F1 h0 I' DFirst derivative, 一阶导数/ [3 J+ h8 _0 Q$ W( i
First principal component, 第一主成分
* q! |8 J, o3 b8 _- |First quartile, 第一四分位数
1 S7 Y2 L: [3 H3 j. w1 ?Fisher information, 费雪信息量( o; [; A1 W! H# K! d9 U
Fitted value, 拟合值( h- |- J, ?2 \0 B: B5 V" H
Fitting a curve, 曲线拟合# I- n! ~ H' r, R. L0 U+ m7 f
Fixed base, 定基
& e% K1 Q# H; O& u* PFluctuation, 随机起伏5 n2 m! E5 X; J1 W# {6 Z
Forecast, 预测5 v- G, y, _9 X, R: K# L. f' T6 d
Four fold table, 四格表! }' p. S4 B7 D" g+ g
Fourth, 四分点: o1 ?5 O, K9 ?/ S6 G% P
Fraction blow, 左侧比率
2 t8 I7 y, D }( C5 BFractional error, 相对误差5 }8 G+ Q2 r- X+ F0 U0 l$ K& i4 H0 w
Frequency, 频率+ k5 W# w; j% c, X! g7 y) R; X) O
Frequency polygon, 频数多边图5 H6 u( U) c3 j, n0 F p$ N
Frontier point, 界限点
( ?' X+ N" S; }! q9 W' V' O- e5 N( GFunction relationship, 泛函关系! m$ T ~8 I2 M& { s- m
Gamma distribution, 伽玛分布 p9 O w$ v8 X3 s: m& X
Gauss increment, 高斯增量
0 b& s, x3 z- s/ V0 CGaussian distribution, 高斯分布/正态分布 }* I; F4 B5 ~- F
Gauss-Newton increment, 高斯-牛顿增量+ T! J* a& Q2 C6 Z0 o0 U, O2 q0 ~
General census, 全面普查8 K: P+ G( @* I) E
GENLOG (Generalized liner models), 广义线性模型 " M t f6 U) s* l4 ~: ], @
Geometric mean, 几何平均数
- d+ q: i! o3 N8 I8 `) C4 q, zGini's mean difference, 基尼均差
- D: Q/ l& u8 t' \GLM (General liner models), 一般线性模型
4 \) v# g$ d. [' I' WGoodness of fit, 拟和优度/配合度1 a/ B& ?. |- L, I# }
Gradient of determinant, 行列式的梯度) I+ k' z/ C4 |* I% u% y' d% x) p
Graeco-Latin square, 希腊拉丁方7 g, Y' J( J+ k$ ?
Grand mean, 总均值% w6 r' t% U) d* S L, G. p
Gross errors, 重大错误- W7 W0 q8 K) T; s! g0 Z$ _+ @ y
Gross-error sensitivity, 大错敏感度1 D* W9 R& y: D* L- h, n8 |0 @
Group averages, 分组平均, } n: }, d" G3 z" R( n1 \
Grouped data, 分组资料& I: j9 m+ T% \. f1 C9 X
Guessed mean, 假定平均数; h, @$ Z' V9 H/ |8 |3 ^
Half-life, 半衰期
0 W' M" |* P# K7 t, ?Hampel M-estimators, 汉佩尔M估计量 h8 y; [- }0 s& h& Q* @7 @$ S
Happenstance, 偶然事件
3 j, ~& n( y/ V/ DHarmonic mean, 调和均数9 A) _ i7 ~ j2 M) N( z# N
Hazard function, 风险均数, f O1 s+ K3 r& p' ?. }1 l: K
Hazard rate, 风险率
& D( R9 J: y5 S. Y" p' F; @! o' iHeading, 标目
' G8 F+ Y( M8 _- OHeavy-tailed distribution, 重尾分布
0 J0 ^$ g8 P# P. CHessian array, 海森立体阵5 z1 B& o( L# d( }# {( e
Heterogeneity, 不同质 J' Q/ e5 o" H0 V4 S3 J
Heterogeneity of variance, 方差不齐 9 @" G; b7 l0 A' }0 c
Hierarchical classification, 组内分组6 e) }( {$ x! x: V# J0 B* V# d0 Q2 Z7 g: T
Hierarchical clustering method, 系统聚类法+ [# @0 m0 G( Q& a
High-leverage point, 高杠杆率点5 [1 F. N0 k. I- V1 L
HILOGLINEAR, 多维列联表的层次对数线性模型
! ^) U- _1 H* M# ~0 [Hinge, 折叶点0 @# O, H; F0 ?2 w$ X
Histogram, 直方图9 o1 Y7 H" s6 B4 g2 m2 v
Historical cohort study, 历史性队列研究
+ m. r) O) m7 ]) ^) r2 K2 `! u/ VHoles, 空洞$ I( p0 o K+ {/ t/ J
HOMALS, 多重响应分析
& n$ r$ q3 g9 z; y6 jHomogeneity of variance, 方差齐性3 P4 `( K8 b2 |9 r/ V& f
Homogeneity test, 齐性检验, X6 }# m" G$ V6 _
Huber M-estimators, 休伯M估计量
# b9 R' \4 \2 P. t3 L6 F2 W+ LHyperbola, 双曲线0 i# s- F* y- c9 Q2 s/ Y
Hypothesis testing, 假设检验! X0 p2 A6 q2 w7 W
Hypothetical universe, 假设总体5 Y3 S; h( J8 {4 v
Impossible event, 不可能事件
" F$ I6 l+ p+ R7 W8 `0 c* V& G# R7 @Independence, 独立性" r# [$ H% o2 [6 O2 |. \" Z
Independent variable, 自变量
9 ~; a5 ^3 A/ B+ n, a( hIndex, 指标/指数
% Y$ @% i5 X; p1 |0 v' CIndirect standardization, 间接标准化法
5 _; r$ p# }3 ?0 n( o9 ?* L0 @3 IIndividual, 个体$ T& O/ N. q4 [3 x+ h$ _7 {1 e
Inference band, 推断带9 O+ F0 O+ w' w* m
Infinite population, 无限总体! R5 ]2 N9 R1 \3 I" ?" F% b
Infinitely great, 无穷大
+ D8 _5 H E# l7 z# v$ AInfinitely small, 无穷小
* F1 H' ~) r- C; {# k* B2 SInfluence curve, 影响曲线
6 M2 `: P, E' }, N: OInformation capacity, 信息容量
, D3 s, s4 {+ T- kInitial condition, 初始条件
0 Z: @8 u" w9 h# k& E* a& ~Initial estimate, 初始估计值" z/ Y6 a& l& }/ v" _
Initial level, 最初水平1 t- {% X) v* G
Interaction, 交互作用
$ u" P% B8 a$ S! q. E- a: JInteraction terms, 交互作用项
% I7 ]2 y6 v5 _Intercept, 截距0 I, i, T5 T8 j4 K9 U0 B' C
Interpolation, 内插法6 k5 Y# r) l5 l' A4 x
Interquartile range, 四分位距
- }: U6 @! U8 O- X- YInterval estimation, 区间估计
" k1 [" U9 ]6 E- U% DIntervals of equal probability, 等概率区间
& G8 U" H5 Y& z* Z8 e, HIntrinsic curvature, 固有曲率
: E; Y+ E! d7 a+ S) R9 eInvariance, 不变性) V- I2 m2 O$ `& Q4 x3 u# B8 ~2 j
Inverse matrix, 逆矩阵
$ h( @% g9 p5 U6 vInverse probability, 逆概率* s" ?/ S d* O! Y) A
Inverse sine transformation, 反正弦变换
0 h8 Y; r2 D6 [7 {Iteration, 迭代 2 S5 h1 O3 K# e- a' I6 |/ f% X
Jacobian determinant, 雅可比行列式) z3 W3 H! }+ e; c; e9 e' t
Joint distribution function, 分布函数
( i H: M! W- \6 VJoint probability, 联合概率 s# G$ W- t9 z7 ]4 J
Joint probability distribution, 联合概率分布
. i: p$ c" k/ l- {4 RK means method, 逐步聚类法
4 N; p" S9 z9 V$ {7 i4 u# RKaplan-Meier, 评估事件的时间长度 , I" c7 e5 R4 K. Y
Kaplan-Merier chart, Kaplan-Merier图
6 H9 y, m! o# ^# F2 A8 D1 |1 eKendall's rank correlation, Kendall等级相关. }6 h$ Q/ E2 H+ n$ \
Kinetic, 动力学
9 }& G. A) K: s& L4 \Kolmogorov-Smirnove test, 柯尔莫哥洛夫-斯米尔诺夫检验( e* j& l8 ` J* X% ]5 U
Kruskal and Wallis test, Kruskal及Wallis检验/多样本的秩和检验/H检验
% V7 l6 J" ~' S# G% JKurtosis, 峰度
0 s7 U F+ E& y# i, u$ F+ n/ ALack of fit, 失拟
8 \) Z4 W# H# dLadder of powers, 幂阶梯1 y* R+ B0 X Y U
Lag, 滞后3 | M/ e) V( y- U' S1 g, q% x X
Large sample, 大样本
( @7 ?. s2 ]" k; T& ~ o; fLarge sample test, 大样本检验; Y. e. T2 s" x9 t* m( ^& m
Latin square, 拉丁方
. {' L8 X" z7 t9 pLatin square design, 拉丁方设计' P3 A$ o( [# O
Leakage, 泄漏
$ X( m' O7 {, b, w( Z- fLeast favorable configuration, 最不利构形
2 M4 l2 d& ^7 {* `& \2 _% gLeast favorable distribution, 最不利分布
: Y$ A& t- f. }3 i9 P6 t# t5 J! ]# VLeast significant difference, 最小显著差法
1 F0 |; S) _9 JLeast square method, 最小二乘法
! F- J$ f# {; DLeast-absolute-residuals estimates, 最小绝对残差估计
1 o* C' ]9 S# t+ h. y6 E' N" \Least-absolute-residuals fit, 最小绝对残差拟合/ |9 v4 S& e. A2 @$ L4 Y
Least-absolute-residuals line, 最小绝对残差线
6 _/ @- Q" X9 z) @' RLegend, 图例
* Q/ s, B* j4 ~' h% j2 eL-estimator, L估计量7 Q1 u+ j( _$ N) s& A5 z8 `
L-estimator of location, 位置L估计量
0 ^$ x. p2 Y) B) b/ g/ x- WL-estimator of scale, 尺度L估计量/ |0 h5 }) m6 `
Level, 水平" u; [ |/ C4 W" z/ w3 w* p
Life expectance, 预期期望寿命
, z" O$ M, S2 p" fLife table, 寿命表
% S% `5 S% E0 N- W8 d4 \Life table method, 生命表法4 G7 k3 D" z& d; J. K H4 g, c
Light-tailed distribution, 轻尾分布
: `8 ~* p1 u# D1 x3 O- nLikelihood function, 似然函数
0 g7 H5 R Z8 [& Y2 V: jLikelihood ratio, 似然比2 u6 r0 t9 Z1 O0 F4 i
line graph, 线图
7 G+ p3 P z/ a* E/ HLinear correlation, 直线相关, z( e- X+ u' A# g) Q2 H
Linear equation, 线性方程' S5 {+ Q* c+ y- @# P* @
Linear programming, 线性规划/ C8 _- u, S: E# v9 O
Linear regression, 直线回归
# N+ ^, _0 g8 b8 DLinear Regression, 线性回归' q; j$ {" T* b% f& h
Linear trend, 线性趋势
! x/ p5 R. P: f( GLoading, 载荷 + O/ d& j! z8 j* k! G- e P
Location and scale equivariance, 位置尺度同变性: Y8 D. G6 ]4 v- x8 J
Location equivariance, 位置同变性
! k) S2 y* P( R. q; y6 |Location invariance, 位置不变性
. O0 R% y# h3 I9 _Location scale family, 位置尺度族
$ j+ o2 b: ^4 f& s: C1 b( C+ DLog rank test, 时序检验 ) Q; b3 H; @1 s3 T8 {* g, m
Logarithmic curve, 对数曲线
! e) C+ |3 u* m& }Logarithmic normal distribution, 对数正态分布* ], } q Z$ y/ @0 }% E5 N
Logarithmic scale, 对数尺度
( u' O l' ~+ O" j7 R5 l D3 p0 n R/ fLogarithmic transformation, 对数变换
$ k i* [9 b7 y1 S( C1 k& @5 fLogic check, 逻辑检查8 K' n8 k5 k- D6 W5 t# G. f
Logistic distribution, 逻辑斯特分布. {# d5 S: [9 p3 _
Logit transformation, Logit转换
" u5 m# h* F: `LOGLINEAR, 多维列联表通用模型
9 N# ]4 f! h/ l% G. aLognormal distribution, 对数正态分布) L0 K5 U* P b8 o+ h$ Z
Lost function, 损失函数, e- M2 ?; g3 B/ ~4 w4 h
Low correlation, 低度相关: o. X& N7 Z# ~ Y9 E m3 x
Lower limit, 下限' p( @3 `" s0 A* r/ R" i& M
Lowest-attained variance, 最小可达方差
' F# N. Y! f. bLSD, 最小显著差法的简称' j" X2 j3 x2 e. L6 T9 F, S
Lurking variable, 潜在变量
, _) [: m: t+ T' q: v5 bMain effect, 主效应+ ~' B2 x2 A' {2 A
Major heading, 主辞标目* U1 b/ T8 j" |& Q/ C9 |6 F& r
Marginal density function, 边缘密度函数
' l+ _) k# C8 F8 ^: J8 b# S7 NMarginal probability, 边缘概率, |# E' y. Q% }) E7 Z. v" }2 N+ `/ b
Marginal probability distribution, 边缘概率分布 }' K1 c2 P. i+ B9 @
Matched data, 配对资料# m( X5 p0 P8 Y2 s: _) u& e/ }
Matched distribution, 匹配过分布! N5 C/ d0 P7 w! \' [$ W
Matching of distribution, 分布的匹配9 [( I% m3 _1 g, b: D
Matching of transformation, 变换的匹配0 b4 C. N/ k9 k
Mathematical expectation, 数学期望2 Y. j, z% I# J
Mathematical model, 数学模型2 i) Q2 p, p) E; M# C
Maximum L-estimator, 极大极小L 估计量- U5 }% @; l/ b' Z# B0 t) W
Maximum likelihood method, 最大似然法" R U* |: W- d
Mean, 均数
3 ?9 H% a8 {+ u/ J( H, A4 jMean squares between groups, 组间均方- B2 A, B. Y. k \: I
Mean squares within group, 组内均方8 k& k7 I- U6 o
Means (Compare means), 均值-均值比较3 I# K2 H# p8 ^
Median, 中位数
4 j F3 S1 e. v. ^$ hMedian effective dose, 半数效量
! B& O o' F0 O; p* ^- eMedian lethal dose, 半数致死量
8 T& @1 i( {8 c2 JMedian polish, 中位数平滑' W8 J" G. Y7 d; L* r T9 A8 Y) @
Median test, 中位数检验
& |! [- W+ S! c5 T* `7 mMinimal sufficient statistic, 最小充分统计量
4 ]$ _) N# G1 j& U2 b& e: jMinimum distance estimation, 最小距离估计
5 V; @1 @; a; G# i( t- R% a$ V; cMinimum effective dose, 最小有效量
9 {8 O3 f7 k. y/ nMinimum lethal dose, 最小致死量7 U. z! ^7 X) D6 u7 s
Minimum variance estimator, 最小方差估计量$ Q$ C! V7 z. X5 {6 p1 D7 |
MINITAB, 统计软件包
) b. W& ]' K2 q0 O+ hMinor heading, 宾词标目
, }- p. G, p- w! R( h/ j6 O7 N- F. FMissing data, 缺失值
6 |" q1 h2 {& xModel specification, 模型的确定' k& _1 R* D, m# F0 V1 v+ X
Modeling Statistics , 模型统计
% v( q' D. \4 H* | W; c' aModels for outliers, 离群值模型
0 m& w% j# m: t5 B3 @, h: b# aModifying the model, 模型的修正' J# D E- n5 l- n
Modulus of continuity, 连续性模# w, W" T+ z+ |2 u
Morbidity, 发病率
! B; [" |- S1 x% @+ m" ]8 `+ }5 X" [Most favorable configuration, 最有利构形' v9 x% W7 b! p
Multidimensional Scaling (ASCAL), 多维尺度/多维标度
4 `# E r" e1 ~9 k4 hMultinomial Logistic Regression , 多项逻辑斯蒂回归
9 B' O9 i$ [# h! q" G2 BMultiple comparison, 多重比较
! D0 ~, h# R2 [Multiple correlation , 复相关
L7 Y) U9 W9 x+ F( T- _Multiple covariance, 多元协方差" P) P1 o& j. S
Multiple linear regression, 多元线性回归" |* L! w, ]9 J. ^9 B
Multiple response , 多重选项
1 k5 T# _$ j9 Z3 pMultiple solutions, 多解
/ B- F7 F& P. b" }' TMultiplication theorem, 乘法定理' }! y; `: B( G5 J$ r& M* k& |
Multiresponse, 多元响应0 Y: T4 G- @+ X, z0 H: m# @
Multi-stage sampling, 多阶段抽样
3 D, v, F0 s& m# j; ]* l1 \Multivariate T distribution, 多元T分布
% L# r7 O# [9 ^# ^2 K5 ZMutual exclusive, 互不相容
* I; X, b4 i' ?2 DMutual independence, 互相独立8 R2 ?( [0 v2 I( \0 P
Natural boundary, 自然边界, T1 L" H' ?" O4 ?2 p0 _
Natural dead, 自然死亡
+ g5 z+ {' D9 c9 L* X* GNatural zero, 自然零( V4 {1 i. C+ E: h0 q: U
Negative correlation, 负相关
/ e2 B& @; @7 x% k5 eNegative linear correlation, 负线性相关
% y. D {* M' H! H& |6 MNegatively skewed, 负偏3 ]8 O) V, I- r6 Z
Newman-Keuls method, q检验
. C4 o8 l5 H, A8 }NK method, q检验
: w1 `2 U) U! I+ u( DNo statistical significance, 无统计意义
' ]1 F0 n% [7 k$ x) Z- ]+ YNominal variable, 名义变量
$ m7 w. s& ?3 `. q' c- i! t! QNonconstancy of variability, 变异的非定常性
# Q1 Y/ R. k) Z* `Nonlinear regression, 非线性相关/ a5 O7 j5 l* F* _3 i
Nonparametric statistics, 非参数统计( u6 S$ o% z3 a+ g; d d
Nonparametric test, 非参数检验
7 @0 Y9 Z- J/ i: F) @1 @Nonparametric tests, 非参数检验0 L: t9 E6 w' G0 Q9 ~+ G) w! |
Normal deviate, 正态离差- N3 b! ~+ D' R- U9 F
Normal distribution, 正态分布+ p* r) i' j" N
Normal equation, 正规方程组, e: [. ~9 T: P1 l. B3 J# O0 b/ A
Normal ranges, 正常范围
. f* _6 L, z+ S9 [Normal value, 正常值
. u; F' [% l, X5 S9 Q& q' ^ Z2 sNuisance parameter, 多余参数/讨厌参数9 r9 u) r6 I! r4 [$ R
Null hypothesis, 无效假设
' N# \6 w7 z6 D# mNumerical variable, 数值变量' N% E ?" y. H" ~8 D
Objective function, 目标函数. y D* H j% H+ ?0 K
Observation unit, 观察单位
( v2 Z7 n2 }8 s9 x) IObserved value, 观察值
5 O, b* t: @$ y1 n. n6 j7 m! vOne sided test, 单侧检验! n8 t# Q7 Z' d& }/ }
One-way analysis of variance, 单因素方差分析* H: W5 K* d) y
Oneway ANOVA , 单因素方差分析4 ?9 b! j. W# F, b! i: u( w
Open sequential trial, 开放型序贯设计7 o1 F6 o* m5 f/ \
Optrim, 优切尾# \+ G; k8 `7 [6 W8 u
Optrim efficiency, 优切尾效率
' a- m+ h# i# ~. y+ zOrder statistics, 顺序统计量
T- _& q2 j. J: b4 O$ h& POrdered categories, 有序分类
; L8 u5 w, ]2 P9 Q0 z/ ?Ordinal logistic regression , 序数逻辑斯蒂回归 m7 G) E$ ]- k) W5 Q
Ordinal variable, 有序变量
6 `+ g0 ^5 J1 R: M; z7 w( `Orthogonal basis, 正交基
. n' \; z% d% GOrthogonal design, 正交试验设计8 q4 _7 E2 p' ], ]
Orthogonality conditions, 正交条件
0 Y. V6 I; Y5 \, o0 Y+ {1 ~3 n. eORTHOPLAN, 正交设计 ! U) k# m2 _0 C' ?% P0 P
Outlier cutoffs, 离群值截断点$ A6 g; V |) w1 h) G2 ]
Outliers, 极端值; s1 k9 c/ z1 m' F/ T. v( a
OVERALS , 多组变量的非线性正规相关
7 d$ \0 {# }* a9 P2 `7 b9 i9 N2 jOvershoot, 迭代过度. c) a4 ~' v$ e" N+ T
Paired design, 配对设计0 _; j/ n* S# Q. b1 r8 q# k1 D1 ~
Paired sample, 配对样本
0 Q9 M" h. ~* h5 c$ [" l- {. tPairwise slopes, 成对斜率
& |" [" q' |7 _) y O: m2 K% w! YParabola, 抛物线$ T9 G% \& o* s2 F n
Parallel tests, 平行试验
( c5 i, }2 T$ Q2 h2 x- `Parameter, 参数5 L; j" V3 v( u! f7 r/ g
Parametric statistics, 参数统计
/ g$ c9 g9 w5 i5 D9 pParametric test, 参数检验) w% @3 }- R# T5 D9 @
Partial correlation, 偏相关$ N$ d, u1 U) @1 k) D0 w% h
Partial regression, 偏回归/ t6 }- a- O4 T, G% P7 s
Partial sorting, 偏排序# Z0 o! x+ T3 x
Partials residuals, 偏残差
' b0 X9 ~! v/ S' M K, m7 z! {Pattern, 模式
* ?% D) H7 j& _+ j0 X5 j; XPearson curves, 皮尔逊曲线
' g3 _! r9 p' E! Z7 GPeeling, 退层$ P. x4 u: U1 K5 ?( f( b
Percent bar graph, 百分条形图
; {" w4 B3 I! u% ~0 }0 k4 JPercentage, 百分比
2 t% r; W$ b1 O) @6 Y% vPercentile, 百分位数. m- a! d9 m' J7 V# E, p3 e9 }; a3 T
Percentile curves, 百分位曲线
. V0 c( }" I% D( e& a/ J* f+ r+ ~Periodicity, 周期性
4 W) J c- x4 y" c+ t- nPermutation, 排列
: N* ~) P9 c% i8 i8 d Y dP-estimator, P估计量
* D3 U0 s3 C" oPie graph, 饼图) V2 S" E! u' `* b, g, q) O
Pitman estimator, 皮特曼估计量
& |9 V! B) f( F/ u. D7 P- MPivot, 枢轴量
# a5 V3 E! w+ d" c1 ^Planar, 平坦* F1 L; j* w0 M, {0 J/ D2 v. \
Planar assumption, 平面的假设
9 F1 p! V7 V' [; |4 L* b3 mPLANCARDS, 生成试验的计划卡; |+ K3 b& ^3 q" j2 g) t
Point estimation, 点估计9 c9 ^& [+ e0 e8 o Y; _0 i
Poisson distribution, 泊松分布8 R* D& p8 E, B$ t4 g# x$ `, |) l# g
Polishing, 平滑& Q) h: I1 c0 r
Polled standard deviation, 合并标准差
& D* g2 R2 B: @3 ~1 PPolled variance, 合并方差
" h7 |# \4 j+ fPolygon, 多边图( n7 {/ b2 X& ^* s' u C. x
Polynomial, 多项式
$ g5 G, Y* @/ u- ~: n/ kPolynomial curve, 多项式曲线
8 a! m8 F# _: G) \6 h3 n6 c: iPopulation, 总体
& ~ O1 o7 V5 O/ yPopulation attributable risk, 人群归因危险度+ B) m+ ]4 s' x; X6 `
Positive correlation, 正相关
2 D' q) e: k; DPositively skewed, 正偏" L4 s5 }6 i6 {5 o9 S6 P% c& A5 J
Posterior distribution, 后验分布$ r; O) q9 }% q
Power of a test, 检验效能( v# F5 E& w. h: U u. e
Precision, 精密度
6 r9 a0 `9 o j& X4 cPredicted value, 预测值1 ~7 j0 \; F/ ^
Preliminary analysis, 预备性分析7 M; |& y) W- W) i; `
Principal component analysis, 主成分分析% w' W8 b; `7 v9 j
Prior distribution, 先验分布5 t+ l9 f% c$ w# I' F3 k M
Prior probability, 先验概率
1 X; l3 Q5 z. b$ p6 k% F$ V8 ZProbabilistic model, 概率模型( f& b" M& l& Y/ }8 L
probability, 概率7 _9 A) j6 H3 T/ Z& v" C `
Probability density, 概率密度
* H. [& ^$ _" `5 @2 j% x3 s% uProduct moment, 乘积矩/协方差3 ^0 h' E; J' {5 ?1 A$ i
Profile trace, 截面迹图3 M+ i7 b$ l$ u) _/ I7 t
Proportion, 比/构成比- i5 u2 d9 i. q- n
Proportion allocation in stratified random sampling, 按比例分层随机抽样3 U: o: d+ M) l; r" q
Proportionate, 成比例
% G. F* T4 E. R- V) f1 qProportionate sub-class numbers, 成比例次级组含量& i0 b0 g+ j6 ^( b/ O7 k
Prospective study, 前瞻性调查/ X% h r3 q; p9 x
Proximities, 亲近性
: _! Y) K/ |, T3 ~, \3 SPseudo F test, 近似F检验
+ F" K0 o) X: y6 F9 c2 Y+ cPseudo model, 近似模型
& z6 S* }5 V: R" SPseudosigma, 伪标准差6 J; g7 w! e3 b5 X# F+ ^" G/ q
Purposive sampling, 有目的抽样0 W0 ~6 O' {" C$ x
QR decomposition, QR分解
% m& F; Z# E$ i @0 k4 S1 e: y, D8 F+ aQuadratic approximation, 二次近似. R% u8 A* t* O5 H! f* A
Qualitative classification, 属性分类
4 s. a5 O0 S! F3 ]$ yQualitative method, 定性方法
% B* V8 ^% s/ nQuantile-quantile plot, 分位数-分位数图/Q-Q图
, y0 J w& V7 J+ J+ o. C$ CQuantitative analysis, 定量分析
$ h1 p0 f7 P% L9 B7 @2 WQuartile, 四分位数- d7 z; Q5 D0 m* ~1 V5 m
Quick Cluster, 快速聚类% y+ y8 v2 \# r2 b4 S; x
Radix sort, 基数排序( g. Y4 L1 Y# ~ o
Random allocation, 随机化分组1 M: R6 L7 ]3 q
Random blocks design, 随机区组设计2 t' j" h8 Z3 ~ w
Random event, 随机事件' E3 Z0 d0 o: g4 ]/ g# C3 j n
Randomization, 随机化$ P1 ]' x6 j% P7 ~, A6 W2 g
Range, 极差/全距
! C% e5 L$ ?3 LRank correlation, 等级相关8 r. w5 q& O0 v; h( J
Rank sum test, 秩和检验
' u, p- X6 T6 k% _0 _Rank test, 秩检验3 Y5 `) `# y, G
Ranked data, 等级资料
6 I! c4 g% Y5 J% O! q* aRate, 比率0 f% ^" T- s* B- O% h% i
Ratio, 比例
7 d& [6 ~* R1 n( n- @' CRaw data, 原始资料
2 ?7 F( Q8 L9 YRaw residual, 原始残差4 }6 n- [% m+ Y- c. O: {/ b
Rayleigh's test, 雷氏检验
) W7 g5 l3 R! \) o, ^Rayleigh's Z, 雷氏Z值 * Q1 W( G1 u' o. f9 n
Reciprocal, 倒数+ c) ~+ g) G- X X. F' `
Reciprocal transformation, 倒数变换1 m4 H7 m, y# w x3 n
Recording, 记录8 ]' H/ |2 M( v2 c1 N8 q% v/ G
Redescending estimators, 回降估计量
5 I- `3 P* q' }Reducing dimensions, 降维* G1 s# c8 a+ D
Re-expression, 重新表达
6 j9 g$ k% J" A& e. nReference set, 标准组
( l' b3 S A+ q: n# ?/ rRegion of acceptance, 接受域4 A8 w, A2 w" x8 T! h* [: `* Q6 w
Regression coefficient, 回归系数
: s3 b' R7 }. A! SRegression sum of square, 回归平方和2 R% i# K' S1 B- `: V% }
Rejection point, 拒绝点
. i/ m) g: d9 T3 XRelative dispersion, 相对离散度
, w2 ]5 J1 O$ e& T6 gRelative number, 相对数0 [2 m" K0 o" u- k3 j1 V
Reliability, 可靠性- w+ L* W0 v- p) O* Q/ q
Reparametrization, 重新设置参数0 B+ W9 l# s/ {! a" d
Replication, 重复; c: ]9 H" c9 t$ y
Report Summaries, 报告摘要
9 f% B' A$ X. I0 L3 Y8 _Residual sum of square, 剩余平方和
# L) b, U7 Z Q$ ~# h, LResistance, 耐抗性: A( N0 X; I# i
Resistant line, 耐抗线
0 u# ?. S( z7 i& X6 T% t9 IResistant technique, 耐抗技术# O" A* C0 L% l
R-estimator of location, 位置R估计量
5 Y0 h% M* x8 l, }/ {! f! M& A& ?R-estimator of scale, 尺度R估计量# B3 C# i P' e3 E, S( ]/ }9 O- e# q
Retrospective study, 回顾性调查
0 l4 I ]/ K1 {4 s" |0 E5 O- yRidge trace, 岭迹
* M4 ]/ y1 o6 }1 h$ U3 iRidit analysis, Ridit分析% P w& y) h8 L
Rotation, 旋转) t( w$ z4 _. D+ n$ M. q
Rounding, 舍入
3 w+ Z# K5 c y0 f v- E, E+ `5 v, ERow, 行2 ~* G9 z% B' R
Row effects, 行效应
& r! B. `1 f: H) FRow factor, 行因素0 S8 b: ^, @1 Z: F9 P* b5 @
RXC table, RXC表" J& P) G: O9 F( n
Sample, 样本
8 M0 u# B3 ?+ w! N6 d* {. eSample regression coefficient, 样本回归系数; r: z! c1 Y8 \- O7 W, u
Sample size, 样本量
. q7 A- A* o0 D1 m) K# NSample standard deviation, 样本标准差# f; ?1 r% E- p0 A+ t
Sampling error, 抽样误差 {% e. Z$ G3 z! E
SAS(Statistical analysis system ), SAS统计软件包1 V4 ~% ?* R# W+ g ]6 Z( I! E1 T& F
Scale, 尺度/量表
4 ]1 c7 |; `4 r' b1 p! n7 pScatter diagram, 散点图
0 u% M, U0 h( k6 h' }) \* _% RSchematic plot, 示意图/简图
7 U, B/ z2 C7 ~9 ^# {. vScore test, 计分检验
- |8 O2 B" ?" J$ Z" I4 p; dScreening, 筛检
1 X% K+ @% t; h' U/ s8 oSEASON, 季节分析
# Q9 V3 T4 ^+ }) N$ s: \9 ^* R! }Second derivative, 二阶导数1 K' X: ~$ X" m, C f/ q% r) R
Second principal component, 第二主成分
5 [$ r: z- W. L7 eSEM (Structural equation modeling), 结构化方程模型 " }" s2 z |% j+ T `
Semi-logarithmic graph, 半对数图& W8 }0 `- h3 f6 p( `1 g' i
Semi-logarithmic paper, 半对数格纸
f/ U' [$ b, w/ W: k/ G- ySensitivity curve, 敏感度曲线. l$ P7 q) }, r m& ?
Sequential analysis, 贯序分析
) ~. U: K4 q) p& J% q, v5 vSequential data set, 顺序数据集
+ u! x4 z0 y3 ` F2 y7 MSequential design, 贯序设计
+ G% {7 O" i5 J$ b! r) hSequential method, 贯序法
5 C7 H8 g% s+ U- r: J3 tSequential test, 贯序检验法2 A0 M4 r8 { W' o, M
Serial tests, 系列试验/ X3 f0 Y$ g4 h7 k5 B) e
Short-cut method, 简捷法
! {9 W U$ ?' xSigmoid curve, S形曲线
$ h/ J1 P3 |, d3 |Sign function, 正负号函数% s6 ?* P, q/ n# o) i
Sign test, 符号检验! A1 u) T+ p, L; g3 F* F& H
Signed rank, 符号秩
5 J" O, A& N; r0 ]. e5 |' K# hSignificance test, 显著性检验% o1 _ y5 ]: }) H9 r
Significant figure, 有效数字
; h7 t8 B: C2 J- g: |) VSimple cluster sampling, 简单整群抽样
, }( N2 [+ @* B8 F& S, ?Simple correlation, 简单相关
4 \* t% H9 b/ z! Z* oSimple random sampling, 简单随机抽样* W7 G r. m. {5 U- g
Simple regression, 简单回归
! E& B/ d5 y6 q2 Lsimple table, 简单表+ u8 g. \" i' L) Q, V6 U4 ]/ {
Sine estimator, 正弦估计量
1 a4 t* q* Q3 K& ^( ASingle-valued estimate, 单值估计6 k$ O% v4 I6 ~/ `+ H% S( [
Singular matrix, 奇异矩阵5 r. j; g6 k1 N2 Y; K$ O
Skewed distribution, 偏斜分布* j9 W2 |* I6 [6 G1 ~# N
Skewness, 偏度
" p# m6 B3 W$ ^- X2 kSlash distribution, 斜线分布- k) j: {, i% N u) _5 Z2 f
Slope, 斜率7 b! ~' ?7 U' ], U7 C$ Q
Smirnov test, 斯米尔诺夫检验
4 _& s& g+ c- _Source of variation, 变异来源; H0 O/ ~- I3 o! a u# M: j" f
Spearman rank correlation, 斯皮尔曼等级相关) P1 q! {+ w9 V, Z" w
Specific factor, 特殊因子
0 t1 r% d/ k! s4 wSpecific factor variance, 特殊因子方差
a7 A/ X+ e3 B0 X" k8 {Spectra , 频谱
' n; S5 G3 L* z) T+ B- USpherical distribution, 球型正态分布; _& U7 K; Y$ ^
Spread, 展布
. _# {6 T2 k) YSPSS(Statistical package for the social science), SPSS统计软件包
! U M* Z" y. c1 f' b4 gSpurious correlation, 假性相关
! U2 p% I. n* u) t1 aSquare root transformation, 平方根变换
8 z! S2 Y8 z2 {) r" m8 pStabilizing variance, 稳定方差
. f; ]7 \6 F- @0 P4 C' Z' eStandard deviation, 标准差
( y/ o% \' B/ [: C$ k( VStandard error, 标准误# |' `9 x1 ?4 e2 w/ w: a0 a! F
Standard error of difference, 差别的标准误+ O4 Q0 F# X" h: m( h7 s
Standard error of estimate, 标准估计误差! b4 n5 h2 a L- n, w+ C; @
Standard error of rate, 率的标准误" h, a3 m# m0 G1 A
Standard normal distribution, 标准正态分布
) C9 v- O1 P" `7 [/ t9 h+ ZStandardization, 标准化0 U! U" s) p( F$ t! e
Starting value, 起始值! V, P0 {' F/ x" w2 r
Statistic, 统计量
; ]& a2 W" e. ^Statistical control, 统计控制
+ g0 U! x! F" YStatistical graph, 统计图
6 Z( P' W. c5 K) K2 Y1 P) \$ R+ MStatistical inference, 统计推断
% i" h& b @; I8 [) H6 w7 {6 HStatistical table, 统计表
* M8 q; I1 N3 L- OSteepest descent, 最速下降法; {0 V& l; C. c5 O
Stem and leaf display, 茎叶图
& D: |$ m' j9 K5 ^; TStep factor, 步长因子
5 G, G* I2 p: I3 o# RStepwise regression, 逐步回归/ ]' q) `" t8 f( W: B! V
Storage, 存
: C' ?; k+ p) c' F) W/ Y" t& LStrata, 层（复数）' i+ v$ ^! y' R9 A# Y6 e
Stratified sampling, 分层抽样
% S3 {/ Q4 W% d$ v8 ?& b, YStratified sampling, 分层抽样2 a6 a! d, O) N u; ^; t
Strength, 强度9 ^, S9 {6 g. p. o3 R
Stringency, 严密性2 \, J& A" D8 `% G9 o) Z/ f
Structural relationship, 结构关系
# s# l; O+ F0 D8 gStudentized residual, 学生化残差/t化残差
& G4 m& a2 d( @- X$ VSub-class numbers, 次级组含量2 m, w; R0 _; P/ S0 r# E. l
Subdividing, 分割
}* W! j a9 y/ q M8 dSufficient statistic, 充分统计量
& w- s) [/ U! y" I+ n9 m! e" P# \Sum of products, 积和
* ]8 M/ b( L5 k4 aSum of squares, 离差平方和6 }6 u+ s( N% C( Q: f ~
Sum of squares about regression, 回归平方和
) X2 A- w: R9 j {Sum of squares between groups, 组间平方和
R& ?8 p# a, U: |; c9 ASum of squares of partial regression, 偏回归平方和; F; y! k! E1 i; M9 _- f# q
Sure event, 必然事件
$ i$ Y+ W3 U+ m( _Survey, 调查1 A; D! P* \& C9 m/ f. @
Survival, 生存分析
' f* z6 V2 C2 c6 e' S1 L7 I# CSurvival rate, 生存率
3 {5 n8 Q0 _, [3 g4 rSuspended root gram, 悬吊根图
* v6 P2 @+ t, v- K% k$ pSymmetry, 对称
& \9 n2 A, g- b r' k' r8 xSystematic error, 系统误差
3 r' v/ U( x3 v- D4 dSystematic sampling, 系统抽样+ \. U3 T5 S. p9 l' x( f
Tags, 标签& p( `( ?! A0 ]# S
Tail area, 尾部面积
# n1 R: f3 T, d! w, P4 \Tail length, 尾长
( J- g0 F# J* S: p: VTail weight, 尾重
$ k. l; V1 h: N# A$ P/ wTangent line, 切线
% Y( e: e! V( ]) cTarget distribution, 目标分布
! {. g* i( P9 k, y, S; Y2 T8 ~/ ZTaylor series, 泰勒级数' U% E* j7 E4 v1 Y: s
Tendency of dispersion, 离散趋势
e$ m! i O& J/ fTesting of hypotheses, 假设检验5 [" R9 ]+ _% d/ l( H" Q ~6 n
Theoretical frequency, 理论频数: K% c% X- X0 J
Time series, 时间序列
7 `! N# E2 @. rTolerance interval, 容忍区间
1 }+ q2 s2 ~) |8 O& q, L* {Tolerance lower limit, 容忍下限- b3 m+ n$ d u
Tolerance upper limit, 容忍上限
8 h0 `- Z t5 k/ O8 T9 ?Torsion, 扰率; ]6 [: E* A1 y1 w+ V
Total sum of square, 总平方和( r' o+ C; ^4 T1 e- h* g
Total variation, 总变异
! |8 q. B. G/ U HTransformation, 转换
! P1 m& b4 [* z3 a9 T5 q2 |Treatment, 处理
, [6 W2 v8 \6 x/ E& WTrend, 趋势) o! i, d5 q2 g/ u, M* U
Trend of percentage, 百分比趋势* [5 g S; A$ n9 ^; f: @
Trial, 试验
7 C% U3 O8 @" s p! b3 aTrial and error method, 试错法6 [5 b; X3 G. w/ X# S
Tuning constant, 细调常数
% {% b7 I! V$ ~( ?9 i( tTwo sided test, 双向检验6 D- V: r; [) n! ]5 i
Two-stage least squares, 二阶最小平方
/ r9 c5 ] a" s/ I2 O6 HTwo-stage sampling, 二阶段抽样
4 Y+ r: g* Y( I; Y" k3 `Two-tailed test, 双侧检验' B6 F# K8 u* G
Two-way analysis of variance, 双因素方差分析2 p9 v9 k, M" l1 L5 i$ Q- J
Two-way table, 双向表 ~: L+ t6 ?8 a
Type I error, 一类错误/α错误4 n4 K C" _2 V6 Y
Type II error, 二类错误/β错误
8 w, L( w9 V0 D, w& aUMVU, 方差一致最小无偏估计简称9 H5 O, I R' ], i* U* T6 ?" Z
Unbiased estimate, 无偏估计
2 z) T: B, K) M2 @9 L3 nUnconstrained nonlinear regression , 无约束非线性回归
" ?0 g4 d8 I3 Z* | `$ y* yUnequal subclass number, 不等次级组含量6 _. x" V* [1 I! I5 v. W" }
Ungrouped data, 不分组资料
8 z F5 T* G# `5 DUniform coordinate, 均匀坐标
/ k9 |+ Q* W& [1 oUniform distribution, 均匀分布
4 J% V& ^. T. U1 ^( RUniformly minimum variance unbiased estimate, 方差一致最小无偏估计0 i; Y; S3 H k- y9 A& S x9 W) |
Unit, 单元1 j0 D, T5 W7 F5 k+ J T6 q, [
Unordered categories, 无序分类
1 u0 O( B/ m% I3 w4 Q) |+ C5 A% `1 NUpper limit, 上限: N- t* L: W _" Y' `( F
Upward rank, 升秩! c0 B- w& E! w
Vague concept, 模糊概念
* O v9 T8 p( `* X8 o* DValidity, 有效性# V3 g( R) e8 ]& Q, \
VARCOMP (Variance component estimation), 方差元素估计
3 @: _) F/ F' Y4 J( Z6 Z" W* n& Y* H: fVariability, 变异性
0 O4 A, S4 q( T2 ^! E6 w7 }Variable, 变量) j2 z: Q" Z W4 i4 F5 K! y8 o
Variance, 方差
, U; T) p! R% _# A1 N6 lVariation, 变异; x$ Y! |+ [4 E. o3 n
Varimax orthogonal rotation, 方差最大正交旋转
, B2 J- t/ ~5 E" k1 NVolume of distribution, 容积: S( \. Z: _8 n' b7 y8 h
W test, W检验9 r) {0 F6 L! S3 t1 E) v
Weibull distribution, 威布尔分布5 U/ d, ~# Z. x3 T7 E+ e
Weight, 权数
, e' T# p, o5 a" |7 @% B% \: y W) q4 X' cWeighted Chi-square test, 加权卡方检验/Cochran检验
3 |3 T* ? |* d$ I OWeighted linear regression method, 加权直线回归9 L/ p, w2 B' k
Weighted mean, 加权平均数
- N: X' b5 L2 N6 a" c2 y" fWeighted mean square, 加权平均方差
1 f7 D3 T1 f: `1 q$ p! IWeighted sum of square, 加权平方和 w6 E% U) k; w7 G2 I+ Y
Weighting coefficient, 权重系数. O. a/ R$ _ j; O% }
Weighting method, 加权法 * {$ z. o7 Q( k3 j0 p
W-estimation, W估计量) s3 A' L( X, N& a
W-estimation of location, 位置W估计量
3 O3 G' l/ J7 _! t0 M" zWidth, 宽度
5 o' D: q8 u7 p1 v& b9 cWilcoxon paired test, 威斯康星配对法/配对符号秩和检验# ^* {, D% R" A/ A5 I
Wild point, 野点/狂点7 G5 c% S R% P+ z- _( a9 x9 S1 m
Wild value, 野值/狂值
" q; j2 _5 Q O6 JWinsorized mean, 缩尾均值
& |3 i; g! y0 I* E: G6 jWithdraw, 失访 7 ~) c& {5 t( t+ _& P$ S
Youden's index, 尤登指数* A; l$ b | R! T
Z test, Z检验. V2 q4 C2 r; F' k
Zero correlation, 零相关
- E6 z! q5 @+ @# e3 \1 _Z-transformation, Z变换 |
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发表于 2009-1-6 22:05
