|
|
Absolute deviation, 绝对离差
1 x$ ]/ @3 @; pAbsolute number, 绝对数
* i/ J+ O; Y( j# a) {Absolute residuals, 绝对残差
/ x @; M: B# a0 g# TAcceleration array, 加速度立体阵- ^8 d' K$ F: ~9 D* E& I* a i
Acceleration in an arbitrary direction, 任意方向上的加速度
8 y/ p k; z0 n. S+ I: eAcceleration normal, 法向加速度
- k8 w, O0 _$ K' S7 J* M0 MAcceleration space dimension, 加速度空间的维数3 I w4 Z3 ^5 _/ x2 z
Acceleration tangential, 切向加速度
$ m* c( E1 @( h* r* A' o6 H9 {Acceleration vector, 加速度向量
' I, K( G5 ~3 Q* G7 N4 r9 oAcceptable hypothesis, 可接受假设" ~* y$ }+ i! B* f: ? K B" K1 O7 G
Accumulation, 累积
% U- q+ S; |" S. ]9 {( t! \Accuracy, 准确度8 A- e7 N$ m, C, x
Actual frequency, 实际频数
. m8 n" K% H( o' a% ~) jAdaptive estimator, 自适应估计量, R) P3 q1 B4 H: Z
Addition, 相加
; j( Q; k) K3 A iAddition theorem, 加法定理
" a9 T. @/ E- l; G. xAdditivity, 可加性
8 G0 _0 L7 A$ |6 [: UAdjusted rate, 调整率
/ v) b/ v% U9 ?) ?4 `9 F# `1 sAdjusted value, 校正值: z2 I6 i, Y& v e( ~! j8 z" `
Admissible error, 容许误差
( z1 @. h3 G& G; XAggregation, 聚集性
# r- g1 y1 a3 J& aAlternative hypothesis, 备择假设
; P+ d6 h$ e4 k: N; [Among groups, 组间
- Y- ]" _+ w( K; k' oAmounts, 总量! r$ N8 I( ^* `0 a7 C' K
Analysis of correlation, 相关分析
, V5 a. Y! H2 A0 k7 b, v2 _/ [Analysis of covariance, 协方差分析9 z1 R" j; D' ~3 I
Analysis of regression, 回归分析9 h4 \& J' Z* I8 a- E- s* K
Analysis of time series, 时间序列分析- A9 Y' G$ u: W, J) j! g. M/ F
Analysis of variance, 方差分析5 g0 }7 ^$ P2 y5 M
Angular transformation, 角转换+ |( o& ?1 I, u( L8 i$ R8 @6 f% n+ B
ANOVA （analysis of variance）, 方差分析8 G3 H/ T* h9 r( D+ m/ m% w
ANOVA Models, 方差分析模型
7 v( q/ i& j! O/ @' pArcing, 弧/弧旋, F% q- n3 x( ?0 _
Arcsine transformation, 反正弦变换. u3 H7 T" \+ {" y$ w' ]6 J
Area under the curve, 曲线面积
/ `8 w& K x+ H0 q7 k& I" \AREG , 评估从一个时间点到下一个时间点回归相关时的误差 . w) ]( i/ z7 ~( x
ARIMA, 季节和非季节性单变量模型的极大似然估计 4 p5 _+ y8 M; N7 O) W, Z4 c
Arithmetic grid paper, 算术格纸
6 i7 t+ \- A% O/ Z, [+ P! e7 E7 V! ~, {Arithmetic mean, 算术平均数- A! _+ a* g; _ g
Arrhenius relation, 艾恩尼斯关系0 L8 w" Q& |+ X+ H2 @8 t5 X' T
Assessing fit, 拟合的评估. n" i6 R- n( P% ?) i/ `7 R4 }
Associative laws, 结合律
9 f4 u, ]1 t9 J7 G p, \Asymmetric distribution, 非对称分布
, v& y9 Y& o3 E- Y# ~) |Asymptotic bias, 渐近偏倚- v7 |" a4 O8 G; d# B
Asymptotic efficiency, 渐近效率
9 P. K- ?& v8 F+ Y7 VAsymptotic variance, 渐近方差
8 F, R4 _% J. S0 `' _0 RAttributable risk, 归因危险度
& ^6 B1 {2 X2 G Y' V' TAttribute data, 属性资料
, D f5 ]8 Y& G; z8 _/ X+ HAttribution, 属性' ]6 h. W7 T2 e6 p* O, _0 Q
Autocorrelation, 自相关
' z$ L: U: O3 c, Q9 w: BAutocorrelation of residuals, 残差的自相关5 B1 q7 Y4 Q* e$ p
Average, 平均数
! ]5 g( j% E% W$ J- T& O# i( [Average confidence interval length, 平均置信区间长度
" O+ ?( l) P) Y% TAverage growth rate, 平均增长率6 j! T1 @, F' @' L# C7 t7 Y1 U
Bar chart, 条形图+ A1 J P, E' r) }' k0 }1 ^& \' D
Bar graph, 条形图/ A _( T5 a3 D- Q- i3 P
Base period, 基期5 N( b# z* W1 @
Bayes' theorem , Bayes定理
0 V! S& N& T J- ~: P4 a" LBell-shaped curve, 钟形曲线7 `- w! F" j. u( f( c: L2 J
Bernoulli distribution, 伯努力分布- n: U: D: u9 Y! z" s
Best-trim estimator, 最好切尾估计量! n. M( `5 \* R9 o: J1 P8 g0 D% X
Bias, 偏性- Y7 E4 E2 ^! u" n/ J# J( A' F
Binary logistic regression, 二元逻辑斯蒂回归
$ x1 N N" x5 `( j' `" cBinomial distribution, 二项分布
\" V" R4 x5 {3 v9 \- u% jBisquare, 双平方1 i5 w- Q& [) x6 ?5 g5 @- n5 Y# K2 e
Bivariate Correlate, 二变量相关
( D. B7 {5 C' z* s! E. X5 DBivariate normal distribution, 双变量正态分布
# e8 W$ @0 O, Y. L0 v- ]. OBivariate normal population, 双变量正态总体
6 M9 Z/ ^, J w( w4 ?Biweight interval, 双权区间0 E( _* W5 R+ [* \0 r. Z& D
Biweight M-estimator, 双权M估计量5 F- \# z1 v8 F: e. F7 K2 Q/ K1 L
Block, 区组/配伍组
6 w) ^6 T9 e5 }! lBMDP(Biomedical computer programs), BMDP统计软件包% V) A5 N" ]' D! P( b& M6 Z2 E
Boxplots, 箱线图/箱尾图) W _: ?" o1 b5 r9 i. F. b$ _
Breakdown bound, 崩溃界/崩溃点 W- K, \* S5 _/ z
Canonical correlation, 典型相关
* b9 ]- R. i1 ?8 H1 NCaption, 纵标目
0 ~5 R' R0 S. y4 ICase-control study, 病例对照研究
3 J; { s2 |! v6 ^! M* YCategorical variable, 分类变量, ~2 t( Y. T% q
Catenary, 悬链线7 i: }; C7 n) O
Cauchy distribution, 柯西分布
& W; ?% f9 t) q @5 zCause-and-effect relationship, 因果关系9 p& n, M3 k/ P6 i1 b |
Cell, 单元3 V, \: M+ m+ c* b
Censoring, 终检( o5 H- I/ I: \$ G+ `
Center of symmetry, 对称中心
, A7 u4 F1 ^4 _& o" O2 } vCentering and scaling, 中心化和定标
& |( |) V2 J n* P9 i8 mCentral tendency, 集中趋势, b( v. D5 T" |4 y* S$ @, J
Central value, 中心值1 u2 a* Z0 s/ Y
CHAID -χ2 Automatic Interaction Detector, 卡方自动交互检测8 u4 j% G$ D4 P; Y: k, w
Chance, 机遇9 R2 u0 M1 m6 e/ x- w
Chance error, 随机误差
3 l7 o$ H7 Z* z% M8 Z. {Chance variable, 随机变量, b5 P$ F5 x+ [) Q, W! b
Characteristic equation, 特征方程4 _8 I. X0 a2 ~8 K
Characteristic root, 特征根' ~, J' ~! ^" Y
Characteristic vector, 特征向量, }+ r8 Z6 D. p, X" V
Chebshev criterion of fit, 拟合的切比雪夫准则
8 U/ ^2 @9 `" c6 F2 ZChernoff faces, 切尔诺夫脸谱图
1 L4 K1 q. d$ @- }9 i/ oChi-square test, 卡方检验/χ2检验
0 s: R6 @0 \. c6 F- H3 x K& e: a9 xCholeskey decomposition, 乔洛斯基分解' ^. N2 e2 ?* f" j
Circle chart, 圆图
+ L) S' _# p/ w3 w3 H! AClass interval, 组距
: a" S8 P3 o3 u5 \$ E9 ]4 wClass mid-value, 组中值/ _& Z% \ D! M s
Class upper limit, 组上限
( e9 t$ R$ R% A( BClassified variable, 分类变量
6 w' H1 {5 w# o' z G5 sCluster analysis, 聚类分析2 t- a0 |! z( F( x R* ?. J
Cluster sampling, 整群抽样5 k+ y' I' P* y. X# t" N' ^# o6 `+ t
Code, 代码
6 K5 ~' W; D' r8 u% ZCoded data, 编码数据0 n$ j# J- D0 I
Coding, 编码( c& @; _. n: w8 w$ C* | H) P6 s
Coefficient of contingency, 列联系数
+ N; w4 M$ L: Y zCoefficient of determination, 决定系数
( M$ b: i/ Q9 MCoefficient of multiple correlation, 多重相关系数3 D( k5 e! x: j$ [
Coefficient of partial correlation, 偏相关系数
9 ^7 B4 l5 j2 }0 s' D3 z% jCoefficient of production-moment correlation, 积差相关系数
, D4 O8 ~' i; t N1 [. h {Coefficient of rank correlation, 等级相关系数
; u8 w: M1 `) x) ]- w* H m$ V; v. GCoefficient of regression, 回归系数
) F" S+ A5 t: Q7 t# h* V) @Coefficient of skewness, 偏度系数2 g8 s2 e; t) J T% c
Coefficient of variation, 变异系数
2 f6 y; y" P% [- ]Cohort study, 队列研究
& m3 P$ l0 B" \8 V- ?* AColumn, 列. l5 r y; p5 w( b+ ?
Column effect, 列效应
7 _/ J& B* ]" l/ R* \2 q1 k- gColumn factor, 列因素
7 [: W$ \. a- p4 F) f0 DCombination pool, 合并7 S6 U$ I0 P+ A6 N# d- j# m0 g. ^
Combinative table, 组合表
! a$ X* Y$ ]) Q! g$ r' O" r1 _Common factor, 共性因子5 l5 }0 z f5 n+ _5 q
Common regression coefficient, 公共回归系数$ C0 h: W+ C) B r: c( E
Common value, 共同值0 j* X/ v. Q$ X: }; z/ Q8 v( ^
Common variance, 公共方差/ B( O1 I% _% E6 x3 c) |& b
Common variation, 公共变异4 K8 o; D" K+ m, W& Y" |
Communality variance, 共性方差9 K% V& f1 h( Z/ l
Comparability, 可比性" @4 h" Z: } \: _, X: g) j
Comparison of bathes, 批比较6 F. u/ c3 ~1 U' m
Comparison value, 比较值
2 W7 s9 w6 V3 p- F& WCompartment model, 分部模型
) _- ^0 E4 P) G- o8 x$ \9 ]! YCompassion, 伸缩
' ? r) \) s4 b8 e7 LComplement of an event, 补事件
( n0 D- J3 B2 W0 v }9 _Complete association, 完全正相关6 w) d8 d/ `4 x w2 ?) P- U
Complete dissociation, 完全不相关0 c s$ u9 c, [9 K
Complete statistics, 完备统计量
3 t3 U+ l- `" N9 S: o6 WCompletely randomized design, 完全随机化设计7 l% e( [8 u7 I, m7 l, c
Composite event, 联合事件
& S7 U; O ]2 p6 Y8 T% dComposite events, 复合事件
/ S7 J/ y5 c6 s X" j; ]Concavity, 凹性- s# Q8 [" O& t
Conditional expectation, 条件期望
) u1 U+ ~5 a4 i" a) \1 o8 a W6 pConditional likelihood, 条件似然( S8 x0 Q3 I7 s5 ?' v& T' A' L3 l3 d
Conditional probability, 条件概率8 `9 C- ~3 s/ l0 G/ J/ W' U5 t
Conditionally linear, 依条件线性. U) o3 \1 e" n$ ?+ n8 g6 |& X
Confidence interval, 置信区间
$ P) l# K! y7 N' i; DConfidence limit, 置信限1 w$ ]2 J1 n2 O
Confidence lower limit, 置信下限
& V- q/ W3 p* d1 k. i9 E. F/ JConfidence upper limit, 置信上限+ p* N5 o5 S) N1 y* a) A* X
Confirmatory Factor Analysis , 验证性因子分析: r( |& H+ H% H* P) V) {
Confirmatory research, 证实性实验研究; C5 R V# [6 s, d, O
Confounding factor, 混杂因素
' G6 [8 ?) }" n6 h! @8 s$ U- FConjoint, 联合分析
( ]$ v; I) ]( g2 n- a U K% gConsistency, 相合性 d1 r' P W: d, y2 c0 A1 x
Consistency check, 一致性检验
. l- L X9 ?1 W4 }9 M( b7 ]Consistent asymptotically normal estimate, 相合渐近正态估计
" L, w( q+ v* q8 m& H' ?2 CConsistent estimate, 相合估计
$ m; G# K( ~" d4 f2 AConstrained nonlinear regression, 受约束非线性回归4 [+ e+ i1 b6 d+ X
Constraint, 约束
, U9 ]7 ]' g& tContaminated distribution, 污染分布
4 F# E4 K0 N3 EContaminated Gausssian, 污染高斯分布( t }. g0 H/ K$ j1 `2 C* I. E
Contaminated normal distribution, 污染正态分布
8 Z8 B- j" _4 V: O$ z5 O4 d( vContamination, 污染
: d' S5 H$ r$ k# DContamination model, 污染模型
~, S7 L. T% }7 y' ~3 QContingency table, 列联表
- s( e1 Y) g9 DContour, 边界线: H4 X' V5 Z0 T* g
Contribution rate, 贡献率 w* \" n; h n9 p ]0 Q# G
Control, 对照
" k% p! t$ j# h8 nControlled experiments, 对照实验
7 G# q5 c( ~' Q, ?4 P) s& g+ D& z" wConventional depth, 常规深度# l5 @3 w. L5 g1 N
Convolution, 卷积
, L( l4 Y/ \) u* C' PCorrected factor, 校正因子
! A# K/ D! {/ e, sCorrected mean, 校正均值7 H5 n( u3 R# Z* q: \
Correction coefficient, 校正系数
' J5 `" S! R8 l6 o6 ICorrectness, 正确性
" `" a6 p/ {7 M! s mCorrelation coefficient, 相关系数
) d' t1 q4 ]+ P: UCorrelation index, 相关指数
; ~: l, U# ^. I; T) u- r6 ^' m5 wCorrespondence, 对应
8 R$ Q6 o2 ^+ K$ f5 iCounting, 计数/ d: `$ j3 t& v' ]
Counts, 计数/频数
' D' o7 X3 k0 d! j. ` {Covariance, 协方差
; _. E2 ~8 u, BCovariant, 共变 4 ~3 r# l6 o; v! ~
Cox Regression, Cox回归9 c0 p0 N$ o4 a& Q
Criteria for fitting, 拟合准则, O+ b( d& M- l* ^! O$ z
Criteria of least squares, 最小二乘准则# V+ x0 S. J* @
Critical ratio, 临界比
7 t0 d! ]3 C. G! u) oCritical region, 拒绝域, M q. b& a7 F8 Z1 @4 s- t I& P
Critical value, 临界值
( W, _( K6 k) s. Z! C( bCross-over design, 交叉设计
3 T! B. l8 c# U7 P* \- M- N' Z2 A, u* e! ACross-section analysis, 横断面分析; V0 C# W4 S- V- ?; S' \
Cross-section survey, 横断面调查
! n# f5 d: {% }! P* wCrosstabs , 交叉表
$ a8 d. J9 y" Z1 i, cCross-tabulation table, 复合表
& T+ l+ n$ Y' m* p. U( G5 \Cube root, 立方根
. } G. v K1 ~0 {5 N5 v; i- oCumulative distribution function, 分布函数
; E& K4 y4 ?, q% O, w6 ^) v hCumulative probability, 累计概率 p! M8 `7 s9 F9 ~5 {' C
Curvature, 曲率/弯曲; }+ ?3 ] G) d" |% ]4 `5 Y
Curvature, 曲率( s' U8 \; u% K4 b: m
Curve fit , 曲线拟和
* b. j! g0 E5 T @ c4 \Curve fitting, 曲线拟合+ t# u5 U' [0 a3 f. h0 E; i
Curvilinear regression, 曲线回归
9 f. l* _ h, E/ i" jCurvilinear relation, 曲线关系6 h. |8 x" s' w( ^9 F
Cut-and-try method, 尝试法# i! r% m' t b6 I5 ] Y$ o3 H) c
Cycle, 周期
5 ?0 ]# Y( A" cCyclist, 周期性- E; Z# ?& z. w# k6 [9 f Y
D test, D检验2 {0 a6 `4 @7 ~0 y e/ V9 v$ O- ?
Data acquisition, 资料收集
4 I5 |5 t5 b2 v7 k! MData bank, 数据库1 g4 g$ m: y& t* {
Data capacity, 数据容量
5 G8 W9 G {5 t- w$ S! LData deficiencies, 数据缺乏
1 v6 ^+ w# J6 D5 KData handling, 数据处理
' ~# W% M4 n7 `% ~6 y" CData manipulation, 数据处理
I; B! L* H/ {* a0 CData processing, 数据处理% @' H: d+ ~4 @7 `. f3 w# z
Data reduction, 数据缩减; }- k. A0 ^& x" k
Data set, 数据集5 f$ s) T- i* k' s, }
Data sources, 数据来源
% z9 K ?3 h1 r2 D4 `Data transformation, 数据变换
' j3 l# P9 o+ cData validity, 数据有效性. k \3 D5 l* C9 @
Data-in, 数据输入
4 J* x+ |$ `3 O: ?- B- V$ |Data-out, 数据输出
% O* |# T# k; B/ xDead time, 停滞期
- s% b6 {+ S1 t4 ~% bDegree of freedom, 自由度
O, ~9 y( a; n( `0 G: u6 GDegree of precision, 精密度
b. [9 S+ c; l+ x6 s5 gDegree of reliability, 可靠性程度
+ _& k& e4 z8 M! m$ X- w9 XDegression, 递减
+ ^: E1 a4 X% |4 D" Q, tDensity function, 密度函数
- g: {3 p! B* Y# ~$ t9 uDensity of data points, 数据点的密度
/ |; J* t6 o" R5 V7 IDependent variable, 应变量/依变量/因变量4 N$ @) Z7 b/ k5 Z8 T7 R
Dependent variable, 因变量& V% L0 ^5 W( Y% r
Depth, 深度
& i9 C$ F% Q" p+ }2 ODerivative matrix, 导数矩阵
+ F% a+ Y! {/ ^: i0 {, w/ nDerivative-free methods, 无导数方法. z# E$ {* E& F" r" Z& `6 c+ M
Design, 设计 Q' c% S: Y4 [% b3 Q/ @& n0 C8 Q
Determinacy, 确定性/ o/ D, h( `$ E8 \( b3 T% Q0 _
Determinant, 行列式
4 {" M! n( p" N- w3 c5 n+ XDeterminant, 决定因素
& p( B8 ?; y$ X# M& R6 J! U/ `Deviation, 离差# S& Z9 Q5 T9 g
Deviation from average, 离均差$ \* T4 c8 X/ K7 ]" O
Diagnostic plot, 诊断图1 V5 Y8 D) w. z; d6 n& {
Dichotomous variable, 二分变量
1 N, Q, y" V% T0 @Differential equation, 微分方程1 I8 e. v: q4 H
Direct standardization, 直接标准化法
% C K# N. w- J" ZDiscrete variable, 离散型变量# Z$ J# I, o; ^- [
DISCRIMINANT, 判断 6 p' |0 ~1 i: J% Y7 _/ W( V
Discriminant analysis, 判别分析
# p- A; |1 z- u. J7 D& ZDiscriminant coefficient, 判别系数
; E+ |* Y* Z% C$ I5 s, q: |9 NDiscriminant function, 判别值
3 L4 K: c& R( I& }4 }2 sDispersion, 散布/分散度) `, v" c( Z3 ]
Disproportional, 不成比例的/ {; A) D9 x; e& M7 Y0 \7 u
Disproportionate sub-class numbers, 不成比例次级组含量
3 }" c {. f0 z' kDistribution free, 分布无关性/免分布7 u" T4 D2 ?+ V; b7 e
Distribution shape, 分布形状
5 G& K5 m* v- ]+ Q- C* EDistribution-free method, 任意分布法
+ h3 K' l' T7 f! L# z& |! Q7 u7 ]Distributive laws, 分配律
# z5 f+ A8 I) P4 q$ p$ hDisturbance, 随机扰动项
2 i9 X+ S2 y5 [& T! C$ ]8 pDose response curve, 剂量反应曲线
+ y" C0 R% a$ a" [+ X% nDouble blind method, 双盲法0 ^3 m) m. q2 d
Double blind trial, 双盲试验
* u' d1 A8 V) m0 p" ?* S* d: w8 o' ~Double exponential distribution, 双指数分布
$ x' N# X0 m1 h, w. T" ODouble logarithmic, 双对数
# v- A6 t9 i p/ k7 B$ n+ F/ a2 WDownward rank, 降秩
/ I6 l. b0 m2 N0 a' RDual-space plot, 对偶空间图! M6 h' E0 g; l! I8 h( ^
DUD, 无导数方法
# M, D! |1 }6 C m" v, ~. b2 X. ^Duncan's new multiple range method, 新复极差法/Duncan新法* a4 c# p+ ~/ n U& l
Effect, 实验效应
9 L& i6 d, S; ?Eigenvalue, 特征值+ ], Z9 |3 j$ V! n1 l
Eigenvector, 特征向量
, ^$ I/ {* O; t" R% v9 F1 q9 ^7 ]Ellipse, 椭圆
1 {0 m0 M. T; j1 \7 d( @Empirical distribution, 经验分布& s% ?7 R9 T3 Y/ Q
Empirical probability, 经验概率单位
& q1 e( i f" Y$ i. k: {/ v8 z7 KEnumeration data, 计数资料
0 {# E% M T* `, ]/ \Equal sun-class number, 相等次级组含量
7 E: i/ E; d2 S( OEqually likely, 等可能
) r5 y4 F* ]" N: a0 w3 TEquivariance, 同变性* D) D% {3 K7 ^1 u8 A O9 U4 K
Error, 误差/错误
* T' W5 x# j$ wError of estimate, 估计误差3 b$ g. g) o+ i+ I( w4 D
Error type I, 第一类错误 h F( W$ o- h7 c
Error type II, 第二类错误" n" Q% M3 s* G$ A8 E6 O5 x
Estimand, 被估量! @! i. g. T% x9 ~: K
Estimated error mean squares, 估计误差均方4 w; t$ [; Y# E S9 s; q0 \0 d
Estimated error sum of squares, 估计误差平方和3 u9 ]- k/ Y$ G5 I) I
Euclidean distance, 欧式距离
5 b9 e0 a. \; E+ l( XEvent, 事件
5 E; z, _& [1 E7 i# n4 y2 p8 aEvent, 事件
' y& v2 R) O j7 xExceptional data point, 异常数据点
+ I+ l C- N# GExpectation plane, 期望平面4 E& M) A% V6 E" R) A8 q: P
Expectation surface, 期望曲面$ R& W+ P7 m/ J3 C) I! b) q
Expected values, 期望值6 b, o2 z# l2 H8 g N9 v
Experiment, 实验
, U$ f$ Y+ Y4 W7 F( C* mExperimental sampling, 试验抽样
% @* k4 p, p4 n4 cExperimental unit, 试验单位" e# x7 y! y! ~; A* o
Explanatory variable, 说明变量
1 p( P; i4 U' GExploratory data analysis, 探索性数据分析8 h4 m+ ~$ q$ q1 n: n5 v
Explore Summarize, 探索-摘要
+ L' e- @3 v; y0 |9 e$ {. zExponential curve, 指数曲线, ]) M" k/ A! q
Exponential growth, 指数式增长
- F, B6 D, S/ U' A# h0 NEXSMOOTH, 指数平滑方法
! R$ M' D/ i; [) e7 W0 r' @7 Y$ DExtended fit, 扩充拟合
4 S2 O1 H5 b4 X. NExtra parameter, 附加参数- r/ D; s5 u" n
Extrapolation, 外推法
. E4 O# p8 s+ D" x; F: t: ^Extreme observation, 末端观测值
' l- d; x; t I% Y# v7 Q9 jExtremes, 极端值/极值
! \1 I2 s0 j6 F7 R# F w! J& X8 o3 ~F distribution, F分布
0 Z4 U! E+ _9 @8 fF test, F检验
) u# m1 K* X0 M8 H# \Factor, 因素/因子
" E* H+ B B* W0 }5 F0 W% q0 y! TFactor analysis, 因子分析/ N/ R" Z) s- z8 W j: f3 q
Factor Analysis, 因子分析9 \& s* g: m- O- V* j4 N+ R
Factor score, 因子得分 $ U( E0 R9 H! {7 h% [+ j4 ]
Factorial, 阶乘: C- X+ e* f E9 _
Factorial design, 析因试验设计
" i8 X5 }5 S. O/ C; s) qFalse negative, 假阴性8 T& H( L. N0 M O# g8 H
False negative error, 假阴性错误
# F, u8 [1 J, a5 R* u' dFamily of distributions, 分布族8 q! O$ V; w- Y8 h$ j! a' |7 E
Family of estimators, 估计量族' L% S; @1 k( b4 t
Fanning, 扇面. B9 K9 l* E8 y, ]* I- u i
Fatality rate, 病死率
; p5 u3 s; V( n3 wField investigation, 现场调查' L7 y) P3 A9 r8 I
Field survey, 现场调查- v' g9 `! } s$ H9 a3 Y" A, [
Finite population, 有限总体
( J& d5 }3 P5 i! G* uFinite-sample, 有限样本
; V% e% n9 j' K- z; C$ TFirst derivative, 一阶导数; b# F3 V* x3 z5 H# ~* {1 q
First principal component, 第一主成分0 Z7 ?; ^; E; J: y9 I6 P" l$ w
First quartile, 第一四分位数; ^2 y/ x5 ~ m
Fisher information, 费雪信息量( N* T4 W3 Z p9 K6 p/ S& x
Fitted value, 拟合值
6 Y. R9 _ U2 x1 }% \1 {) p" mFitting a curve, 曲线拟合! ]7 j/ M5 P+ r9 @8 y+ p4 A
Fixed base, 定基/ \" ?0 L, x2 P! m" G! N
Fluctuation, 随机起伏. k- }) {, `3 P) Q; M$ b
Forecast, 预测
8 S% q" g. V# ]- v- h' W3 j. |Four fold table, 四格表3 [1 y! f" l. R
Fourth, 四分点5 p- }. u& I: F+ z
Fraction blow, 左侧比率' Y& n; }' X3 g8 k5 L
Fractional error, 相对误差9 a3 @9 a2 C* ]$ g* B3 a
Frequency, 频率# c" i* }2 Q, S) \% n- e
Frequency polygon, 频数多边图
- @$ }* s! H* A& i% p, RFrontier point, 界限点
! r7 q8 F0 p P2 A* M SFunction relationship, 泛函关系
3 S; g; a' k! `. n" lGamma distribution, 伽玛分布
* k x! H! K# h' w, X, V) KGauss increment, 高斯增量
, c% t. P" `0 r- o5 F. Z; A1 J! hGaussian distribution, 高斯分布/正态分布
0 V# K7 u8 V+ t1 B" rGauss-Newton increment, 高斯-牛顿增量
/ w; ]1 f: ^) y% K3 C% y9 N* z1 bGeneral census, 全面普查
0 R; A3 S$ ~: A$ i- e3 KGENLOG (Generalized liner models), 广义线性模型 : j: V% ~# U$ x- C1 z
Geometric mean, 几何平均数( U' i' S. F) k% O2 W
Gini's mean difference, 基尼均差
) u; d* m6 W1 X5 g6 yGLM (General liner models), 一般线性模型 0 m# M# q+ |% Q7 g' x+ Z/ W# g( r
Goodness of fit, 拟和优度/配合度
- ^2 c6 C; L3 \! K* pGradient of determinant, 行列式的梯度! }2 O4 y# g s' I3 m( D' }
Graeco-Latin square, 希腊拉丁方- |6 [( c# U& O$ y2 I' u
Grand mean, 总均值0 \8 `8 f+ ^6 }
Gross errors, 重大错误) i; b; ^+ Y+ b+ X! ?
Gross-error sensitivity, 大错敏感度6 x* q8 H1 z" j7 x, ]! D+ `
Group averages, 分组平均
) R9 x5 ^0 v7 OGrouped data, 分组资料
1 }7 F. W" ~3 D& gGuessed mean, 假定平均数
+ i! Q& b# w8 { S& y2 B) KHalf-life, 半衰期
5 |' R& m5 L, i, {* t: ~Hampel M-estimators, 汉佩尔M估计量7 P' i' h4 o1 p" h" Z& d
Happenstance, 偶然事件
6 U& R% T; H* I* S6 w- Y" z5 EHarmonic mean, 调和均数% d; i Y* a1 S' c
Hazard function, 风险均数# x' P0 v- U3 q( d5 ]- ?
Hazard rate, 风险率
7 h L. Y& w+ m7 SHeading, 标目 - }4 V0 X" H, Z! [ G( @5 @
Heavy-tailed distribution, 重尾分布
' X! R- m3 ?7 jHessian array, 海森立体阵
% V0 T( O; j1 }7 U5 M3 }Heterogeneity, 不同质
. M& M6 R7 s* r: mHeterogeneity of variance, 方差不齐 * X' k. d# X$ S- v' f: R
Hierarchical classification, 组内分组
+ [) ^% u/ e2 @: lHierarchical clustering method, 系统聚类法
' {1 V8 L6 X. C5 ^ H$ ^' D0 \" BHigh-leverage point, 高杠杆率点0 Y, M2 X/ @# {# q- F# `& {& ]" ?' i
HILOGLINEAR, 多维列联表的层次对数线性模型# }5 I- P& P0 B4 u2 {
Hinge, 折叶点: P. s7 ~1 ]) v8 [9 ^- I: `" r2 I3 N. }
Histogram, 直方图4 F1 ]6 Z- b* |9 z" K `
Historical cohort study, 历史性队列研究
% m' A( `7 O$ J4 n. DHoles, 空洞
. g: Z. U- F4 w% x7 LHOMALS, 多重响应分析
8 \" a$ q9 Q2 n4 w3 c0 UHomogeneity of variance, 方差齐性: n) A+ }8 }7 m+ r$ r; s, }
Homogeneity test, 齐性检验
. S1 [* `* j4 N& ~6 CHuber M-estimators, 休伯M估计量
, C2 q$ P [3 j9 W0 IHyperbola, 双曲线. \$ Y/ e+ j4 x3 K* A+ Y6 R
Hypothesis testing, 假设检验: Y$ q) b M( }5 l' Z7 I7 U' B. w
Hypothetical universe, 假设总体
$ m( g ~; a2 I8 F8 r0 @/ xImpossible event, 不可能事件
/ y+ B" v% q* u V- _# DIndependence, 独立性& u4 A6 X6 _+ Q7 o) _/ e$ r' m8 u6 x* W
Independent variable, 自变量
6 r+ O2 N6 f$ r! `7 `: kIndex, 指标/指数" b6 V0 k* S; G5 b+ W* N; m
Indirect standardization, 间接标准化法* [) V% s$ {4 O: t
Individual, 个体; g9 c( ~7 \" f- C
Inference band, 推断带
( U9 F. C; p" n2 J% D$ PInfinite population, 无限总体. Q8 y9 @8 V1 s# K1 K
Infinitely great, 无穷大
6 g- u$ t9 x: f2 Q$ P7 t" P" IInfinitely small, 无穷小; a" l3 {+ ~; C& n' G) c2 v
Influence curve, 影响曲线1 R+ ^1 X& W* e0 F- x# V. ?. k: t I
Information capacity, 信息容量
3 P8 I# B! B' aInitial condition, 初始条件2 t' I# }( s) H% |7 Z8 @) a6 [
Initial estimate, 初始估计值5 o4 h3 ]% n" k* c4 l* M
Initial level, 最初水平
# f+ G0 t3 y+ c, P4 {' WInteraction, 交互作用
* P- n8 U. k7 D% q* ~# bInteraction terms, 交互作用项0 r! s$ i) W( _* \* V, H8 L
Intercept, 截距# V9 _5 ?: `% n8 C! U( ?+ j' `: @
Interpolation, 内插法. Z: b T6 X- v7 [4 V9 n. |
Interquartile range, 四分位距+ _- _4 t3 M( w' F& N. a# J
Interval estimation, 区间估计
9 X) ~7 ]4 Z6 Y. a$ |5 h4 oIntervals of equal probability, 等概率区间! h; f" Y/ E0 I1 U% C( X$ {
Intrinsic curvature, 固有曲率. p9 ~" o8 {$ q$ i7 y; J$ q
Invariance, 不变性
' [. D2 I e0 P, ` N/ YInverse matrix, 逆矩阵1 g; p$ V& `( i) M
Inverse probability, 逆概率
% c0 C5 r4 _! M5 o6 u" ]5 g8 ^Inverse sine transformation, 反正弦变换
8 w* b7 o* B+ ~* F: @, d& \- Z% AIteration, 迭代
9 ^6 V* U2 Z( b- y+ |Jacobian determinant, 雅可比行列式
/ D- H* b4 V! G8 C" {4 a9 E1 DJoint distribution function, 分布函数" z: @6 t+ e) E) G7 S
Joint probability, 联合概率
9 ?5 }" j4 A% R* D, h2 ?) |4 rJoint probability distribution, 联合概率分布% m* p/ h+ d( D$ x9 i/ |: e
K means method, 逐步聚类法5 p; h! _8 [ \9 u& V5 A$ W7 m
Kaplan-Meier, 评估事件的时间长度
}3 I3 B; t- g+ Y+ ~" b4 wKaplan-Merier chart, Kaplan-Merier图- s) |" P. \ d& ^ C: d+ ^
Kendall's rank correlation, Kendall等级相关, u8 J# B+ z- { F! |5 V8 ?
Kinetic, 动力学
* y/ q9 z9 p+ P- R2 g+ iKolmogorov-Smirnove test, 柯尔莫哥洛夫-斯米尔诺夫检验
I- b- ~( x& O0 e! C: t. bKruskal and Wallis test, Kruskal及Wallis检验/多样本的秩和检验/H检验
. r+ H4 P; z/ G& o% w0 M z7 S/ rKurtosis, 峰度, ]' e- ~( D* a) F! C
Lack of fit, 失拟
( }3 R x; Y6 P. ILadder of powers, 幂阶梯
8 i5 n0 f, H* ]' S& ?/ G5 VLag, 滞后8 _" v+ n4 H; { N) i; |
Large sample, 大样本
" g! H" {# A4 {- ILarge sample test, 大样本检验) k# V; _# O/ R2 A; c
Latin square, 拉丁方
5 W" r& n6 y0 M0 dLatin square design, 拉丁方设计
4 ~* Z5 L; G. [8 h8 H! V7 GLeakage, 泄漏
; c: o# `+ m/ {- c+ g1 QLeast favorable configuration, 最不利构形
6 [3 p8 E, B7 Q3 H: I: bLeast favorable distribution, 最不利分布9 c2 J) X0 l0 o; }; o2 U) m; L, A
Least significant difference, 最小显著差法
- K: S, e6 k9 {* Y& qLeast square method, 最小二乘法
" E' m' b! e `( n q( ELeast-absolute-residuals estimates, 最小绝对残差估计" G: }5 z5 }9 a3 ^( @
Least-absolute-residuals fit, 最小绝对残差拟合
7 h3 ]" j! g/ L: d+ {Least-absolute-residuals line, 最小绝对残差线
6 o) @0 S$ k# w( `1 U6 R8 w9 v$ }Legend, 图例
" k' `1 @: Y/ `" \) a% e. z+ k! pL-estimator, L估计量- Q9 }" l8 r, |7 g* Y
L-estimator of location, 位置L估计量/ b6 J! p. w/ E& r0 Z; `1 U4 z
L-estimator of scale, 尺度L估计量) T! { @2 m& P% ?" J. U* E
Level, 水平& E: l" z3 n( I' B2 {) r% R! G
Life expectance, 预期期望寿命- Y4 s* Z Y4 c8 [: j) R
Life table, 寿命表
/ P& s0 N! D: s8 J% sLife table method, 生命表法& J2 N6 D& {" t( A3 L% O
Light-tailed distribution, 轻尾分布# M, @: p7 _# d6 h
Likelihood function, 似然函数- d% e; F( ?+ r: ] _ o+ B
Likelihood ratio, 似然比7 n' r' v( X8 a/ B- q- @
line graph, 线图
" s: d' D2 ~' v* ]4 C" wLinear correlation, 直线相关0 ]! v/ u1 c: n: E2 v1 l9 e# Z; l
Linear equation, 线性方程1 J/ `5 S. Z7 G( x& r* A8 r4 b
Linear programming, 线性规划
/ x+ m2 C9 }1 m4 G. \% f0 HLinear regression, 直线回归1 I4 W2 }1 ]: A" \" F
Linear Regression, 线性回归. n6 C# b ?3 ~* `1 _. C* Y4 O j
Linear trend, 线性趋势
$ Q' ?8 a8 W5 l7 _1 m3 m) B7 fLoading, 载荷
5 K! q8 s& R( K2 bLocation and scale equivariance, 位置尺度同变性( G# U7 B8 @' z) S( i
Location equivariance, 位置同变性
6 [+ L5 T5 i+ C6 P$ gLocation invariance, 位置不变性, p1 Q5 Z. i- v L
Location scale family, 位置尺度族+ g9 r3 a0 x" d# T: a
Log rank test, 时序检验
" ]# c. k8 O# }8 ^# SLogarithmic curve, 对数曲线- G3 I" \- |3 U1 s, @5 P: O8 A
Logarithmic normal distribution, 对数正态分布
$ A- ~; E, ]$ @7 Z2 e% K" |Logarithmic scale, 对数尺度- o$ t3 b {9 G3 n
Logarithmic transformation, 对数变换5 F: ^, @3 C$ V* a! e4 Q5 ^
Logic check, 逻辑检查- R7 I6 w2 B/ Q# |4 Y, [: y+ a
Logistic distribution, 逻辑斯特分布 Y! q' F3 ?1 b$ s
Logit transformation, Logit转换
. @6 l y- Z, i' f9 \: M2 [7 `LOGLINEAR, 多维列联表通用模型
2 N, v% b. o4 X- w4 H, N. MLognormal distribution, 对数正态分布
: ?$ N* Q# q" @7 k/ ^Lost function, 损失函数
" k5 c- R( \' QLow correlation, 低度相关
4 u# Q: u% u+ b; nLower limit, 下限
# w8 L# S5 j0 i$ M5 B. I, fLowest-attained variance, 最小可达方差
) n8 @: S% t" m5 F$ {+ t9 d8 tLSD, 最小显著差法的简称* u0 e" l) u; S" g; g% E
Lurking variable, 潜在变量
9 I+ ^( ]2 ^) D1 K8 H1 v( MMain effect, 主效应
% A" A% l0 R A6 u6 gMajor heading, 主辞标目
- e9 G _2 k5 E, W" g) QMarginal density function, 边缘密度函数' Q" b0 y( Y! B) K/ F& ?# r
Marginal probability, 边缘概率
( x% b7 C, g6 ?3 c6 }Marginal probability distribution, 边缘概率分布
3 E4 w+ V; Z0 s sMatched data, 配对资料
! M# a4 _5 S( e) f& _$ \- I3 ZMatched distribution, 匹配过分布
% d0 L3 g& M* N/ k/ eMatching of distribution, 分布的匹配( m6 `5 z1 S+ V5 L
Matching of transformation, 变换的匹配: ]: w" `; N2 X, Z$ H# j3 z2 n
Mathematical expectation, 数学期望3 ]0 E) ?+ [( f4 `9 a3 T% }
Mathematical model, 数学模型
) G/ v4 [: j% h5 p, ?. R! l' E" w5 aMaximum L-estimator, 极大极小L 估计量
) G+ M6 v& i, Y, {) P3 V+ z* DMaximum likelihood method, 最大似然法
! N8 t; U4 T0 ]Mean, 均数
) ]% v, i1 q( w2 x- J# NMean squares between groups, 组间均方
- D6 C1 {* t& d( q: sMean squares within group, 组内均方
3 ?0 G% w6 @% [, }$ yMeans (Compare means), 均值-均值比较
- `8 B4 {% O: z6 ^8 \Median, 中位数
2 H# s+ P( E# Y: u4 _* HMedian effective dose, 半数效量
3 J% N6 l5 ]' h9 [7 nMedian lethal dose, 半数致死量
. p0 F& D( g+ G% JMedian polish, 中位数平滑
+ ] w4 R" L: p+ y& i( i$ FMedian test, 中位数检验* a9 y6 P5 D# o. j
Minimal sufficient statistic, 最小充分统计量
6 O! [* n4 V Q3 z, }" y5 }Minimum distance estimation, 最小距离估计& ]3 D. g2 P8 F+ H D
Minimum effective dose, 最小有效量5 p" v. X0 C, W- U
Minimum lethal dose, 最小致死量
% s# K& [; R) X# aMinimum variance estimator, 最小方差估计量$ K# }3 g- |) C- z* A' I6 D
MINITAB, 统计软件包
0 W2 l2 h, x- |- Y1 ]& hMinor heading, 宾词标目$ \" q% P3 U0 L8 d' `
Missing data, 缺失值
- S; Z1 d0 L& JModel specification, 模型的确定. R* y, ]$ s# ]6 q; j" T" f) b! X6 P J
Modeling Statistics , 模型统计
+ k" m+ y" m+ H+ _Models for outliers, 离群值模型
# V! Z* @' ?4 M" }! FModifying the model, 模型的修正+ Y* U2 T) k, Z7 k! s
Modulus of continuity, 连续性模. L7 N3 h( W: u! c
Morbidity, 发病率 ' K& Z3 X1 B, H
Most favorable configuration, 最有利构形
$ H4 g3 C1 q/ j' ~1 F+ f( M' aMultidimensional Scaling (ASCAL), 多维尺度/多维标度$ F. z& u! `$ M9 L
Multinomial Logistic Regression , 多项逻辑斯蒂回归
' Z7 A: Q/ c) h3 E, S/ A$ [Multiple comparison, 多重比较' x- B% C5 D8 D; R: ?: [( w
Multiple correlation , 复相关; K' R! o, h; N8 @6 r- W- [
Multiple covariance, 多元协方差
# O8 B9 L/ g9 H h+ N3 nMultiple linear regression, 多元线性回归" ~, K/ ^) J/ R3 q y
Multiple response , 多重选项: I$ q! s& V' W
Multiple solutions, 多解* W$ V! G; R4 h8 W. ]0 T
Multiplication theorem, 乘法定理
2 w% A2 b4 p2 L: ^1 Z; lMultiresponse, 多元响应( P9 O: P2 C$ F5 c
Multi-stage sampling, 多阶段抽样
" `9 X$ C, M- y( a7 V6 Q) }* m" {. _4 AMultivariate T distribution, 多元T分布5 L0 y2 a* N9 H+ P+ u* d
Mutual exclusive, 互不相容& R2 p% F8 W# @+ _
Mutual independence, 互相独立' p+ {* x5 D" o! t! S
Natural boundary, 自然边界
8 }0 x: }9 V! U9 r- N' l/ F7 s% @Natural dead, 自然死亡7 _7 ^" z$ Y0 o5 }. G
Natural zero, 自然零
# C8 k3 J2 K2 c6 v+ r! n; cNegative correlation, 负相关9 J. t( n7 r7 O$ r9 [9 {2 r+ V
Negative linear correlation, 负线性相关
7 S- w, Z. n4 L( L0 C% _. S$ tNegatively skewed, 负偏4 T! T& m- B) y$ Q8 O% E
Newman-Keuls method, q检验
* E2 ]8 h7 s ~ F) `NK method, q检验; R4 [8 z8 C, v0 y5 \, w
No statistical significance, 无统计意义
6 b- A: g; _/ v- z# I8 S( O% VNominal variable, 名义变量$ H: r2 ^2 L9 N( i: J# k( G; y
Nonconstancy of variability, 变异的非定常性" I) O7 q6 N6 j1 p I6 }% |+ h
Nonlinear regression, 非线性相关1 {8 B. w, G! _' l1 p! k3 A
Nonparametric statistics, 非参数统计
3 b# [6 d& A" XNonparametric test, 非参数检验5 i( j6 P# V& B |9 }% I
Nonparametric tests, 非参数检验
9 f( i9 J) }) S( W0 J9 M* J" X) wNormal deviate, 正态离差) N2 j# h1 m# F, d* P ?" s6 C
Normal distribution, 正态分布( ]: R% E3 {3 A9 ]2 y
Normal equation, 正规方程组
) a1 y e3 B5 p9 ?+ m$ GNormal ranges, 正常范围
/ C9 _7 F# L" J0 Z0 kNormal value, 正常值
# s: ]& l0 p3 _0 D% `2 `+ L& tNuisance parameter, 多余参数/讨厌参数
; V, C0 ^1 |% l- qNull hypothesis, 无效假设 : @3 a& z, m$ O. R* p
Numerical variable, 数值变量
6 J+ V0 z% A0 D n" mObjective function, 目标函数
1 e- `; _3 V/ NObservation unit, 观察单位3 X* k1 q& ?5 L: a
Observed value, 观察值
* I9 Z5 T' K. J8 O0 VOne sided test, 单侧检验
) F% g( J( X( X7 t R' nOne-way analysis of variance, 单因素方差分析6 p7 u9 j) A4 ?: g
Oneway ANOVA , 单因素方差分析3 R: d4 U% F# H* p% z
Open sequential trial, 开放型序贯设计& N9 `' K3 e) ?. a8 I* ~) l* R
Optrim, 优切尾* I) S5 e0 o5 P8 _
Optrim efficiency, 优切尾效率
8 l# t: ?* V( x% HOrder statistics, 顺序统计量1 A/ ]+ O7 C- q; f1 X' q/ i; z3 t
Ordered categories, 有序分类' Z1 m# e/ I0 n& D7 k
Ordinal logistic regression , 序数逻辑斯蒂回归
; ~: E$ u! X2 H% y9 K9 e' y' F* TOrdinal variable, 有序变量
" e' d; @# ]3 _Orthogonal basis, 正交基
( Q3 b* _0 t" @; v0 h2 VOrthogonal design, 正交试验设计
2 a' Y/ E1 b7 F F; o f& u0 M, i6 AOrthogonality conditions, 正交条件% n( n2 y+ W J2 O
ORTHOPLAN, 正交设计 ' R4 \, B8 s4 \' n+ r8 Q& G
Outlier cutoffs, 离群值截断点7 m: e1 M9 C" }' _) a$ a
Outliers, 极端值; `) u1 O. @: @) I
OVERALS , 多组变量的非线性正规相关
6 u7 \' M. ]: t: Z8 c7 COvershoot, 迭代过度
$ k& u, U1 V. Z s/ PPaired design, 配对设计
5 |+ P% C/ f# E: c1 O `& a+ \1 oPaired sample, 配对样本
4 m7 s0 ^+ w" a- `2 x/ D9 p" iPairwise slopes, 成对斜率' q& S/ j: L2 t
Parabola, 抛物线7 I- U$ Y; A6 f3 h, }6 H
Parallel tests, 平行试验. k6 S: }5 H1 I* Z+ j/ K* q, R$ z
Parameter, 参数
) r: d5 u4 r9 M. C% T) gParametric statistics, 参数统计, i7 S+ K& g# D$ b$ g) d0 ]
Parametric test, 参数检验
" B. _. J% Q) E1 K3 `4 z# uPartial correlation, 偏相关6 ?/ \8 S1 V7 f/ n% K* O" |: I
Partial regression, 偏回归
: ]! ^9 r$ ?( }% _4 D& IPartial sorting, 偏排序5 N: I& H9 X- i# o. X
Partials residuals, 偏残差
2 X9 Y4 `' Q R# v6 jPattern, 模式# i9 Z& n! x9 Y$ T( I- |
Pearson curves, 皮尔逊曲线
3 h1 L- v: C U' b, O/ {* aPeeling, 退层
9 y/ |) u* g1 a& I& n* a6 }Percent bar graph, 百分条形图$ v; W# B h, q0 x- ?4 C
Percentage, 百分比
5 \/ b+ N7 i. VPercentile, 百分位数
' q% d# W9 J: ]* P* hPercentile curves, 百分位曲线# f$ e* Q" L: S% R% Q
Periodicity, 周期性
2 b/ ?! u2 ]: O' w# b n3 CPermutation, 排列
_8 }. I" H) d: i& h4 a! mP-estimator, P估计量8 D2 Z" B* ]& s! \/ I' q5 q
Pie graph, 饼图
7 j* E6 s2 U- z( d3 ]+ ]Pitman estimator, 皮特曼估计量: [$ U) S% k) M: `$ i: T
Pivot, 枢轴量1 x& H# k* }3 ?& K
Planar, 平坦$ O% `( |5 b( p z% l; @. s- p
Planar assumption, 平面的假设
5 v8 l9 _+ {+ U1 @5 b; t" zPLANCARDS, 生成试验的计划卡
9 O# G' H2 h; P( V: ?Point estimation, 点估计
! Y. e% u5 U0 q. V" h7 @- I% gPoisson distribution, 泊松分布
: K& ^, S- e( k% f& ^Polishing, 平滑
& n. E \* ]: O7 ^1 \' bPolled standard deviation, 合并标准差$ _$ B4 C$ l% j0 r$ y y J. L* _
Polled variance, 合并方差( J% D* ~: x! i
Polygon, 多边图
+ f3 j7 {6 I4 c* c! qPolynomial, 多项式
7 |' B) C* e$ m" r" UPolynomial curve, 多项式曲线: S' C1 \7 c# y) l5 B9 z
Population, 总体% t) W) _9 A! k/ m2 {; @& C) I
Population attributable risk, 人群归因危险度
+ t4 u- G& J% v' h# D; x2 kPositive correlation, 正相关' n! ]) g" j# w; y, e( w
Positively skewed, 正偏- t/ Y( e' t3 Y3 j
Posterior distribution, 后验分布! b; P( k- P: X7 a" Z- f, Z
Power of a test, 检验效能
F3 b/ n, c7 c4 S7 HPrecision, 精密度
8 c+ l! H: ~4 a: W, BPredicted value, 预测值
5 E1 L/ q3 L: d$ G2 PPreliminary analysis, 预备性分析
- d" n" b' n J' uPrincipal component analysis, 主成分分析
5 Q% _4 a' J3 HPrior distribution, 先验分布) Q, k# v8 {# C T# D
Prior probability, 先验概率
( N" V% q6 l! y7 Z( A K1 sProbabilistic model, 概率模型. m; i8 l( M/ x; Y) z: z
probability, 概率! i( t o) i, I9 D% ^* g6 g
Probability density, 概率密度
9 l5 D& w4 O" O4 m( qProduct moment, 乘积矩/协方差) n! Q7 ?4 D0 S" T8 x7 P
Profile trace, 截面迹图
! v) r" O0 F" P* k: |% m5 w/ uProportion, 比/构成比% y4 y) A4 P; C( ^/ V
Proportion allocation in stratified random sampling, 按比例分层随机抽样" x6 T' H/ K; s
Proportionate, 成比例, ^8 B% M) E! q" |' @
Proportionate sub-class numbers, 成比例次级组含量8 e- e! u) i+ |
Prospective study, 前瞻性调查2 a7 F. [: X; R
Proximities, 亲近性 + r6 |4 P( W, y5 G) t& G; Q
Pseudo F test, 近似F检验3 A% l6 e3 z; ^
Pseudo model, 近似模型# K9 t3 q5 G4 Q! F0 k y1 K. ]7 h
Pseudosigma, 伪标准差
; P7 Z1 T7 E7 @0 f- W& V' G9 GPurposive sampling, 有目的抽样7 y" {4 Q! T6 a& a
QR decomposition, QR分解
" R2 y% K8 H3 x: s! h& `0 f, r jQuadratic approximation, 二次近似
2 g6 u$ O* R$ t" QQualitative classification, 属性分类
" H+ t* ^. G6 ?' OQualitative method, 定性方法9 m [/ {3 t" |4 O% s" n* k! B
Quantile-quantile plot, 分位数-分位数图/Q-Q图
+ S( I. c! X) ZQuantitative analysis, 定量分析
/ N" S+ x% x% ?Quartile, 四分位数
, V, ?) r1 h) N+ ?5 oQuick Cluster, 快速聚类
! H$ i: h! u) b9 K/ B) N# D& xRadix sort, 基数排序& b+ Z8 V" n- Z, A e. I
Random allocation, 随机化分组7 M' {1 p7 ?+ ]. R, \: }
Random blocks design, 随机区组设计3 \0 m! ?! `0 V8 t/ _
Random event, 随机事件
3 a8 n- F& L9 wRandomization, 随机化9 R8 T6 l: m4 K+ ~: T) N7 i' ~
Range, 极差/全距
& ?2 L# c9 ?, L$ o6 w; ?Rank correlation, 等级相关( ] J4 O, E9 L$ q
Rank sum test, 秩和检验9 A9 E( |9 w% b' y& h
Rank test, 秩检验3 C, _- r6 ~+ U# A
Ranked data, 等级资料9 ~- d3 w( M4 W7 `0 Y; g
Rate, 比率
u7 Q7 b% N7 Q0 Z$ i* uRatio, 比例
7 m* Q% {5 d. URaw data, 原始资料* _0 Y5 B3 C8 m7 C+ {
Raw residual, 原始残差
3 c5 Z5 X4 K; e- @: oRayleigh's test, 雷氏检验! ~9 \8 n- M9 r6 ~8 |; B
Rayleigh's Z, 雷氏Z值
+ S9 Y! d7 d! b. L! j7 l: b1 rReciprocal, 倒数
4 r/ a7 R/ R& @4 F: @! `; o/ v9 IReciprocal transformation, 倒数变换# j d7 B" k# E: _
Recording, 记录) \$ b j: K" t% M# H
Redescending estimators, 回降估计量
+ t7 `' P; p, i, PReducing dimensions, 降维$ {$ W$ A; U& e' x! V( r# q: F- h& N+ u
Re-expression, 重新表达& v* g, }/ }2 S/ |+ [8 Z
Reference set, 标准组: ~( v, \8 o" N0 R
Region of acceptance, 接受域2 y9 [, Q( K) i8 s, o# I
Regression coefficient, 回归系数
& L* n+ H1 _0 @5 F5 ORegression sum of square, 回归平方和
8 w% a& ?6 Y; ]/ m' uRejection point, 拒绝点4 g) J3 |# p6 a1 [. }6 e
Relative dispersion, 相对离散度5 {% X- {6 e" I4 ~7 H
Relative number, 相对数% [5 u' f5 `/ o2 Q* p/ s% o
Reliability, 可靠性
# }" c% ^3 c% Z3 C3 ]4 YReparametrization, 重新设置参数) p$ @8 D4 z, Q0 @7 i
Replication, 重复
! l, M- d' C5 rReport Summaries, 报告摘要1 h7 E H" K5 }( ]0 p% d6 G
Residual sum of square, 剩余平方和
: Y. b6 k' v1 S0 WResistance, 耐抗性! H5 x0 V+ h2 [7 q( f
Resistant line, 耐抗线- C, \! e4 A- L4 H8 q. L# }5 |% R2 z
Resistant technique, 耐抗技术5 J- f0 `( O( o) f! {1 \+ ?; c
R-estimator of location, 位置R估计量
( z" m& A. ^6 ^% {R-estimator of scale, 尺度R估计量 F' d3 H% `: ^; L. g+ o
Retrospective study, 回顾性调查
3 _" E: t1 z! y( t( \, Y" p7 s4 y! YRidge trace, 岭迹" T" L0 ~* t% M( y N: ` P5 z
Ridit analysis, Ridit分析
& o0 Y# w6 Y3 p* m6 dRotation, 旋转
- i, U4 Y c! G7 d2 D0 e/ hRounding, 舍入
$ D. Y: E; l; L2 G3 ]; p9 g% [, I7 P% IRow, 行
3 { z0 |, ~. M4 a. f: V, w$ dRow effects, 行效应
/ c! B/ R0 r- N$ JRow factor, 行因素
a7 ~7 D# J2 u4 ^RXC table, RXC表
& Q, r) w5 b6 l) R/ m; F3 \Sample, 样本4 e% ?- [2 t+ U
Sample regression coefficient, 样本回归系数
9 r9 q' j: H: g: u6 V1 b5 WSample size, 样本量+ J. d. Q6 z! p. y
Sample standard deviation, 样本标准差
( H+ h; E# M: n7 j/ {, aSampling error, 抽样误差4 R4 i; f$ c2 L7 W: A$ z2 m
SAS(Statistical analysis system ), SAS统计软件包
0 S' O/ a; d) d. M$ t: ?Scale, 尺度/量表
" j0 m# Q3 k7 M/ \' gScatter diagram, 散点图
# l( }% t4 l8 L; nSchematic plot, 示意图/简图6 @) Z3 r) L ~0 L# }
Score test, 计分检验# i3 X2 m" r0 W6 h$ i _' J; ~
Screening, 筛检
6 N( z2 ~- l( B5 T" cSEASON, 季节分析 : H6 n1 U- r7 m- o3 N6 n0 s1 j
Second derivative, 二阶导数6 }+ K! S: t! ?
Second principal component, 第二主成分/ l+ E: U1 s" U- P) P, |
SEM (Structural equation modeling), 结构化方程模型 " d* z) i6 G; d0 ^) @
Semi-logarithmic graph, 半对数图. X7 L1 D' {4 l3 C& m
Semi-logarithmic paper, 半对数格纸
1 Y+ W: K0 H# z( _% D7 gSensitivity curve, 敏感度曲线/ n2 N2 A- [+ u' J+ j1 ?* O' v
Sequential analysis, 贯序分析1 c/ b2 l" x7 U
Sequential data set, 顺序数据集' X! z0 t: ^- j7 I, C
Sequential design, 贯序设计5 _0 J8 |; G# c7 K; ]; y
Sequential method, 贯序法
/ N) U- v P6 w4 }! `+ ~6 [Sequential test, 贯序检验法3 l( ^; L& e. M
Serial tests, 系列试验, `7 P/ y1 r/ o- e$ B
Short-cut method, 简捷法
) e7 c$ r& g# TSigmoid curve, S形曲线
! ]" `- R! ~+ A$ `! iSign function, 正负号函数
" V p0 X7 z3 N. E4 U# cSign test, 符号检验1 S, f& `4 C7 w1 ]
Signed rank, 符号秩
9 T1 ~& T6 g2 j: W& a" I# T0 rSignificance test, 显著性检验
G2 \; P& z" H( \( MSignificant figure, 有效数字- G/ H, S' f4 F7 M+ @
Simple cluster sampling, 简单整群抽样4 N8 n9 |; s$ F
Simple correlation, 简单相关
$ I2 C k5 z% m# iSimple random sampling, 简单随机抽样3 U2 }7 Q- b) U0 N. n3 `* [
Simple regression, 简单回归
1 u# b8 ] {$ d" j& `simple table, 简单表
6 C, G& d4 n O. v- G1 VSine estimator, 正弦估计量
+ o1 E5 F, g( t/ p! g* g% zSingle-valued estimate, 单值估计
; V5 j. ^3 j4 z. E* T R9 z( a# M) A+ zSingular matrix, 奇异矩阵
9 ~, g' o& c" @) gSkewed distribution, 偏斜分布
# ^2 L( V3 e: l5 Q) C/ y& BSkewness, 偏度$ ?6 ]5 _9 i. x0 z& ] u5 f
Slash distribution, 斜线分布
- x. l$ e& {( B" l3 bSlope, 斜率: E" X+ c% `" E
Smirnov test, 斯米尔诺夫检验
$ u, u$ m5 B, ?2 }/ Y4 s; WSource of variation, 变异来源
* _7 K- C% L( v" m$ ?& ISpearman rank correlation, 斯皮尔曼等级相关2 l7 _3 s) c: C
Specific factor, 特殊因子
, I r+ R( ?0 oSpecific factor variance, 特殊因子方差0 {, }0 Y5 M8 M6 f+ ?( F; K& K
Spectra , 频谱7 p* e# {7 U, f% H" q
Spherical distribution, 球型正态分布" }/ ^, z5 J& J7 H. b* F/ ?& M
Spread, 展布
* k1 L( }$ P' L* X- o0 lSPSS(Statistical package for the social science), SPSS统计软件包
% ?2 e1 K* I/ \) b0 C' g0 o/ w4 rSpurious correlation, 假性相关
m1 V7 p: j0 Q7 @' mSquare root transformation, 平方根变换3 c; o0 A& Y: h2 ~8 Y* Z
Stabilizing variance, 稳定方差3 @- f0 m; ]; Z6 Y' T& T& f
Standard deviation, 标准差: m9 g" A6 u; g# ]$ m T- b
Standard error, 标准误
5 o# f3 i2 D; z9 R& q; p. EStandard error of difference, 差别的标准误4 a2 V! w A$ _# T- V2 l0 ~1 L& O
Standard error of estimate, 标准估计误差- y% b9 J2 ?( \9 V' i
Standard error of rate, 率的标准误* x; h( P- r$ R
Standard normal distribution, 标准正态分布
! q- Y% n7 f, _+ fStandardization, 标准化' \+ V4 w+ N/ i
Starting value, 起始值: D; F% Q) _, W; S2 L4 \" G4 j
Statistic, 统计量
' t) Z1 i1 U4 f% `* K$ ~Statistical control, 统计控制
/ j/ r' U+ N6 \. l! M2 oStatistical graph, 统计图8 w# a/ [7 b( c5 a
Statistical inference, 统计推断
& w1 m1 {* j6 R4 A* W7 A, J, GStatistical table, 统计表
% z9 N' Y4 t* h. |; pSteepest descent, 最速下降法
, Y7 V1 Q' ~$ s, r8 J3 g" U( MStem and leaf display, 茎叶图0 B: M4 s9 q2 l! D; Q( c; i
Step factor, 步长因子
$ w, l$ D0 u. D. zStepwise regression, 逐步回归( J, e4 p* }( U3 W) P1 L
Storage, 存
0 A$ W+ T* y1 k& R! @Strata, 层（复数）2 V" \) I' P5 |+ }; ^
Stratified sampling, 分层抽样
2 B/ c; A& `! \& W. t+ Y: @" [Stratified sampling, 分层抽样: N0 R$ ]! p% u+ R d5 t
Strength, 强度7 l( B# Z* t) _6 b( e/ n
Stringency, 严密性
. B: R" _% y8 }9 B: ?3 n. B: M ?Structural relationship, 结构关系0 S: S9 \; p* t- v3 O. o, C7 [
Studentized residual, 学生化残差/t化残差4 C. L! m( F- ]9 N- `4 p' A
Sub-class numbers, 次级组含量
& S6 [ H0 x9 {0 a0 aSubdividing, 分割6 r8 w. a5 z7 g4 d1 W
Sufficient statistic, 充分统计量3 |9 n0 N; y e3 G+ y! g# h6 R
Sum of products, 积和
8 X) k) ~, O) A1 l, A' ESum of squares, 离差平方和: I: e- U# j$ C6 N+ h# y
Sum of squares about regression, 回归平方和
" x2 K$ Y: r/ ^: \8 z1 eSum of squares between groups, 组间平方和
# e( B1 l% N4 u3 LSum of squares of partial regression, 偏回归平方和
+ W' f5 U& ^) p9 g$ O4 ~Sure event, 必然事件
) u# @- p- R( W0 W$ H3 g; D) L$ P3 aSurvey, 调查 \% z* E: J2 k, `! O% p" a
Survival, 生存分析
3 M; U n$ `& C, }$ Z. SSurvival rate, 生存率4 m# b, Y- N* j& C5 ?
Suspended root gram, 悬吊根图+ P- ?4 ~- k, w" u" q. [; w$ E; |( S
Symmetry, 对称/ S7 K1 v- p6 Z( V* T
Systematic error, 系统误差
* Q* q* x' o H5 v1 C$ \Systematic sampling, 系统抽样$ l6 ?: u# s i( m7 e, z
Tags, 标签$ }/ E" [0 ` {) j8 N+ r% m
Tail area, 尾部面积+ n7 N* z/ F/ W, V: r/ W/ y" `
Tail length, 尾长4 Z' X/ ^* o- z" P* J# O! u
Tail weight, 尾重3 t0 O( I: P! p: \. Z* b
Tangent line, 切线6 L( ]0 l$ \. Q9 O# w
Target distribution, 目标分布& v5 K4 u v6 t4 ? n1 d2 t
Taylor series, 泰勒级数. k+ ^: ^: f, |$ K. a1 I
Tendency of dispersion, 离散趋势
1 S$ P1 B3 l5 h8 zTesting of hypotheses, 假设检验
+ q% V7 [2 P" v5 u" BTheoretical frequency, 理论频数
+ }! D4 i' G$ ~8 y: k, ~Time series, 时间序列1 S/ K, w& N/ r, ]' _, k% L) r
Tolerance interval, 容忍区间
- T1 O+ l: F: H- v0 zTolerance lower limit, 容忍下限
; ]6 R: ?/ ?# Z: fTolerance upper limit, 容忍上限
9 P+ E" h/ _; y7 }& T$ w! q7 cTorsion, 扰率% h) f+ S l) R
Total sum of square, 总平方和1 @0 a/ m! F" H2 ^6 @" j
Total variation, 总变异5 G7 B% i$ H g9 W
Transformation, 转换
9 o& Q* ?" s' Q7 k$ RTreatment, 处理
: c+ n7 b% i( \% y" b' `" MTrend, 趋势0 _+ k* [$ |6 w' x, H
Trend of percentage, 百分比趋势
6 v9 }8 X5 K' C4 B* D4 l _7 gTrial, 试验0 E0 W: j9 m+ n& h
Trial and error method, 试错法0 b" J6 b- p; \4 o# Y
Tuning constant, 细调常数$ W2 j. ]- g& T) W
Two sided test, 双向检验/ d& y" U0 F k
Two-stage least squares, 二阶最小平方& W& `! G* t: J4 q$ Y9 a
Two-stage sampling, 二阶段抽样
6 ^; |+ J+ Q! Z6 }Two-tailed test, 双侧检验( l) @( p& G0 d0 A# {, d
Two-way analysis of variance, 双因素方差分析
: `- |8 Z" J+ B" cTwo-way table, 双向表* k- o0 r8 G# I$ w
Type I error, 一类错误/α错误
3 U, z8 B& Q0 z6 H C' cType II error, 二类错误/β错误3 l; n, m" w' X' a# q
UMVU, 方差一致最小无偏估计简称
$ w* ~2 `6 i- n9 g" P& b# XUnbiased estimate, 无偏估计
/ F( E, k. m: }8 O+ VUnconstrained nonlinear regression , 无约束非线性回归
B/ Z q; K% Y7 o: rUnequal subclass number, 不等次级组含量7 g% _% M, D& a- P2 P
Ungrouped data, 不分组资料
( \& O; v8 N1 b! e& m4 ?5 ]5 YUniform coordinate, 均匀坐标
2 p, |5 J' I7 W2 I! g+ ^: IUniform distribution, 均匀分布
6 ]: ` m- m) e8 T$ s& CUniformly minimum variance unbiased estimate, 方差一致最小无偏估计
, Y5 k: ~5 q* ~5 g3 j, u3 VUnit, 单元3 _# ], c$ H1 y$ Z
Unordered categories, 无序分类
) j( s- \0 S0 \1 L* j/ ~9 wUpper limit, 上限- c0 i- ]' u9 I6 _0 ^8 m: E; @
Upward rank, 升秩' }9 @6 C# ^, n% s
Vague concept, 模糊概念
& L" |$ C% [5 [. yValidity, 有效性5 y- F( V& x7 U6 q6 }
VARCOMP (Variance component estimation), 方差元素估计5 _' C, K2 W. k( D. N: @" q
Variability, 变异性
8 G8 O$ _* A2 Z6 t1 g5 I1 ]: L0 {5 @Variable, 变量
1 z, e6 X) c! @) U/ r8 sVariance, 方差; L3 Q- T8 f$ z/ u/ F. g3 \
Variation, 变异
- g5 ~. o! b! F6 sVarimax orthogonal rotation, 方差最大正交旋转. e; t! F$ Z) ?# Y
Volume of distribution, 容积) m% U, G! ^5 x( A8 r. S
W test, W检验
; y' j `3 I/ R& f$ h, aWeibull distribution, 威布尔分布
. `: A h" S) N3 ]; AWeight, 权数
& N8 _) @! v( OWeighted Chi-square test, 加权卡方检验/Cochran检验
I- ^: x5 W* J$ g- dWeighted linear regression method, 加权直线回归# S8 P1 b. F& q$ i6 ]% V! \
Weighted mean, 加权平均数
- w' ]0 B5 ^0 `5 B9 o) _# VWeighted mean square, 加权平均方差) m" H: M/ q. x; h( Y
Weighted sum of square, 加权平方和/ D+ g: O% Q& c" p S
Weighting coefficient, 权重系数% }% a8 H; L' b) o/ T, P) N
Weighting method, 加权法 ; y. K0 x) Y& }( L& U; W9 M! ?+ N- Y2 h
W-estimation, W估计量! J# x* S9 x: L" |
W-estimation of location, 位置W估计量% j% o( n, t( X" h
Width, 宽度
7 ~" T) { R4 f$ r- Y& E; ZWilcoxon paired test, 威斯康星配对法/配对符号秩和检验
: u' l3 y6 B$ j! J; s5 p+ U0 U/ tWild point, 野点/狂点7 ]# _8 F, z0 A) W8 {. @1 z4 A; N! v
Wild value, 野值/狂值
6 [1 j6 B, O) e$ y, B, [4 ZWinsorized mean, 缩尾均值
1 i' E# s5 H! j# q. [2 ]6 N2 gWithdraw, 失访
& E. s w& t( \( ^1 vYouden's index, 尤登指数
8 N! S- g" a0 y7 v" i4 j! JZ test, Z检验; a; w5 P& k- o( Z' L0 J8 f
Zero correlation, 零相关
% Z( X* ^2 H C3 p; Y- U: M6 tZ-transformation, Z变换 |
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发表于 2009-1-6 22:05
