|
|
Absolute deviation, 绝对离差0 y0 D/ s, ^$ x9 C
Absolute number, 绝对数
8 p* w4 l; l6 `4 G: {6 eAbsolute residuals, 绝对残差
* y( u" ]1 ^. f$ j4 Q) D2 H" MAcceleration array, 加速度立体阵
( W5 i& d9 ^" f0 d' e: AAcceleration in an arbitrary direction, 任意方向上的加速度
8 h0 Z/ A: M: b9 W7 z% QAcceleration normal, 法向加速度
: q1 S: g( e0 w; Q( fAcceleration space dimension, 加速度空间的维数+ b: G) k/ o5 I5 T! J2 x) P
Acceleration tangential, 切向加速度
0 P8 z" z4 ~7 dAcceleration vector, 加速度向量
j1 e, a3 @! d8 V( d" m8 o2 FAcceptable hypothesis, 可接受假设
0 i8 X" ~! c& h, RAccumulation, 累积
/ }' R% G3 H$ WAccuracy, 准确度' b- S' r- O Z7 p% S. {/ @
Actual frequency, 实际频数
) g/ q B6 J$ M, V; R! I; NAdaptive estimator, 自适应估计量
: A% I4 p; G# _' ~ B3 p1 GAddition, 相加2 |& a- o0 S% W- J/ Y
Addition theorem, 加法定理
, p6 U2 t# U. p! D$ S& I6 OAdditivity, 可加性
9 _! c) k4 G+ \3 mAdjusted rate, 调整率; X6 d8 ]/ ]4 ]
Adjusted value, 校正值# R* D7 D) `- r" C4 f6 b) ]
Admissible error, 容许误差! s! y) x) K0 u% m) a
Aggregation, 聚集性9 a0 p9 v2 e- B) o4 I# I& ?
Alternative hypothesis, 备择假设
3 C/ s; ~4 k- @% xAmong groups, 组间
4 S0 R$ w( s2 {) \# Z( PAmounts, 总量
; f. t0 _: Q. G V b: J; P6 uAnalysis of correlation, 相关分析* _/ n+ R' M7 p7 y
Analysis of covariance, 协方差分析
7 `- v! g; ?0 `3 ZAnalysis of regression, 回归分析
6 |9 k/ [" g: zAnalysis of time series, 时间序列分析
# |; c m6 a5 m2 J2 x0 ^0 X jAnalysis of variance, 方差分析1 x# W% z& M- j5 j0 p2 D
Angular transformation, 角转换8 Q( O& P% X: y
ANOVA （analysis of variance）, 方差分析
% T# W, Z G6 r, |/ q3 PANOVA Models, 方差分析模型! V& i5 X; m: t c
Arcing, 弧/弧旋
$ k; Q8 `; G% q6 l( V6 F( kArcsine transformation, 反正弦变换4 x" [/ O: F' l7 \! W
Area under the curve, 曲线面积
( b5 G6 ?8 p" i" K5 C5 v' ?AREG , 评估从一个时间点到下一个时间点回归相关时的误差
' C. z+ ~4 r# eARIMA, 季节和非季节性单变量模型的极大似然估计
% _' A' M. [, M, y' A. lArithmetic grid paper, 算术格纸
4 B t% K* v3 A/ E7 ^. CArithmetic mean, 算术平均数
, H& U* Y; j, G% c. z' o BArrhenius relation, 艾恩尼斯关系
5 Z$ B0 A% F1 y3 h: ]( p/ J* KAssessing fit, 拟合的评估4 U/ Z5 A6 K+ o
Associative laws, 结合律
! A+ W G m& h% m" P( {Asymmetric distribution, 非对称分布
: L+ J8 m' j' `8 }4 ~) y4 R7 i A9 M% cAsymptotic bias, 渐近偏倚
5 s4 |, l/ e& y2 G* z* @Asymptotic efficiency, 渐近效率
8 }& Q8 f# D& @ O: qAsymptotic variance, 渐近方差+ E0 U& s+ D- e# a0 \ O: y! e
Attributable risk, 归因危险度) R- ?; H5 f# l1 ^! i- K( `
Attribute data, 属性资料. s' a7 I. Q- X% O
Attribution, 属性
1 U6 Q3 X4 F4 a# Q pAutocorrelation, 自相关: c1 ^$ W) _$ n0 [# c# E
Autocorrelation of residuals, 残差的自相关* O! b* X2 z! E- }, X3 {
Average, 平均数2 p H/ `/ F& q8 C' {: h P
Average confidence interval length, 平均置信区间长度
5 ]8 B9 a8 Y, {4 HAverage growth rate, 平均增长率
% \. N1 A8 l* \1 \: _Bar chart, 条形图
2 e$ j0 E, n% Y/ I8 _Bar graph, 条形图, ?7 d- C+ K2 d+ y7 N
Base period, 基期# o6 Q9 D7 E! j
Bayes' theorem , Bayes定理
: u1 F2 i# C0 ?: b; x# T# A! qBell-shaped curve, 钟形曲线+ {2 H8 o3 |' i8 ^4 O: t0 Y4 m
Bernoulli distribution, 伯努力分布6 g& C" s/ r5 f4 C# G
Best-trim estimator, 最好切尾估计量
6 h+ r D6 r" k2 ^' n* YBias, 偏性
0 O4 C3 S( H' y0 q1 s O7 \Binary logistic regression, 二元逻辑斯蒂回归
$ ~) V" J8 M1 E1 G# j* B, PBinomial distribution, 二项分布
( [5 j9 J& g) [6 GBisquare, 双平方
9 x! O: z8 J* s% C2 `Bivariate Correlate, 二变量相关+ y* h. u% w+ I% }3 m9 @
Bivariate normal distribution, 双变量正态分布& m$ ?3 x- j+ T
Bivariate normal population, 双变量正态总体
% [1 s; f+ P. ^! _) A6 WBiweight interval, 双权区间
" j. V: Y$ ^2 M2 }Biweight M-estimator, 双权M估计量
5 h: a3 w+ `: Z9 {9 KBlock, 区组/配伍组
! a( A" J( p# t9 Z6 jBMDP(Biomedical computer programs), BMDP统计软件包% E' r; `0 r3 B s& [1 k
Boxplots, 箱线图/箱尾图: l% s, A6 S+ L. F1 l; E6 I
Breakdown bound, 崩溃界/崩溃点, ~0 S4 }6 n0 E* n3 L; x x/ s1 i
Canonical correlation, 典型相关. ^2 g" L; U3 @ n
Caption, 纵标目
" d! W# k( ^2 W" ~/ pCase-control study, 病例对照研究4 Q& Y+ d2 b& T/ M" F
Categorical variable, 分类变量! l0 {( i: i5 n" b0 c% u5 }$ T
Catenary, 悬链线8 {; r+ @3 E6 K8 f" h) H
Cauchy distribution, 柯西分布% ^' y% b0 R, } |( d" ?* L, z7 \
Cause-and-effect relationship, 因果关系
% T1 A# Z9 A1 D2 C& E+ I/ [4 R5 iCell, 单元
) v) o$ g0 B7 G7 c3 ZCensoring, 终检
4 ]! _0 P7 W$ u( D; t- \3 v8 NCenter of symmetry, 对称中心4 }& N# e5 ~4 N* F; H3 I6 j
Centering and scaling, 中心化和定标8 T( D# s" X& e1 R& V
Central tendency, 集中趋势
+ J; q& ?& M5 y/ G( B4 FCentral value, 中心值
4 c4 d @. ?* I" I% PCHAID -χ2 Automatic Interaction Detector, 卡方自动交互检测
& H1 F1 S) F& H2 IChance, 机遇
0 e. n. T, L3 B! ?; K1 ^4 {/ AChance error, 随机误差- W' G$ i5 B* \3 L
Chance variable, 随机变量7 v6 X7 K( [( M' R1 P
Characteristic equation, 特征方程
: l* Y/ o! }9 S0 z3 Z2 q, e" {8 gCharacteristic root, 特征根
; ]& ?/ }6 @6 _+ D8 M( wCharacteristic vector, 特征向量7 T. C+ ^% D& C% ]" O/ O- `$ c$ y
Chebshev criterion of fit, 拟合的切比雪夫准则* _- @6 o: `' {. m5 t/ Z
Chernoff faces, 切尔诺夫脸谱图
+ f/ c7 @. D9 S- z2 e2 T# KChi-square test, 卡方检验/χ2检验8 q, L1 u- Z/ u' A( t3 o! v
Choleskey decomposition, 乔洛斯基分解7 \! } y) X" e+ Y( K9 H
Circle chart, 圆图 / w k1 Q6 m& |1 c$ D
Class interval, 组距, a' H: O6 d) X3 A3 ~
Class mid-value, 组中值
% g- d3 b* B' X6 B- ~0 U) o9 iClass upper limit, 组上限
4 l Z- `8 h3 f3 j! H( w4 `Classified variable, 分类变量/ B/ |9 M) X( Q
Cluster analysis, 聚类分析: v9 L/ Z9 L+ p. `% ]
Cluster sampling, 整群抽样* t/ j/ z% M$ S* @
Code, 代码
+ z- [; t; f0 ~" XCoded data, 编码数据5 Z/ F! S9 s5 V( [' |7 Q
Coding, 编码* H" x4 [8 ] X6 H4 ^
Coefficient of contingency, 列联系数
- m% ~: D4 `: X1 L4 I* gCoefficient of determination, 决定系数4 [! Q! H1 @4 m/ p/ L
Coefficient of multiple correlation, 多重相关系数- p( h; A4 B. A
Coefficient of partial correlation, 偏相关系数/ O% r0 S! E5 W6 Q
Coefficient of production-moment correlation, 积差相关系数: d& D1 }. B2 _) D4 B" T. _
Coefficient of rank correlation, 等级相关系数
. y$ B+ o2 C+ JCoefficient of regression, 回归系数! E) J& }+ o# I& J, Z* ]6 z
Coefficient of skewness, 偏度系数
* U; g' Y9 G% `. G9 Q3 H. @& v+ Q. HCoefficient of variation, 变异系数
1 v+ J% q. o8 T* p' \+ KCohort study, 队列研究
' [+ v7 S* |# Z% Y% I8 ]& oColumn, 列
: V1 E4 \9 \) gColumn effect, 列效应, L$ n& Z8 e! `
Column factor, 列因素( O3 c( n# g5 G- Q( S# U$ A1 _* w
Combination pool, 合并" Y* W( C/ E$ h0 I( I) d
Combinative table, 组合表
0 [* `2 u. X* S2 v I! bCommon factor, 共性因子+ F8 i0 R' \7 M2 B* _2 ]7 H u
Common regression coefficient, 公共回归系数
) _2 A4 ?$ f8 ~* p9 d+ pCommon value, 共同值3 Y# B$ d% h1 ]3 u2 T' `* _" v
Common variance, 公共方差- R ^* W5 ~! b/ Y3 o
Common variation, 公共变异
; G: \+ `/ j9 n; h1 w- O" j0 e4 VCommunality variance, 共性方差
' l+ j5 C# v+ s$ L( ]9 WComparability, 可比性( c# W0 c6 u& A# ^; `
Comparison of bathes, 批比较 O. r- B% u3 x2 g1 `
Comparison value, 比较值
9 s* s, Z7 W! F3 F9 ^/ C" pCompartment model, 分部模型
6 L5 e: W4 p, ]0 _Compassion, 伸缩
- c* @! @( Q( Y" S, D' CComplement of an event, 补事件; P4 R3 r9 X5 j9 W# W7 T: U' t
Complete association, 完全正相关
9 F! }% F, z0 VComplete dissociation, 完全不相关
: B4 |$ d7 l, l( C4 R/ A) MComplete statistics, 完备统计量* V+ E$ N4 R) V3 V
Completely randomized design, 完全随机化设计) B6 s% {: U: U9 _
Composite event, 联合事件
* E$ ~3 Y* M( i4 T+ BComposite events, 复合事件
+ ]! U2 `2 j3 |Concavity, 凹性6 _3 M; \4 N O6 D1 I3 P# B. i6 F6 g7 ]
Conditional expectation, 条件期望0 P4 b: l* p( L: M
Conditional likelihood, 条件似然- ?: ^4 k' S8 {
Conditional probability, 条件概率! z$ Y5 Z9 `. _+ W8 _! l) T0 w0 o
Conditionally linear, 依条件线性8 S+ s E$ k y8 d( l$ M
Confidence interval, 置信区间7 ^+ m L% p, a# c6 c- }# k! N
Confidence limit, 置信限: t; j* F9 [1 w% \5 S' O
Confidence lower limit, 置信下限
+ c* U% @/ k4 X6 E5 vConfidence upper limit, 置信上限! o( g3 V5 P# f( w5 ~
Confirmatory Factor Analysis , 验证性因子分析
& e, I6 u) f8 q1 v! B( x6 VConfirmatory research, 证实性实验研究' n) F; Z4 }) C8 d& }. S H
Confounding factor, 混杂因素& I b) a* v8 y& C0 y
Conjoint, 联合分析
8 D9 L2 Q9 w1 b& I. K* V$ ~Consistency, 相合性+ A9 E# y0 H: m1 B3 N
Consistency check, 一致性检验
1 m4 H" u+ D7 f SConsistent asymptotically normal estimate, 相合渐近正态估计7 g; y% L# H7 x6 t: h' T
Consistent estimate, 相合估计( n; U, q8 z) G( ~& s
Constrained nonlinear regression, 受约束非线性回归0 p$ L4 b: ? |
Constraint, 约束
8 P& C& [+ k5 b* q- c0 tContaminated distribution, 污染分布
- O3 m$ _4 G9 } n' m0 W9 gContaminated Gausssian, 污染高斯分布
; z1 T, A5 @. L2 Z1 k8 YContaminated normal distribution, 污染正态分布
1 i0 f1 `( Q5 H4 v$ L" _Contamination, 污染6 d" c% M9 O6 K+ O$ F- g
Contamination model, 污染模型 Y$ T% K/ {2 |3 s' P3 H! F% L
Contingency table, 列联表
* R2 O; y& A6 OContour, 边界线2 `) H* _7 L% E s9 b& R2 J6 U7 |
Contribution rate, 贡献率
9 B L; P1 d4 U& A5 ?: y% _4 KControl, 对照" S1 z+ Y+ ~+ F& @% W: E8 j
Controlled experiments, 对照实验: x- n- z; y4 ]6 }9 q$ B+ r8 g8 U
Conventional depth, 常规深度- S& v' J& Z# p8 g0 n8 _
Convolution, 卷积+ |+ U/ H8 f1 B
Corrected factor, 校正因子2 j5 Q+ X/ R) e+ [
Corrected mean, 校正均值1 p. _8 H# W Q1 D( Z( b. l1 z" I
Correction coefficient, 校正系数
; Z$ X$ T5 `6 I( G; J7 l5 ?Correctness, 正确性, U1 b; g* s( {+ H' q8 A
Correlation coefficient, 相关系数
) t/ j6 s+ N" L+ h: |. l. b+ ~. wCorrelation index, 相关指数$ g! }4 w$ w* v: |+ w$ t
Correspondence, 对应
; Y6 p( Z" O" }Counting, 计数
$ i1 y* {# N2 H' ?Counts, 计数/频数0 n0 B" h5 h/ Y3 H" [0 O
Covariance, 协方差
5 Y! p6 C3 M: D3 `* UCovariant, 共变
! J' X$ A$ ?, [' p/ wCox Regression, Cox回归0 e m( ?! l0 Y4 J' z Y4 l
Criteria for fitting, 拟合准则" f0 [) G/ ]/ h$ n) p% j
Criteria of least squares, 最小二乘准则3 w. Q8 l% A/ R: B% m
Critical ratio, 临界比: C- ]6 r9 l9 X3 e: t. U
Critical region, 拒绝域: M' S" g: I F) j3 k
Critical value, 临界值
* T ^" X# N% n: P% P5 eCross-over design, 交叉设计
. Y' ~9 I4 n% o ~/ XCross-section analysis, 横断面分析8 K4 V( a1 \, _3 K9 `/ x \( r
Cross-section survey, 横断面调查
2 N0 K6 Y- d6 _" FCrosstabs , 交叉表 " ~4 M& \% z2 x0 x/ V% g3 j
Cross-tabulation table, 复合表6 V6 T3 z D! A# ^ U
Cube root, 立方根
) [! I4 P1 q8 u1 q. s4 w, KCumulative distribution function, 分布函数
. I1 {! I+ n$ E) s' P4 E G/ |+ VCumulative probability, 累计概率
! k$ p% n* X: LCurvature, 曲率/弯曲$ U9 E0 b# }9 e+ A/ _- E' D
Curvature, 曲率
1 ? A1 f5 f( Z0 U1 ?; e ~Curve fit , 曲线拟和
8 j( j: ^+ U- m9 u4 v& K/ rCurve fitting, 曲线拟合
( e5 ^4 P' I1 fCurvilinear regression, 曲线回归0 K* v/ `* o! e# s( H% W
Curvilinear relation, 曲线关系 E$ C. D0 [7 E% K
Cut-and-try method, 尝试法8 L6 W' e& g& o- q, t( W9 }
Cycle, 周期6 K- g5 F* l. `4 A' G& L" ^
Cyclist, 周期性
0 R0 j; F1 N% l" C% C) I8 N) f: nD test, D检验! q" n. w s; [% R$ {
Data acquisition, 资料收集
; l- [' A2 B0 t: r! q8 |5 R9 o! ZData bank, 数据库9 W! E7 n# p1 D$ B& J
Data capacity, 数据容量
1 h+ S* i2 e- c* L7 q3 j' JData deficiencies, 数据缺乏' w( j% I7 _+ c* r
Data handling, 数据处理
! `" s: l1 V9 aData manipulation, 数据处理, o! t+ W* |. p- u
Data processing, 数据处理6 x( a: a' b- c& u2 G
Data reduction, 数据缩减( F* j# |8 s6 o) J6 T
Data set, 数据集
; ^: l* V# e/ t( j4 \Data sources, 数据来源; n! |1 r X, c3 M* V4 k
Data transformation, 数据变换
# f! Q8 c' q& \2 _; gData validity, 数据有效性
* I8 E1 K* l' v9 @Data-in, 数据输入1 @2 f( l& _; H2 F) @/ u
Data-out, 数据输出7 W! n) w' `9 I8 W; X. J) ^$ J
Dead time, 停滞期- H5 y' ~* n' i* }% n$ Q4 V4 w- R+ {
Degree of freedom, 自由度7 @( J( h! N; Y, i- ^
Degree of precision, 精密度
1 E/ p z- s" ]/ u# [Degree of reliability, 可靠性程度
3 K* R& b/ j; iDegression, 递减
4 @4 y4 g8 x" k) Q3 TDensity function, 密度函数
& T: d4 x! T" d" G/ iDensity of data points, 数据点的密度9 o% r: Q0 H2 _
Dependent variable, 应变量/依变量/因变量
/ P& j( r0 H# u7 D6 h! VDependent variable, 因变量" L7 ?) ~. }* Q2 F2 ^ v3 Q
Depth, 深度1 U7 o& V# m% A: b3 m
Derivative matrix, 导数矩阵
4 z" z! `( w% _Derivative-free methods, 无导数方法
' L9 Z8 q4 Q" ]$ Y' U% Z7 `Design, 设计/ G5 y3 o" A4 E0 k/ [
Determinacy, 确定性' g/ Z* F4 j7 u/ Q: B; g/ t2 W+ m
Determinant, 行列式
8 o- n6 d4 R5 ^! WDeterminant, 决定因素/ ?& w+ \6 \; _7 b0 ?" G* f4 g
Deviation, 离差
. k% Y1 J: [9 q4 D% |Deviation from average, 离均差
+ W4 S1 Y! _. C# X- G* q4 UDiagnostic plot, 诊断图2 z/ j3 F$ _" p
Dichotomous variable, 二分变量
% p0 w$ @( B6 u$ e \' UDifferential equation, 微分方程
" E- e5 r% Q4 g+ F( j: aDirect standardization, 直接标准化法
* u) }4 j3 V. W9 o; ~) n4 M3 ~Discrete variable, 离散型变量/ P( r. Z/ p3 C2 W
DISCRIMINANT, 判断
6 {3 S. Y& e. i. a; oDiscriminant analysis, 判别分析7 o7 \5 \" O' b3 `3 S2 t) D1 s
Discriminant coefficient, 判别系数
e6 s3 y0 }4 f8 @9 Y5 yDiscriminant function, 判别值
' c0 r3 k* @/ @5 K7 C. IDispersion, 散布/分散度
$ m, x- R6 ~3 j+ y% g7 c' s9 VDisproportional, 不成比例的
/ D$ T! i$ `9 Q7 a$ S9 pDisproportionate sub-class numbers, 不成比例次级组含量; U) W2 r' r( S4 c9 S! V
Distribution free, 分布无关性/免分布 X8 ~ Z" Z$ V" O {) w" k
Distribution shape, 分布形状
' H" P5 P5 h0 m, [( wDistribution-free method, 任意分布法$ o% ^+ k3 h8 C: C' ~
Distributive laws, 分配律
% h' J+ {* c* B* e. K P! fDisturbance, 随机扰动项
# T/ J' p6 s6 G8 BDose response curve, 剂量反应曲线7 ?1 E0 \) h/ L# z0 ~, ~) t4 G
Double blind method, 双盲法
4 X4 l' p2 _( gDouble blind trial, 双盲试验
* e3 v" _! G$ o- H: `Double exponential distribution, 双指数分布/ E2 h# f/ m& ?( S8 N, {7 ~, G
Double logarithmic, 双对数1 h, Y+ R5 N# w4 s, k0 k
Downward rank, 降秩$ F2 q! B" M4 W+ |! B
Dual-space plot, 对偶空间图
8 M3 c/ c. F. B! _; b& ?4 ODUD, 无导数方法. m1 w6 y" `. F7 N1 R# Y. z
Duncan's new multiple range method, 新复极差法/Duncan新法
" ~! y0 i5 a: {% U( J' q+ v& h, YEffect, 实验效应 i* D4 |5 `, s- j4 ?& b
Eigenvalue, 特征值0 e* o) l7 B& H- V7 f, u
Eigenvector, 特征向量
* e! R' o5 U d" {Ellipse, 椭圆
7 Z& W/ }) \: ^: J' c4 j) eEmpirical distribution, 经验分布
! b3 ^0 |. R( w# l: \* [4 ZEmpirical probability, 经验概率单位5 f; M0 K% B, j- G- b5 b ?
Enumeration data, 计数资料
/ ^ p$ h$ E0 B0 b: d5 `' ]Equal sun-class number, 相等次级组含量
& a: k- O& h) O2 d5 KEqually likely, 等可能0 |9 Y2 ]/ ]* z! {! |
Equivariance, 同变性' w6 T1 X3 n- X2 p/ S1 I( A
Error, 误差/错误6 }7 A4 _, L2 W1 | F" \
Error of estimate, 估计误差
- k! @4 l0 e% E( L& u+ { C& `, r" y2 t# cError type I, 第一类错误
. I8 ?. [0 Y: U& c) iError type II, 第二类错误. f* P5 T5 ] m2 N
Estimand, 被估量7 K/ Q1 P9 M% e, I
Estimated error mean squares, 估计误差均方
# U" ?1 h2 O+ \; x' M& |) v. BEstimated error sum of squares, 估计误差平方和& D( @6 M- y9 r* \7 s1 ]9 l( S
Euclidean distance, 欧式距离
. e3 {4 J+ \0 Q1 mEvent, 事件- B2 Z$ `3 H! C' v; P+ e
Event, 事件+ J5 V" i9 c: y6 d1 `3 {
Exceptional data point, 异常数据点; q9 V8 r/ @. M5 @3 a
Expectation plane, 期望平面
' H7 @$ L# h) U" s& Y; ~: VExpectation surface, 期望曲面
' g, u& Q- |8 \ R6 {. [- mExpected values, 期望值8 ]9 W/ G& }( I: b, u$ G4 G
Experiment, 实验1 P% n$ K' K! P! o" i1 U
Experimental sampling, 试验抽样
( K5 M J3 o; n1 L6 bExperimental unit, 试验单位
' k* \# h9 J) m# ]Explanatory variable, 说明变量
9 v8 @! Q8 N" w( M$ x$ ]7 A% NExploratory data analysis, 探索性数据分析
# L& m) L5 L. l% T1 X0 V: |; Z( `; uExplore Summarize, 探索-摘要
+ _/ Z e, `$ j! m6 H f7 ]Exponential curve, 指数曲线
$ m2 G" }" F- T. K+ m; iExponential growth, 指数式增长) z7 J0 Z7 c# X' F( ^
EXSMOOTH, 指数平滑方法 2 H. R/ C. \4 Q1 x$ v
Extended fit, 扩充拟合
4 z l3 e; B1 z1 _, r- xExtra parameter, 附加参数/ Y" S# G2 o5 [; m& q+ z- O% l
Extrapolation, 外推法
/ I D, {6 o: G1 {$ RExtreme observation, 末端观测值' N7 B4 k- N# o6 u
Extremes, 极端值/极值- W0 S- f+ j' k$ G2 c
F distribution, F分布
' F: {5 m! F( q1 u. c3 rF test, F检验' o: f/ \0 V7 j
Factor, 因素/因子
! E1 n Z) {, H, c5 r% `6 K3 ~Factor analysis, 因子分析
5 d) H/ @' |# H% b- bFactor Analysis, 因子分析2 F/ L; b- Z% p! } \
Factor score, 因子得分 0 \# x; Z# p* d1 [
Factorial, 阶乘2 |( D$ }$ R- p& D& T2 Y! ]
Factorial design, 析因试验设计
2 K0 ~8 a- E5 ^8 x+ e' o: qFalse negative, 假阴性
. a$ H6 M( r. k5 s+ G9 T- Y' OFalse negative error, 假阴性错误# v7 b9 F1 P8 J9 d8 A1 D. G9 I
Family of distributions, 分布族# Z4 [: b3 m, W6 i- I: I8 p$ j
Family of estimators, 估计量族3 M1 T [3 H- ]2 }
Fanning, 扇面/ V- J; o6 r# Q p0 {2 S) U& G0 N
Fatality rate, 病死率
9 c2 F. z1 f3 z0 u, wField investigation, 现场调查9 i% B* e# v+ N2 S
Field survey, 现场调查% I6 t: @- R6 Q4 y
Finite population, 有限总体' O& F |# ~) h9 z/ f9 V
Finite-sample, 有限样本: u; E6 @! W% ]" I
First derivative, 一阶导数
% z8 K4 ^3 b( k3 Y6 g2 u1 D2 E7 TFirst principal component, 第一主成分
7 A1 c% n' o4 M* U" N* j W jFirst quartile, 第一四分位数9 o1 L) v: n% t; V; I
Fisher information, 费雪信息量! k( n1 z& Y+ }/ F7 j6 Q( ^
Fitted value, 拟合值
: F3 r6 ^! X0 N- k, {4 z' y# BFitting a curve, 曲线拟合5 X2 y; L P9 U" T3 w/ `
Fixed base, 定基
4 d4 R7 `9 M+ `# V0 ~% d9 _Fluctuation, 随机起伏
) Z& d! a! v z9 |8 @Forecast, 预测
, q) y$ W# X% H. iFour fold table, 四格表
$ g- A5 r1 I; w& ]: T$ TFourth, 四分点+ ~& E1 k" m Y" A
Fraction blow, 左侧比率
5 f' h/ D7 o3 C* [, e& Y9 KFractional error, 相对误差8 A! a, F- f% X% J
Frequency, 频率
+ j G) J: v. O% c7 a- LFrequency polygon, 频数多边图
/ J, M; Q! P! |1 H3 W( C- Y" \Frontier point, 界限点" H/ y( O g: m! d; y) I
Function relationship, 泛函关系
9 N) c, ?5 T# z0 }6 X( _# Y& _Gamma distribution, 伽玛分布
$ D4 E, d2 t8 g4 v6 NGauss increment, 高斯增量6 x- o# [& p( e5 }( \
Gaussian distribution, 高斯分布/正态分布
[: ?) d& d' @6 ^. g* dGauss-Newton increment, 高斯-牛顿增量' C' Q: n# r) Z4 P# q
General census, 全面普查2 D1 ^% J% X- {+ g
GENLOG (Generalized liner models), 广义线性模型 ( x& n0 C ?; A j' g9 V. p3 A0 Z
Geometric mean, 几何平均数
8 c% c5 f" C! iGini's mean difference, 基尼均差
0 _9 J3 \4 l: q$ O* j2 JGLM (General liner models), 一般线性模型
, |' H `3 Q' g& U" [2 O9 BGoodness of fit, 拟和优度/配合度: V. f1 l6 {2 c: b. c' m
Gradient of determinant, 行列式的梯度$ k. ?) H' }; t+ }, J3 M
Graeco-Latin square, 希腊拉丁方
! K/ s7 s0 W! B! g, G! IGrand mean, 总均值% ]# [2 }. E6 G7 d5 M9 v. O
Gross errors, 重大错误' ^, d- J8 y- E
Gross-error sensitivity, 大错敏感度
, J9 X5 L. y. M9 kGroup averages, 分组平均& {- |' ~* i) T; F2 R" v
Grouped data, 分组资料
% _2 U1 N" Z3 c5 EGuessed mean, 假定平均数: @0 `6 e' p, |4 q* u
Half-life, 半衰期
0 Q8 {4 r+ E* y- u# i7 `- JHampel M-estimators, 汉佩尔M估计量
; j: [9 Q: A9 g# _+ i2 |5 ]1 uHappenstance, 偶然事件2 H' [& [# i5 G' m6 W% [
Harmonic mean, 调和均数% U' }4 |, p) W9 [
Hazard function, 风险均数
7 s* q* U+ B$ g9 u0 WHazard rate, 风险率6 y8 H9 e x5 {+ [
Heading, 标目 + C7 p8 {. [$ g `
Heavy-tailed distribution, 重尾分布/ U/ T+ T0 }1 K
Hessian array, 海森立体阵
( G! w; ], m' ~% }Heterogeneity, 不同质
- Z% g4 ~6 t- q( z* Z K" `Heterogeneity of variance, 方差不齐
4 F% ~3 t; c7 A* g% IHierarchical classification, 组内分组
- f" q3 c! N: p% h5 V8 h% EHierarchical clustering method, 系统聚类法: }/ H' z0 L" X. C$ f
High-leverage point, 高杠杆率点8 O3 r" \0 Y* S) B' `. H+ c
HILOGLINEAR, 多维列联表的层次对数线性模型! [4 P# i3 S' r' B, Z7 n" d
Hinge, 折叶点2 M3 z/ W5 j6 k5 N! t
Histogram, 直方图
5 P! V) ]+ a5 @, Q* o$ {. VHistorical cohort study, 历史性队列研究
8 y: _( _3 F( y& y: \Holes, 空洞
( `' F9 a& U7 `; v7 d) fHOMALS, 多重响应分析& t8 B7 L% A4 R) o
Homogeneity of variance, 方差齐性
3 z$ c: U' u8 c& ?0 r+ @Homogeneity test, 齐性检验; L( U- L4 S; s `, R
Huber M-estimators, 休伯M估计量
% ~* X2 S( N N; O- b) c: xHyperbola, 双曲线
, x3 a# g- K4 _Hypothesis testing, 假设检验
+ t; @- H' M1 E7 CHypothetical universe, 假设总体
& {! ~/ U3 F1 {: T- s3 V9 uImpossible event, 不可能事件3 k. _1 i) E) h
Independence, 独立性
% @( ?( J, V1 R0 W3 t- `$ s# lIndependent variable, 自变量- D% A% D6 K$ @' f
Index, 指标/指数
0 u( x* B0 d, P/ D, S4 |Indirect standardization, 间接标准化法
Z+ R- t7 |% \2 B, r4 WIndividual, 个体0 @8 {2 ?+ e4 `7 p/ k1 ?2 C
Inference band, 推断带
. C @4 }1 }4 H/ p, XInfinite population, 无限总体) c8 J" E, D6 U( W" \
Infinitely great, 无穷大& B- [. e, k |. j& u
Infinitely small, 无穷小$ I, n5 Y7 _: H8 ?5 J: H
Influence curve, 影响曲线
+ E) w8 ^4 o L6 BInformation capacity, 信息容量 ^5 c) D. T; `) _
Initial condition, 初始条件+ ?' y7 ?# m4 N% J% b" [ C& `
Initial estimate, 初始估计值
8 @* Y( m3 t( n# ~8 SInitial level, 最初水平+ Y' Y5 c U$ [. C2 d+ f
Interaction, 交互作用
' C6 F! f* p5 [8 m! ~! [Interaction terms, 交互作用项
! i0 W( s( D3 u4 hIntercept, 截距
7 p# G R5 P% |* e& z- VInterpolation, 内插法6 ?. h/ x# f- X o2 e- |- R# c
Interquartile range, 四分位距
; f* P8 C# y" B6 k, s% X0 RInterval estimation, 区间估计
' g, L0 K/ d$ c- D/ ^+ {Intervals of equal probability, 等概率区间
: c' M& N+ }+ b' t) z$ pIntrinsic curvature, 固有曲率& Z& a8 E: ^+ ?; F" U
Invariance, 不变性
2 X5 i7 |' y! x/ _; M. K% @Inverse matrix, 逆矩阵
8 S: s1 ?/ Q# `- y; J8 bInverse probability, 逆概率
; t* S7 r& o `Inverse sine transformation, 反正弦变换
: v" u8 J! d( WIteration, 迭代
! y* f- h. {0 |7 t" v _: h/ WJacobian determinant, 雅可比行列式
2 o9 h) g/ c9 TJoint distribution function, 分布函数' x o# Z# u8 e; v( G! H
Joint probability, 联合概率
: _8 _& O4 U! s4 V/ s% }0 ^Joint probability distribution, 联合概率分布# }4 Y% j6 x& q) |9 T9 L
K means method, 逐步聚类法/ Z% [5 k) _" K6 A Q* {+ W' T6 u
Kaplan-Meier, 评估事件的时间长度 . Y ?' \. n' a: l$ R7 A
Kaplan-Merier chart, Kaplan-Merier图4 I* G$ S; `; L# r" k2 I
Kendall's rank correlation, Kendall等级相关
0 _, W3 H1 \8 |6 D: _, ?6 uKinetic, 动力学) t; x8 c' Q3 U
Kolmogorov-Smirnove test, 柯尔莫哥洛夫-斯米尔诺夫检验3 t0 [2 j6 R4 `" [$ E
Kruskal and Wallis test, Kruskal及Wallis检验/多样本的秩和检验/H检验& x; N) {" |6 P6 {
Kurtosis, 峰度
9 {. [" m% N, h! RLack of fit, 失拟2 N- L% _# ]+ N. R
Ladder of powers, 幂阶梯/ o* y& q! _" l. P ~! T
Lag, 滞后0 M% Z: V- n# V L$ z" q9 p
Large sample, 大样本% P0 ^ _/ D/ t2 \* D: B; a
Large sample test, 大样本检验
6 U/ H; Q' e3 nLatin square, 拉丁方. j1 B5 u* m0 U7 R
Latin square design, 拉丁方设计6 a, A5 F8 ~* x5 m' U
Leakage, 泄漏
6 r1 m# O( N/ r' @# Y1 ILeast favorable configuration, 最不利构形
' {* _5 W } y9 \) I2 eLeast favorable distribution, 最不利分布
/ z3 u1 l4 b+ T! rLeast significant difference, 最小显著差法+ f6 k; i7 B* p2 L
Least square method, 最小二乘法1 e/ v) \( C+ a0 W$ P6 l3 y0 ]: k
Least-absolute-residuals estimates, 最小绝对残差估计
% |6 x% L$ M; `. G, z8 Q. WLeast-absolute-residuals fit, 最小绝对残差拟合5 ~$ a8 ~, @; A8 a6 \! H/ ]
Least-absolute-residuals line, 最小绝对残差线% |' y6 W6 ?5 s1 _
Legend, 图例
' b7 T4 C: @4 M' C3 e; A+ l, CL-estimator, L估计量
, O: g( H9 w. s# p3 T3 T) q5 OL-estimator of location, 位置L估计量' i: Q( m& E4 c4 @2 C+ y$ c% O7 o
L-estimator of scale, 尺度L估计量
' |1 F& b* _$ |Level, 水平6 _1 N$ ^4 {& M/ r
Life expectance, 预期期望寿命
( q7 R5 P$ N) s8 eLife table, 寿命表
' B) k5 m* z4 s% i# GLife table method, 生命表法0 A' `9 y2 Y. } s2 P' L n: b& ?1 B
Light-tailed distribution, 轻尾分布
: C2 N$ k& i' {( Y V# YLikelihood function, 似然函数" h X. i* c0 P' P/ C0 a
Likelihood ratio, 似然比
& Z8 L, V/ v# _7 o7 A# Sline graph, 线图- G, @# M+ b+ D3 F- O, z+ R
Linear correlation, 直线相关6 }$ k0 r2 R$ J3 }
Linear equation, 线性方程& X# N: E+ W" g4 x, w: m. N0 D5 l# h
Linear programming, 线性规划+ X3 g' }) |. g& |* o
Linear regression, 直线回归
, a5 m/ n3 O% gLinear Regression, 线性回归9 T9 I0 s9 w7 _% q
Linear trend, 线性趋势
# e5 Y$ z6 X. _- @" T' d7 OLoading, 载荷
+ ^8 a7 d# u; {+ ?Location and scale equivariance, 位置尺度同变性3 o) T* E8 t" Z; `* R
Location equivariance, 位置同变性
. F" _ R. C% d0 B8 p! ZLocation invariance, 位置不变性# P \4 @" u2 P! B
Location scale family, 位置尺度族
' {9 ?2 R! H+ j. o1 m1 A4 yLog rank test, 时序检验 9 }; O) g0 A9 b4 [
Logarithmic curve, 对数曲线
4 q9 ]: j5 o" iLogarithmic normal distribution, 对数正态分布5 S6 {% ]8 K- ?% m! O' z( N
Logarithmic scale, 对数尺度
2 K0 f) N" w8 ?% w, @ sLogarithmic transformation, 对数变换
' B' Z! b: k3 |6 s; c1 ZLogic check, 逻辑检查6 U. Q" `1 R% A- u( }
Logistic distribution, 逻辑斯特分布3 W4 Y+ g$ c0 Y# v F2 h" X
Logit transformation, Logit转换% `; u! o* i7 F8 J. r; U+ a6 l
LOGLINEAR, 多维列联表通用模型
8 E) v, J2 F; | G% P- O( \Lognormal distribution, 对数正态分布1 `/ c* D Z; J/ i
Lost function, 损失函数
$ Q* k' y4 r0 N4 F5 v. v$ uLow correlation, 低度相关& f& i* u7 M% o4 s# p
Lower limit, 下限7 Q" d4 x4 z4 b5 e4 M7 c
Lowest-attained variance, 最小可达方差3 U' x. y& T1 ^( Z o
LSD, 最小显著差法的简称. T7 ?8 o& Z8 _" p' n8 ^
Lurking variable, 潜在变量
9 ?5 n9 @6 A2 O7 e& Z" x* ^Main effect, 主效应" X# ] o7 V0 w( Z
Major heading, 主辞标目 O8 M2 A6 F' |9 p/ |! w8 j4 e& ^
Marginal density function, 边缘密度函数
" r( Z9 z* h! rMarginal probability, 边缘概率
5 s w2 V" j4 F- P B4 bMarginal probability distribution, 边缘概率分布
: H9 l1 @ `) X0 v- f9 j* v, s- aMatched data, 配对资料
9 R. k% p1 _ R( R( o0 uMatched distribution, 匹配过分布( w3 z0 f" [4 ~2 p6 ~
Matching of distribution, 分布的匹配
% W- |$ Q6 U# h/ j/ l9 ?Matching of transformation, 变换的匹配
' p9 H# l; J2 O3 ?Mathematical expectation, 数学期望2 ], h( r1 S7 o/ l
Mathematical model, 数学模型
/ x" T3 _1 \7 d. fMaximum L-estimator, 极大极小L 估计量
9 l. r1 N: T3 S( V0 T+ u/ MMaximum likelihood method, 最大似然法# v% w+ |0 l, i+ q- p" f4 z
Mean, 均数
1 K: G8 U. l; n4 u' y% L& nMean squares between groups, 组间均方; R4 f* h# M* @8 [
Mean squares within group, 组内均方% B, y1 k, a/ B- m+ e, _0 ?
Means (Compare means), 均值-均值比较
7 M1 x P! n9 [" {Median, 中位数 [$ W3 P/ Z c0 n
Median effective dose, 半数效量" K# T# C$ {0 X) M
Median lethal dose, 半数致死量2 T* g) q# Z9 U" P/ Z
Median polish, 中位数平滑. K" ~ B. O6 p6 W# \# S0 H3 Q% N7 l
Median test, 中位数检验- c; @9 N; r: i5 w3 W( \
Minimal sufficient statistic, 最小充分统计量' |+ s; a2 S+ d
Minimum distance estimation, 最小距离估计
) D' \; r4 m& i# \$ k6 e4 \Minimum effective dose, 最小有效量
, j, G+ D& P/ E0 G8 b. IMinimum lethal dose, 最小致死量7 A3 M1 J, h+ W# ^# }" E+ i- D& q
Minimum variance estimator, 最小方差估计量
S; D w, M' \MINITAB, 统计软件包) i8 D+ w6 t% z% k( P5 x9 f" `
Minor heading, 宾词标目2 `5 p/ c3 W6 @% j. W# v
Missing data, 缺失值
, W4 V+ A1 c0 Q9 `( O' e0 y1 z8 TModel specification, 模型的确定; [, k1 X% G% O$ s/ |5 S- O
Modeling Statistics , 模型统计
; O O' r4 w: u6 B8 }Models for outliers, 离群值模型
5 ^' w5 R+ r) V' F( hModifying the model, 模型的修正8 Y+ u9 o# l0 Q! u% o4 W
Modulus of continuity, 连续性模
+ a( `6 y' {0 ~0 B2 W; q+ Q EMorbidity, 发病率 & v# j$ E: U* z2 Q& ^4 y3 g4 S
Most favorable configuration, 最有利构形, e+ L' {, k( \8 w# o
Multidimensional Scaling (ASCAL), 多维尺度/多维标度! }3 l! P3 |- E7 n" l( [
Multinomial Logistic Regression , 多项逻辑斯蒂回归+ l" B G0 z- k- T/ c
Multiple comparison, 多重比较 Q4 S- u% h) {; Y
Multiple correlation , 复相关
. q% z1 X4 W1 ~Multiple covariance, 多元协方差
* Q/ E1 `& c5 B5 Z' v3 ] jMultiple linear regression, 多元线性回归
) r" S7 X* F, P _9 VMultiple response , 多重选项5 |: L2 n. O/ M* Q! b/ k
Multiple solutions, 多解: S- p; h- Q( o1 ]# t/ f
Multiplication theorem, 乘法定理
" L/ e8 i" O9 l' i( Y: H1 c mMultiresponse, 多元响应; n8 c4 ^: c/ _" Y; z, q. @
Multi-stage sampling, 多阶段抽样; ?5 M0 G+ `; B" d) u8 z/ s
Multivariate T distribution, 多元T分布5 p; R, i9 n$ X1 g# v2 e5 W! ~
Mutual exclusive, 互不相容2 e& w- E/ H2 z0 O0 W' H8 h
Mutual independence, 互相独立
' ~1 b; f+ d0 Q) c' k4 o9 F- ONatural boundary, 自然边界
4 k, e$ H% R3 o8 r5 h& {Natural dead, 自然死亡
1 q6 t. s. r6 j; ANatural zero, 自然零0 y5 g# B& _3 {
Negative correlation, 负相关) a, S% A1 P4 z6 {, Q
Negative linear correlation, 负线性相关
* p" |' u. J, E! xNegatively skewed, 负偏1 I- Y/ K) W3 x$ Z8 ~# p
Newman-Keuls method, q检验
7 Z4 J5 m9 k3 C) S6 VNK method, q检验0 e: k# Z2 }; R0 c6 [6 I% j) {. V
No statistical significance, 无统计意义
+ r w& Q8 i; UNominal variable, 名义变量
+ c; A7 U- L( \9 e( t6 WNonconstancy of variability, 变异的非定常性3 T1 X3 G: z' x- T* i
Nonlinear regression, 非线性相关0 N- A2 A- P0 D' T
Nonparametric statistics, 非参数统计- ^6 m2 X$ \+ Q# ?: }6 ?. h
Nonparametric test, 非参数检验
6 e) O9 }9 b. H6 @) V* ]Nonparametric tests, 非参数检验
# G) Q1 ^+ D" g, K6 {% k( XNormal deviate, 正态离差
8 R" D t5 j; Z3 e$ R) CNormal distribution, 正态分布$ } }$ Y6 s8 }5 l
Normal equation, 正规方程组: J. q% h9 O5 x$ G: o) v. [% _
Normal ranges, 正常范围
8 A1 \0 ~9 j% O. bNormal value, 正常值
^7 E( U6 |- ?+ K9 Z1 jNuisance parameter, 多余参数/讨厌参数
! U; Y+ C1 T) j3 [3 b3 BNull hypothesis, 无效假设
) h3 ?9 x' c- [- d/ o9 w; nNumerical variable, 数值变量
' J( v: a2 ?$ M2 T; X5 JObjective function, 目标函数
( f+ E, n- l: X% W9 VObservation unit, 观察单位
; C$ a R0 o0 A/ eObserved value, 观察值
: x0 u) j) o3 Y3 S1 AOne sided test, 单侧检验
9 ]# s6 I# X4 C3 e0 Y0 e' O% g+ }7 j+ lOne-way analysis of variance, 单因素方差分析
+ d3 r j4 Z* r( s. ] xOneway ANOVA , 单因素方差分析6 y" a$ j- W9 ?$ M4 b6 r5 o
Open sequential trial, 开放型序贯设计, Y+ j* p3 _" W5 _# f
Optrim, 优切尾
' a% B# t! j/ C+ C5 QOptrim efficiency, 优切尾效率
4 h7 Z, P: b5 x9 f) B- ~Order statistics, 顺序统计量9 R. K# R, {: q( Y2 y
Ordered categories, 有序分类$ s+ ` s$ U- f6 _! A5 D+ k7 B
Ordinal logistic regression , 序数逻辑斯蒂回归6 m+ a0 p3 a: r/ l2 A# ~& Z
Ordinal variable, 有序变量
, z' K0 l( O y: G% tOrthogonal basis, 正交基
! { n& m3 s9 MOrthogonal design, 正交试验设计
- {8 _; d) `; O% D% p" \! N5 FOrthogonality conditions, 正交条件
. I& j* N; H! x+ Y( K* o1 DORTHOPLAN, 正交设计
: B6 H# d6 H9 |7 p; Y% pOutlier cutoffs, 离群值截断点 m; g, d2 c% y6 K, `
Outliers, 极端值
/ c( b7 U2 `$ F5 E2 E% o1 }/ FOVERALS , 多组变量的非线性正规相关
+ m) j4 ?) S7 o9 S) NOvershoot, 迭代过度
1 S9 U0 A; ?9 ~7 xPaired design, 配对设计
0 P$ p3 |9 N' k( w1 _) ^Paired sample, 配对样本, E1 V0 c( O$ l: o6 _# X
Pairwise slopes, 成对斜率
6 `( d3 k, n* j7 R/ h3 f) H' S& zParabola, 抛物线
6 w* w% Q$ H& M+ iParallel tests, 平行试验
4 \" f0 q+ H) x. H, y; zParameter, 参数
& @" k0 d/ D" f6 RParametric statistics, 参数统计
( q) L: n- k2 D7 F. `1 SParametric test, 参数检验
1 J2 o/ [- J$ ]6 n1 {( k+ pPartial correlation, 偏相关% k( G- j1 C/ m2 p
Partial regression, 偏回归+ W+ Z; o7 F3 B0 A) G# _, t
Partial sorting, 偏排序' T0 C( }; {; c' B% o1 U$ a. w
Partials residuals, 偏残差: `/ Z7 F1 r# D
Pattern, 模式
, F) d2 }- W; ~ Q; xPearson curves, 皮尔逊曲线
3 x# D) Y: g$ j1 `! e! c4 H& ZPeeling, 退层7 L1 B ]% U5 [* u+ N0 R
Percent bar graph, 百分条形图4 K, O. H# G4 b4 J" p a5 T% u
Percentage, 百分比
" f0 J/ h, }; t+ o3 o) }Percentile, 百分位数' o6 E/ f# S0 s0 p5 `9 k
Percentile curves, 百分位曲线5 k, g+ d/ [7 W5 j
Periodicity, 周期性
9 D7 U& H$ v9 L8 fPermutation, 排列
6 n$ N3 Q0 b% F5 l4 k4 HP-estimator, P估计量, y: X( l7 V8 X% r8 ?
Pie graph, 饼图
! v6 M" c8 T7 t1 ?, x3 lPitman estimator, 皮特曼估计量% P/ \0 P- c0 X! D, @0 a& m: x
Pivot, 枢轴量
) E8 f t i1 MPlanar, 平坦
* ]! [, J( m8 w" {1 L" ~! }Planar assumption, 平面的假设
: u+ i* U# a" X o0 k4 S% ?PLANCARDS, 生成试验的计划卡
# J' p- z! t7 ]8 {! h* d2 U hPoint estimation, 点估计
4 a7 x2 T, h1 h: h TPoisson distribution, 泊松分布7 {0 ]& ?! ?0 \# C+ ^- f( ~' c3 G4 g
Polishing, 平滑. k. }# e0 D6 E& f% K' h* i- z
Polled standard deviation, 合并标准差
! g% q+ l [+ b( _! G- L' PPolled variance, 合并方差
! X. s( e: p* C5 YPolygon, 多边图- X, V; x' k1 F
Polynomial, 多项式
' A W4 k' d+ ~Polynomial curve, 多项式曲线 ]1 W, J8 ]( B9 f9 y
Population, 总体
' K& e( _" i$ gPopulation attributable risk, 人群归因危险度
3 e- f, Y. l$ r1 i# {Positive correlation, 正相关
7 U3 _2 I4 h' ]% R: h9 vPositively skewed, 正偏
2 t4 W+ S. [5 v. I, vPosterior distribution, 后验分布
% q$ l- E& P4 O- |( p' n7 CPower of a test, 检验效能
) J. u U- v+ C! J }. q" O3 O) jPrecision, 精密度* O: b: c. O+ p
Predicted value, 预测值( O+ ]8 E8 a; ]# g
Preliminary analysis, 预备性分析
" M1 C. r% f/ b3 z' N; v/ M R* @; aPrincipal component analysis, 主成分分析
, M" A( Q2 N6 `! }: ^: {" dPrior distribution, 先验分布
8 Q. o( z" T0 kPrior probability, 先验概率, M& L; |0 P6 [! f
Probabilistic model, 概率模型: V; ]/ L3 D* n' l6 O
probability, 概率/ `/ M6 C3 A8 B5 q# t
Probability density, 概率密度" Q" M1 F; e n+ J
Product moment, 乘积矩/协方差* R: ~5 O3 L) o- z7 i
Profile trace, 截面迹图
1 W* h8 X' j2 e, w# X- r7 T( uProportion, 比/构成比% U+ D7 v! }- ^6 H% p2 _
Proportion allocation in stratified random sampling, 按比例分层随机抽样
* e0 a+ W3 M6 o' C+ aProportionate, 成比例
. |7 H1 P0 B$ C+ I1 v4 gProportionate sub-class numbers, 成比例次级组含量
& I; p4 T7 U1 ^/ M% kProspective study, 前瞻性调查& F8 Z- O7 N6 T3 B* d: \ h( x+ c9 J5 r
Proximities, 亲近性 8 ?1 o' L5 p% a3 Q9 q
Pseudo F test, 近似F检验
I& Z" {- T/ v2 s6 i+ DPseudo model, 近似模型2 K. c. Z; \1 k" F. K W: O0 A2 M
Pseudosigma, 伪标准差; k. S* i( j' c4 r$ W! T
Purposive sampling, 有目的抽样5 q; h* [! f0 D$ n. R
QR decomposition, QR分解
" H2 y& U# n! F3 ]% I4 cQuadratic approximation, 二次近似4 @* {3 k% e5 o% t4 x
Qualitative classification, 属性分类
( k6 B* h6 v6 A8 ZQualitative method, 定性方法
. J d) p- R8 @1 n2 X, tQuantile-quantile plot, 分位数-分位数图/Q-Q图( [6 K5 j' \0 N# [
Quantitative analysis, 定量分析" a g- ?: f. [9 P3 C
Quartile, 四分位数
8 q& j9 W' z$ m* U' l D3 aQuick Cluster, 快速聚类
* N2 p* Q' o" X; L. ^( jRadix sort, 基数排序
2 y2 j* W: B8 QRandom allocation, 随机化分组6 q; ~; o! p8 F2 @: {0 x' R
Random blocks design, 随机区组设计
/ n- ?7 L! f$ p1 G: {Random event, 随机事件8 Y) h$ }" X9 a/ p6 R$ `
Randomization, 随机化. x; E1 |. b% H4 x$ j* o6 i1 d
Range, 极差/全距
5 K: T0 ^) u y6 e h3 r6 n% oRank correlation, 等级相关& U# i r0 J/ Q% A' i
Rank sum test, 秩和检验4 f. B& H# F) A2 N; m1 l! i0 \
Rank test, 秩检验& }' N" u1 v5 D/ ]& X: k+ t& W2 g
Ranked data, 等级资料6 X4 z/ E Z9 \' N, E" X* U u; j
Rate, 比率
4 R; e2 S' o$ G6 X# u% }Ratio, 比例5 Y& z7 H8 ]& A) A$ H7 M$ w
Raw data, 原始资料% ^6 n3 o1 F# n# J$ R, n
Raw residual, 原始残差' m4 N, G. E* T6 n7 H, G
Rayleigh's test, 雷氏检验
' t1 u1 o/ T# v' r7 sRayleigh's Z, 雷氏Z值
: o6 S2 F7 I- E; l* h) bReciprocal, 倒数$ `7 o. s* ^, X) h, z4 }
Reciprocal transformation, 倒数变换* ^5 x% @5 \6 o
Recording, 记录. p# x& d5 g# X! Z W
Redescending estimators, 回降估计量
0 K( N: ^2 T7 B ]& y1 GReducing dimensions, 降维
4 W9 T9 K9 Z+ c, G3 Y6 z/ Z; SRe-expression, 重新表达
) P: A3 x; Q# d7 ~+ t2 Y! MReference set, 标准组
( \" E* K4 ]1 I# Z, ^Region of acceptance, 接受域
# r" A1 G) {+ b$ f, y1 V4 v* W8 qRegression coefficient, 回归系数
2 U- I! L x f* m( z. nRegression sum of square, 回归平方和
2 \- T: q# |0 R; Z5 G! t$ }9 ZRejection point, 拒绝点0 ]( z: o% [% v% e' E7 Q
Relative dispersion, 相对离散度6 N2 l( X* x1 {% Y0 [! g$ e" f* f9 N
Relative number, 相对数# o4 L, l- [+ E( [# s' z
Reliability, 可靠性( E' L# E. G0 B" M9 L
Reparametrization, 重新设置参数
( a, c9 U: w' o' zReplication, 重复
& k9 x$ m. O' n( t$ IReport Summaries, 报告摘要
8 A: P: C* b+ Q2 T9 wResidual sum of square, 剩余平方和
$ B" p+ _9 _/ @/ zResistance, 耐抗性
; s- z5 }' O8 `5 f, m+ E3 |/ Y% P/ m* TResistant line, 耐抗线
# o$ s- P( O6 Z9 B& A, E0 iResistant technique, 耐抗技术9 [" h' K M0 E r) P. }
R-estimator of location, 位置R估计量
2 k! ^ {8 Z$ P$ l; RR-estimator of scale, 尺度R估计量5 R, f0 A5 A2 Q3 U' d, J j0 \
Retrospective study, 回顾性调查6 b+ }, w4 A1 o" K
Ridge trace, 岭迹; I/ C' I* M0 k8 |/ q5 v: m
Ridit analysis, Ridit分析
2 ^' n5 q$ ]: p4 sRotation, 旋转
9 U, L% N+ Q/ z4 I6 s, O V' FRounding, 舍入; `: u+ n+ t6 b* g- c# c
Row, 行, e4 c0 k5 L$ G" S2 M. E" s$ y
Row effects, 行效应* v6 C- X0 P8 X5 A
Row factor, 行因素) {4 V) M% T( f' k
RXC table, RXC表8 U% i. |- Y4 I4 n3 B
Sample, 样本+ C0 y# L: f3 L! A5 b, z* G
Sample regression coefficient, 样本回归系数/ g/ p0 P0 Z: e' V3 M
Sample size, 样本量4 w3 \7 ]) Q6 X# b# G
Sample standard deviation, 样本标准差: Y: q! u8 u _' E
Sampling error, 抽样误差, b1 N" Y2 k; v$ `
SAS(Statistical analysis system ), SAS统计软件包
7 y6 o; M& i' R8 IScale, 尺度/量表
4 Z& T c9 D+ ]. b# K- d4 i0 P5 KScatter diagram, 散点图
. z9 `0 [( J b! d. B$ K5 R6 bSchematic plot, 示意图/简图
! b% F5 d' M ] I5 |Score test, 计分检验9 ]8 _+ [- T5 t7 T
Screening, 筛检
" y8 z T: Z: ?1 ?9 S8 oSEASON, 季节分析
; x$ t y* b( J$ BSecond derivative, 二阶导数. T, d" H$ m! ? C+ l3 [
Second principal component, 第二主成分9 W6 ^. N6 t! S0 z$ }: D. j, m
SEM (Structural equation modeling), 结构化方程模型 9 c! X" j* ~- K) {
Semi-logarithmic graph, 半对数图
& b% T# _7 g7 S& o# ISemi-logarithmic paper, 半对数格纸
# `% e$ Q( T5 ESensitivity curve, 敏感度曲线
/ q7 M: j3 n& V T. X8 nSequential analysis, 贯序分析
5 W. |$ k. i9 }Sequential data set, 顺序数据集
$ ^9 R. h! w- t' X% w) ISequential design, 贯序设计
/ k" U" Y# A5 @) qSequential method, 贯序法
/ y, X$ K* J6 J+ P& u. s4 PSequential test, 贯序检验法
$ A" g, t- u* y7 T! S- Y; WSerial tests, 系列试验
( n$ ^; o3 y; |7 TShort-cut method, 简捷法
' Q1 n! T( M$ p- aSigmoid curve, S形曲线 ~1 j2 g+ S0 j
Sign function, 正负号函数3 B" a: s# U+ z9 T4 B% p+ A
Sign test, 符号检验 ~/ F) n& j: f
Signed rank, 符号秩
) i* X$ K7 f, f* T4 S3 SSignificance test, 显著性检验3 n* ?; C, q0 E. |, J$ r
Significant figure, 有效数字8 z8 e1 e3 I5 `1 x. R2 j
Simple cluster sampling, 简单整群抽样
1 z7 w5 b8 ~( U- Q% D! t& R7 b3 U2 gSimple correlation, 简单相关
7 F O& g7 q, N5 M2 ]4 z0 V; zSimple random sampling, 简单随机抽样
; _0 z( E% t4 Q' SSimple regression, 简单回归
8 ~: ]+ L) ?9 }# c) I esimple table, 简单表
! a; F$ q) M1 d) H/ |8 [8 WSine estimator, 正弦估计量
# I7 o; p/ R/ _9 aSingle-valued estimate, 单值估计
0 L" s4 }( s: ~6 _. x: A1 _Singular matrix, 奇异矩阵
% Z" P: o7 |7 R2 r1 ]- _1 q }Skewed distribution, 偏斜分布5 Q* z, b) X! @+ M6 B4 ~2 M
Skewness, 偏度. F6 H" F g h/ |
Slash distribution, 斜线分布" ]$ E2 W: t0 |( Z& \
Slope, 斜率, Y* {: X6 t% U8 a, J# W
Smirnov test, 斯米尔诺夫检验
" }$ s1 _! h' P1 kSource of variation, 变异来源
, v7 O' I# P' I% W+ ?6 N* s* B, b7 \Spearman rank correlation, 斯皮尔曼等级相关; V" w( n: w# ^7 Y1 |
Specific factor, 特殊因子7 c ^$ _# ]7 \# j
Specific factor variance, 特殊因子方差
! V: g/ G7 S) B: YSpectra , 频谱
; q5 k$ g- v8 u$ r$ ?8 l- f0 S: ASpherical distribution, 球型正态分布
7 ~/ F+ |: U" fSpread, 展布
* W4 j7 W- l1 \+ l p( s% DSPSS(Statistical package for the social science), SPSS统计软件包) W1 B1 {: c* D) I/ \+ [
Spurious correlation, 假性相关
$ V9 o/ x/ O* o8 |& O l# G# GSquare root transformation, 平方根变换
% o4 F" [* x/ pStabilizing variance, 稳定方差
+ U8 v1 H+ \$ c9 p9 X$ d; KStandard deviation, 标准差( h7 X' n) k: q. G0 k
Standard error, 标准误
$ D- V. ]! K: T" zStandard error of difference, 差别的标准误5 n. L* G/ V1 z' ]5 ]8 s& a- \
Standard error of estimate, 标准估计误差
A9 I. `7 [4 ]5 wStandard error of rate, 率的标准误
& W. ]. Y- Z2 m% U# \Standard normal distribution, 标准正态分布: s/ E h0 L g# z7 _1 D
Standardization, 标准化
0 O- R* k% E# x0 yStarting value, 起始值3 `. A. L- K" Q/ H+ [6 U4 ?7 s) {
Statistic, 统计量6 C6 n8 F% @' h0 o2 w6 a
Statistical control, 统计控制
$ I. T- l1 w/ sStatistical graph, 统计图
9 H; L- k* }; t: V% D* T& m$ LStatistical inference, 统计推断
5 R. f5 c! M( O$ k4 cStatistical table, 统计表# @* G( o$ b+ B. V+ r5 ]( j
Steepest descent, 最速下降法- M" H, B x: y7 Y: Z0 l7 f, o# a
Stem and leaf display, 茎叶图
( o$ K+ G% m1 E: ]% k3 L& W/ PStep factor, 步长因子
% P# K3 b6 d7 y5 [2 tStepwise regression, 逐步回归
. ]) f$ M; N i3 e( w$ p X0 L4 JStorage, 存, B* v! d, S+ k% A. _3 P
Strata, 层（复数）) D- S: X0 `/ O. {
Stratified sampling, 分层抽样0 A2 Z( s5 _& ^. {& D ]. f( ^7 A7 @
Stratified sampling, 分层抽样1 e+ O% J- u5 c. E
Strength, 强度" b* H+ `% b" K+ |1 {
Stringency, 严密性
Q; i1 @5 I$ ]. I# ^Structural relationship, 结构关系4 x! d1 c& H( d
Studentized residual, 学生化残差/t化残差
/ u: W+ E# j* k% ]8 G3 |4 CSub-class numbers, 次级组含量
5 W2 D ~1 `$ k4 d& h+ |" ^Subdividing, 分割$ y' _- l3 u* G, B7 e7 M2 f# E
Sufficient statistic, 充分统计量
& }( k# O- O/ n d& fSum of products, 积和
* N7 b! \ h0 @" Q$ \. F) \Sum of squares, 离差平方和
; |; |0 M1 I# {! _% DSum of squares about regression, 回归平方和7 W% Z5 H1 H1 H: X
Sum of squares between groups, 组间平方和0 q7 x: A- L# f4 s0 |$ T
Sum of squares of partial regression, 偏回归平方和
, `% p9 o8 U0 d. }, M, |9 P' A5 N# PSure event, 必然事件$ |( c, h2 ?* Q
Survey, 调查' X h4 D* c+ y: E1 |( q' g3 S' I
Survival, 生存分析
6 ?& Q- q* a; Z& }6 H- t! H7 sSurvival rate, 生存率2 @* `; t, V% u' e7 s, o- O
Suspended root gram, 悬吊根图
4 p+ i2 c; J# x+ G1 l6 HSymmetry, 对称& N- h Z" q L
Systematic error, 系统误差4 f; t* H; H! i/ v: @, b3 R
Systematic sampling, 系统抽样3 B) o' G! B7 `, q D& E
Tags, 标签0 u% }: k+ ]% w" A B9 r
Tail area, 尾部面积
4 Z4 R: j( t' L4 e4 qTail length, 尾长
% p6 d. q' j v* z. QTail weight, 尾重
8 a) e7 _( M# \ E7 J% u- FTangent line, 切线2 X4 {; Z) R$ r I2 ^
Target distribution, 目标分布
9 o/ e8 w# [; G: h8 wTaylor series, 泰勒级数
) |+ G, b# q I% C' O" ATendency of dispersion, 离散趋势$ G% {. e9 i9 {) ~7 N
Testing of hypotheses, 假设检验- S' e/ V- a0 s2 |0 h& A* l4 w: I
Theoretical frequency, 理论频数3 ^ t' Z* z" V' q9 F( u
Time series, 时间序列
( ?$ d; q8 p2 h5 R& bTolerance interval, 容忍区间
9 p5 s# T, t. s1 J7 [5 ] z' t7 KTolerance lower limit, 容忍下限& n" U$ c3 A1 s, N* J2 `" X
Tolerance upper limit, 容忍上限4 ^1 q6 @/ ]$ \
Torsion, 扰率 V) B3 K) V5 c( Y
Total sum of square, 总平方和
. |, j% \+ b' pTotal variation, 总变异4 ]4 V3 \& B6 t1 h" i
Transformation, 转换/ P5 I% @5 x0 U8 J" g( \
Treatment, 处理0 `! X6 H; a( S# e" B6 T P6 @
Trend, 趋势; p8 M7 [' r. `
Trend of percentage, 百分比趋势7 \7 M5 Q% C1 A3 S
Trial, 试验
3 I/ P* K8 J; I: m0 }/ ITrial and error method, 试错法1 o* u" @' L& E7 Y
Tuning constant, 细调常数
; E, u' I: ~8 p3 z$ BTwo sided test, 双向检验$ _1 b5 z- z/ u1 m& T* [2 O4 i
Two-stage least squares, 二阶最小平方
* p e4 n+ f6 [! h% N- y' |+ G6 PTwo-stage sampling, 二阶段抽样
$ U6 u5 w6 q# STwo-tailed test, 双侧检验
' K) V( K! n0 G; c3 ITwo-way analysis of variance, 双因素方差分析6 O* k. e( z' I- j7 H4 e. W
Two-way table, 双向表9 _; c, q: m! Y3 t7 Z
Type I error, 一类错误/α错误& b& E- j9 _; K3 `/ X6 j
Type II error, 二类错误/β错误
1 j' Y* D. ]1 X: v" X6 PUMVU, 方差一致最小无偏估计简称$ v7 g1 e, Y& Z% E3 e$ a. G
Unbiased estimate, 无偏估计
: {% J& a- A# x/ m" S$ c; f% }0 oUnconstrained nonlinear regression , 无约束非线性回归+ K" i3 V2 H5 q; c% {4 J
Unequal subclass number, 不等次级组含量' N" W/ S% l. k) A
Ungrouped data, 不分组资料
& U, d! `$ ^5 M9 p. R9 YUniform coordinate, 均匀坐标
7 p2 O* L9 ]5 r* _% e- k! YUniform distribution, 均匀分布
4 L) d( B" t! o: ]Uniformly minimum variance unbiased estimate, 方差一致最小无偏估计
; v: o2 ` t! p& LUnit, 单元9 \% d/ J) U3 A
Unordered categories, 无序分类3 h e U. `9 P: q
Upper limit, 上限
, j! Z# I- y- ?% @" E5 L8 HUpward rank, 升秩5 f' }8 Q& U) y5 P6 o6 z: ]& o
Vague concept, 模糊概念$ b; ^. u9 ^1 d* g8 G
Validity, 有效性' o1 s0 X% I; I f8 d' R
VARCOMP (Variance component estimation), 方差元素估计
6 m* \' ?6 U4 n: ZVariability, 变异性
' C+ ^9 Z" n6 F! G/ GVariable, 变量
: W0 ~, Q- S# b' l3 o: EVariance, 方差
0 e3 Z5 e6 d, ~* s0 GVariation, 变异
. v+ d( J; R6 p1 [% Y$ _, k1 y) tVarimax orthogonal rotation, 方差最大正交旋转; n: `8 D* ]7 n1 F
Volume of distribution, 容积
. I8 i3 c# N0 l; I) K7 AW test, W检验
4 X# o% x$ V# j4 Z& O/ `Weibull distribution, 威布尔分布
5 x2 [% U* i p; _8 ?" \Weight, 权数+ A% I" X7 k# l1 n
Weighted Chi-square test, 加权卡方检验/Cochran检验" T4 N/ V* N! Z" M) ?* d
Weighted linear regression method, 加权直线回归& ?$ y- W0 s2 `# z, r
Weighted mean, 加权平均数3 n) u& z- } k4 z: F7 g* w! z6 s
Weighted mean square, 加权平均方差
# y8 E9 {1 Y- gWeighted sum of square, 加权平方和
. J! W+ U5 n7 Z Z u HWeighting coefficient, 权重系数. P) K5 P$ E0 d+ [+ |* ]/ p+ `3 |+ A
Weighting method, 加权法 4 \0 T3 M$ g# s$ Y8 B
W-estimation, W估计量 T6 {0 }" X& O+ ^: U/ \4 P
W-estimation of location, 位置W估计量
3 ^1 H, D5 p- gWidth, 宽度
3 Y q5 i8 ?- y: Z0 U* s0 FWilcoxon paired test, 威斯康星配对法/配对符号秩和检验
( q2 X8 n' w; p; e9 W% [- [1 LWild point, 野点/狂点
5 @. a, Z* K U, ~. V* dWild value, 野值/狂值6 E& w4 [& |3 i1 z4 S
Winsorized mean, 缩尾均值3 K7 `2 d7 A" d
Withdraw, 失访 * ?1 g- O$ p3 r1 R, j# Q
Youden's index, 尤登指数1 @& N+ C: f( z* A' M
Z test, Z检验& Y) H [4 D& |) [
Zero correlation, 零相关: K1 A6 q) \% V+ O; Q4 _
Z-transformation, Z变换 |
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发表于 2009-1-6 22:05
