|
|
Absolute deviation, 绝对离差, e% l) \! _9 d! w! i
Absolute number, 绝对数0 l' X. C, t! L# {% ~3 O' H, o
Absolute residuals, 绝对残差
+ \3 S( k2 Q1 @5 V5 K# ^, R$ UAcceleration array, 加速度立体阵; S% y' p- x6 c
Acceleration in an arbitrary direction, 任意方向上的加速度- T& W0 Y, y* m/ o, S0 V/ z: X4 Q6 m
Acceleration normal, 法向加速度
' _8 |" G n$ {Acceleration space dimension, 加速度空间的维数
& B* x; w# G. Z7 K+ TAcceleration tangential, 切向加速度
) ?0 @5 x- L9 D7 o5 U; vAcceleration vector, 加速度向量9 y u3 _% d8 d6 B1 d( \
Acceptable hypothesis, 可接受假设
$ \: T5 f; W: n3 nAccumulation, 累积' Y5 G9 s, `* {# o
Accuracy, 准确度
- G h; W9 I6 j6 E y" K( yActual frequency, 实际频数
$ O# o* i5 o# ]' v. T" nAdaptive estimator, 自适应估计量
; v4 ]5 F" L. Z2 C: P) e& @: t! lAddition, 相加
0 d" x3 m/ M$ `% qAddition theorem, 加法定理
) B$ K4 n5 K' z5 j1 u$ Z6 zAdditivity, 可加性" u4 O9 Z5 E3 U
Adjusted rate, 调整率
" ?/ W- ]9 w+ x8 u1 i( s, x$ @Adjusted value, 校正值
' h/ ^ l3 o, |+ W' OAdmissible error, 容许误差
# B( z* m3 P" ?1 }, @Aggregation, 聚集性
' X3 ]1 b) y7 y# Z- iAlternative hypothesis, 备择假设$ i m# o6 G# D- I9 C! ]+ v5 n
Among groups, 组间
, M; l& A/ o5 i. `- l! t8 ]% S9 r9 A, |0 qAmounts, 总量! \8 Z! K- L) a/ A8 |# N" R
Analysis of correlation, 相关分析7 R1 r: C) X' K6 ~ @/ @
Analysis of covariance, 协方差分析( K* Q8 |8 H( \, R
Analysis of regression, 回归分析' g1 d; @4 g b* R' K7 [) ^6 ^4 k
Analysis of time series, 时间序列分析
* g! p: S. m; A% V7 K' u: EAnalysis of variance, 方差分析- l2 k9 n' o: j% O% E2 ^
Angular transformation, 角转换
, Y& Z6 W. B8 M3 N2 GANOVA （analysis of variance）, 方差分析
& X) \, M5 W: U9 q$ r1 G G' AANOVA Models, 方差分析模型
$ x6 f/ A0 n8 |) y5 _/ RArcing, 弧/弧旋
1 ~9 J; Q, @1 A. `1 L# ~Arcsine transformation, 反正弦变换3 Y3 e6 Z, g. S! e- v
Area under the curve, 曲线面积
' X! V& D$ X h' qAREG , 评估从一个时间点到下一个时间点回归相关时的误差
! y/ Y6 F" W3 x+ VARIMA, 季节和非季节性单变量模型的极大似然估计
+ j; O* u" s8 H& `/ P; L6 HArithmetic grid paper, 算术格纸4 B% [5 a, c4 j% B
Arithmetic mean, 算术平均数8 F3 o5 I3 d4 l# j h9 z2 M+ y
Arrhenius relation, 艾恩尼斯关系9 [0 _8 X0 [0 f' d) W# z
Assessing fit, 拟合的评估& W/ z1 i8 Z$ p- S" W
Associative laws, 结合律
: t8 i3 \+ z# z( e0 U# |* C& S- hAsymmetric distribution, 非对称分布: P8 f" Z/ y: I# \9 U
Asymptotic bias, 渐近偏倚
& F# z. T$ g/ Y7 q# k' t9 EAsymptotic efficiency, 渐近效率
' _5 j6 C- \; C0 z/ yAsymptotic variance, 渐近方差9 ^* n0 y. [7 {! Y( |
Attributable risk, 归因危险度
& E/ w. c! J" H1 T$ H4 sAttribute data, 属性资料: ?- q: V; ?) v; Z" f
Attribution, 属性
: y# _) n0 ?: eAutocorrelation, 自相关
' P2 e+ @. F+ U8 t& ~Autocorrelation of residuals, 残差的自相关+ v5 h# U" @( \5 w) I s; o
Average, 平均数0 ~; ^1 r& J6 v3 O- v( G. |4 t" u
Average confidence interval length, 平均置信区间长度; r' S8 O" n! T6 L( f6 p
Average growth rate, 平均增长率
: e5 V) G' u7 ^, W; q* o1 X% X k" uBar chart, 条形图
$ \* E8 t3 @& R) v, VBar graph, 条形图
; ]* S( o( V" ^* Z7 k% x% V' SBase period, 基期! F6 k' R" E* w, P+ A" D
Bayes' theorem , Bayes定理
, o. |. K6 [3 F/ v. z' }Bell-shaped curve, 钟形曲线$ [( c# |; r+ d+ y8 Q. E( E" k
Bernoulli distribution, 伯努力分布
. F/ b% |, R5 v; ]; h- fBest-trim estimator, 最好切尾估计量
/ U; I$ ?- u# R- y8 MBias, 偏性
" `0 p8 [7 o9 d! HBinary logistic regression, 二元逻辑斯蒂回归
- _: q% k: S: X' OBinomial distribution, 二项分布
% [: n! j# n8 J) _" M0 S3 @Bisquare, 双平方- K- c9 b. f0 g. f
Bivariate Correlate, 二变量相关
- b6 j: R" t* _: GBivariate normal distribution, 双变量正态分布+ c- k2 M" X0 e& G4 n! m0 p6 T+ g
Bivariate normal population, 双变量正态总体9 v. p+ ^+ d+ S
Biweight interval, 双权区间
! y6 ` |) e6 V9 q1 ~* `' jBiweight M-estimator, 双权M估计量
' `& X) J- L3 }- f4 R+ [# R# G* U$ XBlock, 区组/配伍组0 L7 U: r0 R2 W* C# L9 {
BMDP(Biomedical computer programs), BMDP统计软件包
$ D, g+ P c8 A$ J; o) WBoxplots, 箱线图/箱尾图
8 O" ^" n7 D+ F. k1 Y9 N% ]: C, @! b% o* aBreakdown bound, 崩溃界/崩溃点
& ], V' n4 q* n. R q1 pCanonical correlation, 典型相关1 Z; b; @6 K6 b, D$ g4 b
Caption, 纵标目
8 D4 T, v' x; [9 j& @& T0 v* h9 v- mCase-control study, 病例对照研究
. ]- M. _: U! t# yCategorical variable, 分类变量, t% X d% D/ }3 ?0 t) f
Catenary, 悬链线
1 w$ J; h& _) K) l* a% QCauchy distribution, 柯西分布
; {- @( ^# x9 S" d8 tCause-and-effect relationship, 因果关系/ L0 E6 V( [7 w5 X
Cell, 单元+ c$ q- A( k: K+ O, }9 U
Censoring, 终检
* T- K& C# v1 |( S cCenter of symmetry, 对称中心
2 V0 ?+ n2 R+ E) n+ _4 F/ O4 \) OCentering and scaling, 中心化和定标
) O% K. J% v% |) M) xCentral tendency, 集中趋势, C+ b X4 t' m j
Central value, 中心值8 h4 Q, G) B- @. M* ~6 w+ m
CHAID -χ2 Automatic Interaction Detector, 卡方自动交互检测+ i( E9 c; j; O1 g
Chance, 机遇% k X& X0 v/ \8 g
Chance error, 随机误差6 B3 {- ^9 E. H4 H d8 E
Chance variable, 随机变量
4 W! _2 W# E5 L2 v/ f, ?, NCharacteristic equation, 特征方程6 N9 p& l, p4 E6 R
Characteristic root, 特征根% w% R% c2 K# R' i/ o1 I
Characteristic vector, 特征向量) D6 W$ \+ S* Q
Chebshev criterion of fit, 拟合的切比雪夫准则9 r' K* i: q( @& B% b
Chernoff faces, 切尔诺夫脸谱图' h1 p z8 i# C P
Chi-square test, 卡方检验/χ2检验/ u+ L4 ~0 \0 N* n1 ?
Choleskey decomposition, 乔洛斯基分解' T$ v6 ~5 w! g1 Y: ]% z
Circle chart, 圆图 6 P2 m+ p" b# f4 ]
Class interval, 组距
0 |7 b9 v. Y' X5 ~8 j: j/ @Class mid-value, 组中值8 w3 E9 T1 F8 h- w. P O
Class upper limit, 组上限: W3 }7 c k# \: P
Classified variable, 分类变量
" B( f1 c+ g( A$ H2 l) w6 M$ bCluster analysis, 聚类分析6 O% k- d9 j1 {; h0 D- W V) `& G
Cluster sampling, 整群抽样- Z {) ~0 T8 o0 ?+ h2 C+ N
Code, 代码
) T+ K8 h5 G1 D& T8 Q) oCoded data, 编码数据
* D* j/ F7 Q P; @$ Y2 X4 _7 RCoding, 编码: B1 Z& Y3 z( k, U1 G
Coefficient of contingency, 列联系数
9 S O2 j# U5 ]Coefficient of determination, 决定系数" X. l" ?8 L* h* a
Coefficient of multiple correlation, 多重相关系数- ~9 b3 c. F O. {/ Z9 s0 {2 M, a
Coefficient of partial correlation, 偏相关系数
1 |8 f% o Q* y7 cCoefficient of production-moment correlation, 积差相关系数9 k* @, ^" X: o/ i
Coefficient of rank correlation, 等级相关系数
' j" o; a' |- B! ZCoefficient of regression, 回归系数0 U4 _: i% W1 @( u% |; z5 R
Coefficient of skewness, 偏度系数
% {: L" q# |3 ~; PCoefficient of variation, 变异系数
7 h9 H h" I( YCohort study, 队列研究+ s* s/ }& \$ }9 L% [ t1 J f
Column, 列1 T9 _, x1 O+ V: r0 |
Column effect, 列效应$ Q3 H4 I* {; F9 J4 y) ]$ R. i
Column factor, 列因素
$ R8 f4 [$ J2 ?7 D- ^Combination pool, 合并
. l6 h" m& p" @1 l9 BCombinative table, 组合表
9 ]8 ]2 r4 v) s) N1 P9 j3 RCommon factor, 共性因子! d- g; A8 J( j/ v; `: `: M
Common regression coefficient, 公共回归系数
' G; C1 s" I- K( LCommon value, 共同值" r, [: H# _0 D* O2 u. `' J
Common variance, 公共方差
4 Z8 @' }: R* [0 l4 m# ACommon variation, 公共变异$ H& M( p1 ?, W+ j2 X
Communality variance, 共性方差2 U6 K/ ?3 u2 U2 m8 F
Comparability, 可比性
3 V* ?0 e. z" E6 e1 n- x8 L' UComparison of bathes, 批比较
4 |, U4 |1 J7 t T7 j' iComparison value, 比较值6 M7 Y8 P3 P) ]
Compartment model, 分部模型$ y6 ^; j5 l- D0 E6 [5 T
Compassion, 伸缩
6 \) _! B$ b8 {Complement of an event, 补事件
8 ]* T7 E/ i( q+ oComplete association, 完全正相关. k0 d/ o6 A. O% f |7 M
Complete dissociation, 完全不相关. C7 z* o8 c( u) f6 s5 a# b7 p1 C
Complete statistics, 完备统计量
2 @4 ~( ~5 z* HCompletely randomized design, 完全随机化设计: Y+ j- c8 }" j7 P: @+ s
Composite event, 联合事件
$ v7 D3 i1 Q. U# u# J) SComposite events, 复合事件# X+ `% a" q! `: S5 b U
Concavity, 凹性2 Q: R3 {1 W% ` i7 q
Conditional expectation, 条件期望
/ N3 U5 X/ d5 SConditional likelihood, 条件似然' j: E R" B- |
Conditional probability, 条件概率. Q4 s9 }0 G' b6 H
Conditionally linear, 依条件线性( V( q8 ~0 ^# u' l$ _4 E- y N
Confidence interval, 置信区间
; h! }4 ~: ] ]% o$ ~; sConfidence limit, 置信限7 m* q( Q5 ]% Y: z- P
Confidence lower limit, 置信下限
, _" `8 w* M4 B- X# a1 _. E" fConfidence upper limit, 置信上限3 t7 T) Y. L9 K6 P
Confirmatory Factor Analysis , 验证性因子分析
9 r/ P) x8 _4 ?# g# ?' ^Confirmatory research, 证实性实验研究9 ^" x1 e4 n0 D; S* u* F
Confounding factor, 混杂因素1 z% @ h- |% s
Conjoint, 联合分析5 O6 w! y! m- S* y' @5 p( C
Consistency, 相合性 T2 U! I9 g' J( y0 }% R( [) r+ ? g9 _$ W
Consistency check, 一致性检验
' S0 ~4 p: s/ x5 L1 XConsistent asymptotically normal estimate, 相合渐近正态估计, ~! h6 O+ ^+ K4 c6 F+ j) g
Consistent estimate, 相合估计+ O/ ]9 P+ l$ t
Constrained nonlinear regression, 受约束非线性回归
$ a2 O) [9 r1 BConstraint, 约束
5 D- J2 H) r% F8 c. ~- lContaminated distribution, 污染分布- {" q9 T% i; ]& t# j. q
Contaminated Gausssian, 污染高斯分布" z4 _" D5 |* {
Contaminated normal distribution, 污染正态分布
: L6 \2 f- D% e+ P2 |Contamination, 污染
& D" B' i2 \9 \. P% H7 j2 iContamination model, 污染模型
% C' Q+ s2 J: W' Q4 a' d* sContingency table, 列联表: V" ~0 p% q* C% _
Contour, 边界线! ] ~& K8 |# k7 G6 Z
Contribution rate, 贡献率4 I" A- D; O$ Y! X6 \& _( X
Control, 对照
" O. ?( i7 y3 T# X- LControlled experiments, 对照实验1 X- o. x9 l7 _$ v! F
Conventional depth, 常规深度
* J5 @0 |3 e6 Q9 H0 _* oConvolution, 卷积
, o1 d& D4 y2 E7 ?# |' j5 f) v5 x mCorrected factor, 校正因子) _3 C& R; }0 f0 ^* R- v0 u, V
Corrected mean, 校正均值
2 W' o. r5 V! T% ~Correction coefficient, 校正系数" U. ^ G v# }; z8 e; `
Correctness, 正确性
6 T" _6 m% [( f2 PCorrelation coefficient, 相关系数
* V1 E4 y; `, Z7 M2 k0 a5 bCorrelation index, 相关指数5 D# o/ C4 |, O1 R
Correspondence, 对应9 t o* f$ D" J2 L
Counting, 计数' m3 n( f1 q _( a7 G
Counts, 计数/频数$ \; ^6 w i" V# W: }* n3 j7 A
Covariance, 协方差
a: E/ c( ]1 a& aCovariant, 共变 + K" O+ {6 I' A; e
Cox Regression, Cox回归
) L( [- m: e& a( QCriteria for fitting, 拟合准则( _( R) r( Y E" z, u
Criteria of least squares, 最小二乘准则
! n' q; r& d+ \Critical ratio, 临界比
9 `) F9 S5 V" z5 NCritical region, 拒绝域
* p3 V, ^. M" W9 iCritical value, 临界值
( i' d: O- }8 F- Q% u" S0 G5 Q% NCross-over design, 交叉设计
* f! W5 l' v/ s& s& [- |" ~+ xCross-section analysis, 横断面分析
3 x' s. _# X6 M' cCross-section survey, 横断面调查0 d3 U) j: t# L9 F
Crosstabs , 交叉表
: ?! q0 v2 O3 G4 B! r# L5 XCross-tabulation table, 复合表9 o% ~% N! d! R% b g% C
Cube root, 立方根; F ~7 U1 F% Z) ~, j! P I
Cumulative distribution function, 分布函数6 g( U9 X. D- e$ F
Cumulative probability, 累计概率9 R6 o& O1 n0 W+ Y
Curvature, 曲率/弯曲. m5 c$ X4 X: o; p2 f
Curvature, 曲率- P! y7 D D( L1 Z: a
Curve fit , 曲线拟和
) n1 d1 F S! G; t: jCurve fitting, 曲线拟合
0 ~ p% f- Z' _$ w, n0 JCurvilinear regression, 曲线回归
0 `5 Q3 J3 R- O" g9 C: R$ MCurvilinear relation, 曲线关系
$ G, h- E$ S: ]: U( ^Cut-and-try method, 尝试法
6 a, U7 J7 m1 \" T# xCycle, 周期6 ~7 E) N2 Z+ C3 W) C
Cyclist, 周期性- Z$ ]$ f$ K* m! m: A( @( u
D test, D检验( v- r2 i, g6 Z7 \ ?3 M$ H9 _: c
Data acquisition, 资料收集" U) |2 H7 t/ d2 Q! P; J4 R
Data bank, 数据库& J8 P' c# l2 j" M
Data capacity, 数据容量
+ C8 q4 x+ o/ n3 Y# dData deficiencies, 数据缺乏5 F7 |; g3 [# @4 ^
Data handling, 数据处理3 ?3 a6 x6 Z! {- f( U
Data manipulation, 数据处理
7 b0 ^. y) m, W1 JData processing, 数据处理
: l" j: R; v N1 QData reduction, 数据缩减$ O v1 D0 s+ l( @
Data set, 数据集
. |, I: Z' e8 [9 gData sources, 数据来源0 i: |" e8 g9 I, D, H0 @
Data transformation, 数据变换/ q5 j; P3 f6 @1 D4 J6 u
Data validity, 数据有效性0 F m$ _% `! i- ~3 p2 P1 a
Data-in, 数据输入
8 m# I+ T: P0 Q7 [8 t+ p& mData-out, 数据输出
0 }/ \ ]9 Z) z& U5 M' FDead time, 停滞期# Z. f4 g6 g: V5 C6 H. w, V2 F' b
Degree of freedom, 自由度# I2 }/ i; q, ]. q- Z' C
Degree of precision, 精密度
! q9 z9 [; o8 a1 z- y) o" x. zDegree of reliability, 可靠性程度) S6 {6 z. Z7 N5 V: Y7 s2 i
Degression, 递减7 b( E9 Z# F- ?0 J
Density function, 密度函数
& [( v+ q4 p) K# t. z$ DDensity of data points, 数据点的密度
$ R1 C2 c0 h7 ]. ^3 k7 z5 c" XDependent variable, 应变量/依变量/因变量
% z5 ?. ]! N% i9 \7 R: ^3 nDependent variable, 因变量
" l: }, Z. Q! g( Q. CDepth, 深度
% V0 r. {! H% ]: E! FDerivative matrix, 导数矩阵
7 x9 v* m% j) } tDerivative-free methods, 无导数方法" ^: n, ~ N. ?" f% b) Z2 s/ B
Design, 设计1 Z$ c, E/ P; P1 f) g; C* j ^
Determinacy, 确定性
% Z$ d& ?+ [/ |# N- h: NDeterminant, 行列式: B- Q! L! l/ ~! j) `
Determinant, 决定因素
. s. R. a& r: q% Q9 j1 j/ i2 Z; q0 bDeviation, 离差
3 }" V! R/ h( bDeviation from average, 离均差
* O {, B+ `. m& }5 D2 PDiagnostic plot, 诊断图
& L+ N% [$ I. t9 PDichotomous variable, 二分变量1 q( e. _: z E0 P5 [
Differential equation, 微分方程
# ~0 I: w* R! C0 K4 F& {, QDirect standardization, 直接标准化法
, i o3 J, |( l# tDiscrete variable, 离散型变量
( b2 k5 a$ ?9 K6 ~1 `% i' pDISCRIMINANT, 判断
( h) c) u2 ?' Y1 Q! K7 F% h' yDiscriminant analysis, 判别分析3 }6 T! r: t; ^' j: i. B
Discriminant coefficient, 判别系数 f& g8 q1 }* R4 x
Discriminant function, 判别值
. Z0 k3 N. h+ U1 u: _5 w/ ^Dispersion, 散布/分散度 F$ C) S9 E+ @ v4 S! @) C4 S
Disproportional, 不成比例的9 } t2 h; Z( L8 H' _, n1 y
Disproportionate sub-class numbers, 不成比例次级组含量
. z/ v% j3 X1 w1 F9 x2 TDistribution free, 分布无关性/免分布. f; {# M9 A) t f
Distribution shape, 分布形状
0 D" E' ~7 |+ R$ jDistribution-free method, 任意分布法. b2 D* C& z% I: @
Distributive laws, 分配律
( u, P( `3 a* Z# [1 o: {Disturbance, 随机扰动项! y" _) L7 W' N q& s
Dose response curve, 剂量反应曲线 l0 @- B& L* L' F# H9 g% |) q
Double blind method, 双盲法
5 b, y9 S; Q; Q3 [$ h& a# _Double blind trial, 双盲试验
& }+ o/ L' Q8 H% K, x- ~7 _: eDouble exponential distribution, 双指数分布* k- m# O' k& g+ }% Q% {* J
Double logarithmic, 双对数
" @$ G0 i# ?: S5 x- p$ ADownward rank, 降秩) T4 @. l) `: t8 \& w2 L0 O
Dual-space plot, 对偶空间图
8 _7 k3 Q+ ?" J2 L' eDUD, 无导数方法* t1 }9 M! ]+ w* r0 J4 E. l; h& }1 D
Duncan's new multiple range method, 新复极差法/Duncan新法
& l F* j" `- x# lEffect, 实验效应
( [ a! e: S1 |. e2 }$ V7 Q+ T" |Eigenvalue, 特征值
# p4 |+ k/ I9 { |! r: aEigenvector, 特征向量
* ? I+ @( e4 X2 u$ K4 O( Q" {( V9 pEllipse, 椭圆8 i; a( g- i! z) c% k3 t' a
Empirical distribution, 经验分布* K$ e5 ?0 Q W0 B) Z
Empirical probability, 经验概率单位1 ~: O5 |, \/ H2 h
Enumeration data, 计数资料( s( W2 G4 H- u* j
Equal sun-class number, 相等次级组含量! F; d9 q3 d* R7 X2 X Z( u) L
Equally likely, 等可能
+ a$ t/ E R+ N0 x' ?+ REquivariance, 同变性
' Z. k; D* Z3 E; |Error, 误差/错误, S/ y5 D3 o( j
Error of estimate, 估计误差
/ x2 ]+ O8 ^; s* l1 n/ K5 fError type I, 第一类错误
$ ]8 a1 u: o3 U% `/ ?4 MError type II, 第二类错误5 `) V5 _ F) G9 N# h$ s
Estimand, 被估量
. f, M9 }7 U X3 @6 SEstimated error mean squares, 估计误差均方8 ~3 r7 ~( V! d$ A$ C( `
Estimated error sum of squares, 估计误差平方和6 Z1 a( l% q& B; T9 }$ j
Euclidean distance, 欧式距离
& L1 J7 F: W& Z" B/ tEvent, 事件: K/ k- f. a$ `
Event, 事件
6 o0 O4 n, y! |Exceptional data point, 异常数据点/ B [& ^4 H/ w( P; w7 W+ _
Expectation plane, 期望平面2 h/ w% t- S" E* b' |
Expectation surface, 期望曲面
: c4 v5 K4 c4 U W9 |3 F A+ `( }Expected values, 期望值1 H+ Z6 |; H3 i6 y/ u
Experiment, 实验
. P' g0 Z) m, A: n% y dExperimental sampling, 试验抽样8 Q/ a7 s2 n" Q; J
Experimental unit, 试验单位
* E' s' h7 V. J; `8 bExplanatory variable, 说明变量
6 u/ M a7 E1 p4 K3 n! ^) XExploratory data analysis, 探索性数据分析, {; R m; x8 I7 \# B4 M
Explore Summarize, 探索-摘要
& Q, P% G: n5 |* D* VExponential curve, 指数曲线
' C8 w4 b b* e/ |% O. OExponential growth, 指数式增长) Y3 k8 @2 f, [4 r
EXSMOOTH, 指数平滑方法 5 z' g9 Z) G- V. t0 y
Extended fit, 扩充拟合
/ d0 l. H/ a, n8 B- `) RExtra parameter, 附加参数8 s$ }2 F4 E( k4 }
Extrapolation, 外推法
" n- B6 m* v7 ^9 ?Extreme observation, 末端观测值
0 O8 `( Q$ B2 r5 qExtremes, 极端值/极值2 h4 _5 l; w c2 L% n
F distribution, F分布2 _( S6 t' N. g y5 @+ p
F test, F检验2 J) I$ A0 f0 u; f* `7 t1 W
Factor, 因素/因子
) d/ p4 L8 B! p3 H% ~. XFactor analysis, 因子分析
' |: F( T$ [) g2 ^ E; jFactor Analysis, 因子分析/ h6 l) @0 F, @/ S& x
Factor score, 因子得分 0 X; j7 Y+ t+ z& @8 n
Factorial, 阶乘) q* a2 b4 f1 V9 r0 E( _+ q7 t4 M
Factorial design, 析因试验设计
( V Y8 ]0 K3 m* A1 IFalse negative, 假阴性
) G! _( {4 `& e9 W. a+ r( zFalse negative error, 假阴性错误
" f2 P- r) {- X2 B% B, Z* L# x0 x; tFamily of distributions, 分布族8 A# y$ K. @3 `0 ^% n
Family of estimators, 估计量族
, x; `% G/ H& a5 [Fanning, 扇面6 X5 H$ {4 s+ }; h. v
Fatality rate, 病死率
# Z% q8 e& d" MField investigation, 现场调查3 o. f1 K/ U) B
Field survey, 现场调查' A R7 q# W( W1 e+ b
Finite population, 有限总体
' o# j% G0 H! V" p. h! u% W' ]Finite-sample, 有限样本
' T8 K8 N4 S/ a* a2 \; q. OFirst derivative, 一阶导数
0 K6 W& R! `0 g' R( S# VFirst principal component, 第一主成分
& M1 O$ Z- G! F& B( ^, xFirst quartile, 第一四分位数
( C3 P C0 K/ @: d/ w& T) yFisher information, 费雪信息量, m j1 s" b# q3 \: A
Fitted value, 拟合值6 x. z/ M9 b7 h7 _/ B- [
Fitting a curve, 曲线拟合, Z1 C$ r+ ^2 r3 M
Fixed base, 定基
c. B( G. |3 D AFluctuation, 随机起伏
* [/ K# m: V2 v e, i. R e( ^! \ `Forecast, 预测
$ S2 V5 g7 y. g- c4 W' wFour fold table, 四格表
- l' H9 H' _% A- I. @Fourth, 四分点6 _0 i) h$ I1 n+ {' F7 C" Q. q& f
Fraction blow, 左侧比率. P$ n+ W* k, W6 v v* i
Fractional error, 相对误差: q' H( f6 J- @: C7 n! X* F( b
Frequency, 频率/ t6 s# U: M' _7 |6 P( H
Frequency polygon, 频数多边图. ], a+ {) V9 m9 ]
Frontier point, 界限点9 y5 u5 A9 r0 q( L S6 q" x: ~
Function relationship, 泛函关系2 ~; Y) |$ @7 b) P7 e+ _# @" K
Gamma distribution, 伽玛分布2 n v+ V0 h9 f m8 @9 e
Gauss increment, 高斯增量
- o- g, ?! I' T8 x1 { I% wGaussian distribution, 高斯分布/正态分布. a7 |) U. W7 G5 W! E6 T
Gauss-Newton increment, 高斯-牛顿增量
l1 r) Y, G9 {! x" LGeneral census, 全面普查$ ^$ A5 P% w4 R% v2 j# P
GENLOG (Generalized liner models), 广义线性模型 & p; L6 ^( a( ?% M$ H
Geometric mean, 几何平均数: h6 q; d m6 \- v; t& z
Gini's mean difference, 基尼均差
) G. `8 s0 ~2 c! U# {& G5 CGLM (General liner models), 一般线性模型 b) w: P% `9 m+ S0 ^% A3 C
Goodness of fit, 拟和优度/配合度9 K0 _# \9 d* h% K7 Z' W8 K0 D
Gradient of determinant, 行列式的梯度4 {& A- P( y/ R
Graeco-Latin square, 希腊拉丁方8 }! } \' {% s% [
Grand mean, 总均值3 L5 h! a0 s9 x! Q
Gross errors, 重大错误
. \1 _% n, b, E: Y' ?) qGross-error sensitivity, 大错敏感度0 ]) B1 b' s: J+ |
Group averages, 分组平均
. J. I" J/ Z* N' Q' VGrouped data, 分组资料- K3 P9 }6 Z4 t$ m8 C" c4 [
Guessed mean, 假定平均数
/ k9 C) x: d% m8 _3 f" K$ T8 I' vHalf-life, 半衰期
& _/ D% h/ e! k. `- b S1 _% g" CHampel M-estimators, 汉佩尔M估计量
5 D" U) a/ E& t( x4 f7 D, EHappenstance, 偶然事件' J$ Z( m( s5 Y4 Q5 K
Harmonic mean, 调和均数' U! m0 O: W; n4 O' {
Hazard function, 风险均数
! \4 G T! R* y4 B7 q3 b3 gHazard rate, 风险率' i7 S1 G# t+ \# W2 S
Heading, 标目
7 C( ^/ Z# G2 r0 S% k& [Heavy-tailed distribution, 重尾分布; ^' p/ V$ P% C d& j3 k/ s" T
Hessian array, 海森立体阵
( e' k- {9 \" X$ S4 ?; m% lHeterogeneity, 不同质
" J9 n. Z1 x; DHeterogeneity of variance, 方差不齐
/ k5 D2 B. W: [* Y$ Y% B SHierarchical classification, 组内分组
* Q% _9 Y3 i/ T) U& j$ o1 [+ A( }' }Hierarchical clustering method, 系统聚类法
6 ?) M `& K4 PHigh-leverage point, 高杠杆率点
- Z- j) a8 l YHILOGLINEAR, 多维列联表的层次对数线性模型, h5 R% h8 L2 d4 i. C' R; Q, [; ]6 I
Hinge, 折叶点) r0 g& o% ]' `- [+ U0 N# ]; W/ `
Histogram, 直方图# E/ Y0 p+ J) n* p& I5 Y, o% V
Historical cohort study, 历史性队列研究
& i2 J. `1 P2 Z0 I& ?Holes, 空洞
8 x: C5 C( p o" s# I2 UHOMALS, 多重响应分析5 C3 o8 o% b6 [6 g
Homogeneity of variance, 方差齐性! D, q! T- e/ E1 Y5 n3 d
Homogeneity test, 齐性检验
& c8 e) ?$ p( T$ ?Huber M-estimators, 休伯M估计量
. M; @% ?3 P$ h6 g d) K4 b7 ~/ ZHyperbola, 双曲线# E! ~$ }5 \; r: p
Hypothesis testing, 假设检验
3 e: \3 `3 X+ C4 OHypothetical universe, 假设总体
0 `8 S" y3 F/ W Q7 oImpossible event, 不可能事件
: O# N2 V0 r/ H( Y" ]3 tIndependence, 独立性, d O$ _ K3 W! O. c, G
Independent variable, 自变量
0 M( M, t) F" _2 N+ ]0 j, |( SIndex, 指标/指数
9 u% H) p: B' z" O I. \Indirect standardization, 间接标准化法
, k# @7 w' r7 ?( s8 |. \; aIndividual, 个体/ f& `, g$ t2 ]; K# G" Y
Inference band, 推断带0 m. m: E0 L' I+ C
Infinite population, 无限总体
5 y! l/ `' v# l2 sInfinitely great, 无穷大
7 Z9 m# n9 R! u1 w* v' DInfinitely small, 无穷小
; j8 Y! T6 v- r+ B3 a. _Influence curve, 影响曲线/ ^/ q9 @3 N% h
Information capacity, 信息容量, Y3 O, r+ ?" ~% T( l I; o7 U
Initial condition, 初始条件
1 ?6 h- C' [" T+ Z( K7 l7 _Initial estimate, 初始估计值
$ d, c, I! O; e" zInitial level, 最初水平7 V& U/ B5 p: K$ z5 F
Interaction, 交互作用; C$ y; A9 C3 s) i
Interaction terms, 交互作用项
7 y% ?( B# Q* i! }! l3 RIntercept, 截距( x R7 ~% Q( R" \5 C; J
Interpolation, 内插法
: S; T" x6 e1 z4 \$ L5 xInterquartile range, 四分位距" E7 \5 S: ]* ?5 ~0 A- U) S
Interval estimation, 区间估计. ~. G; {: s& Y# B/ [( b: ]
Intervals of equal probability, 等概率区间) q F4 I, f, h/ o
Intrinsic curvature, 固有曲率. E# [( T% Y0 K) d+ m) L4 a
Invariance, 不变性2 w, G% L7 S3 s0 D
Inverse matrix, 逆矩阵' F% {% d) c; S
Inverse probability, 逆概率
) \# v. D# R, PInverse sine transformation, 反正弦变换% x: w1 D( n5 \/ Q: {- d/ o
Iteration, 迭代
; O' S% J9 A& E( r# L g2 DJacobian determinant, 雅可比行列式
# H2 o6 g6 r, X0 IJoint distribution function, 分布函数
8 q7 N) F8 K) E+ uJoint probability, 联合概率/ c7 @# E* x6 B/ e
Joint probability distribution, 联合概率分布
4 v( s5 @; R vK means method, 逐步聚类法
7 c7 b/ |3 ?& Z5 g2 g2 Y p0 WKaplan-Meier, 评估事件的时间长度 ! Z2 b3 X Y( H3 u
Kaplan-Merier chart, Kaplan-Merier图2 p0 @( _+ z7 b! r
Kendall's rank correlation, Kendall等级相关/ X" T, C; m/ e
Kinetic, 动力学
/ m2 q" m- n" b* U/ E/ ?5 r# CKolmogorov-Smirnove test, 柯尔莫哥洛夫-斯米尔诺夫检验1 V& S8 ?8 e8 F. o; f" O
Kruskal and Wallis test, Kruskal及Wallis检验/多样本的秩和检验/H检验
$ s# ~7 z( e: }Kurtosis, 峰度
# |, y1 K; F* ]2 y1 h. Z' xLack of fit, 失拟
9 q7 p( e7 p ^% B" k- x6 M6 S+ xLadder of powers, 幂阶梯; g& p) B* w4 J, o0 ^- k6 O l
Lag, 滞后9 S7 V9 A4 M) r& Z3 u% X
Large sample, 大样本
4 z' p6 n9 X( k3 W' ]1 d) iLarge sample test, 大样本检验& w. Y. h6 `4 ]9 {& _% g
Latin square, 拉丁方
, @; A+ i5 Z1 z; M- SLatin square design, 拉丁方设计
& q' ^7 M; l3 a2 J9 iLeakage, 泄漏
+ a$ m0 O7 e" a4 gLeast favorable configuration, 最不利构形- p9 f3 m- ~3 }, ^( Z
Least favorable distribution, 最不利分布2 o7 K5 `* q. z# S! V6 b/ ] o) d/ x
Least significant difference, 最小显著差法1 a$ V7 D7 r) r" `( f% F6 @
Least square method, 最小二乘法" ]( n8 Y, Z/ b! w
Least-absolute-residuals estimates, 最小绝对残差估计5 Y6 H! V* T6 W$ p
Least-absolute-residuals fit, 最小绝对残差拟合( o) @: ^; Q4 s0 S) z: P. }4 ^
Least-absolute-residuals line, 最小绝对残差线
9 A3 o+ I+ Z6 ]Legend, 图例
0 r2 i) c1 l Y, PL-estimator, L估计量
& W$ S. ?, u* HL-estimator of location, 位置L估计量' r% D2 ]" N' E
L-estimator of scale, 尺度L估计量5 L+ ?7 {; Y* T5 R; c7 b6 {& n
Level, 水平% q) G- V2 m6 H( ^# Y' x# H
Life expectance, 预期期望寿命
+ f; l2 p. F+ n' z) U2 R6 e5 O+ DLife table, 寿命表
% c& B% g6 q; V# i! m7 jLife table method, 生命表法
: H: I1 V- A0 ]Light-tailed distribution, 轻尾分布, P. g6 w, K* G& J2 T
Likelihood function, 似然函数. L) C$ j2 L" }2 M; } H8 [
Likelihood ratio, 似然比8 h9 M; t/ i5 @3 x3 S. Y
line graph, 线图" i9 H8 n0 i$ N/ l3 }3 i$ S
Linear correlation, 直线相关
* R! Z, d' I# K5 s' cLinear equation, 线性方程
0 V4 {5 J$ p+ T! {3 J0 t* CLinear programming, 线性规划3 k/ _$ k8 |% B" w+ R# U
Linear regression, 直线回归
7 c" I2 Z0 m- N" C- f9 q" R/ m: bLinear Regression, 线性回归
; T/ b$ b$ b) |. I) x. @& ALinear trend, 线性趋势. z5 u3 S7 _6 i1 C$ X
Loading, 载荷
5 `+ i( k( x0 f4 }" xLocation and scale equivariance, 位置尺度同变性# z& p) E: v+ [. }2 Z
Location equivariance, 位置同变性
( t7 o! V% Q3 aLocation invariance, 位置不变性+ k3 K2 `' E; Q# P1 N, Z( l9 d' S
Location scale family, 位置尺度族
) c+ x8 F; t6 l5 K F: Q& _7 OLog rank test, 时序检验
' `1 P" |9 {$ T1 I. l2 u- [Logarithmic curve, 对数曲线
. G2 _4 ]/ v! _2 M" V+ C* u$ r" [Logarithmic normal distribution, 对数正态分布$ u0 C1 H+ P7 c: B V3 z
Logarithmic scale, 对数尺度
9 Q ^, s$ e, OLogarithmic transformation, 对数变换: Z# @. z% ^/ q& W
Logic check, 逻辑检查2 [; O: }% k" J C. B0 z8 G) c8 e
Logistic distribution, 逻辑斯特分布
h% @5 r: L# ]( G# U. ~Logit transformation, Logit转换) m* S( `* J5 |# k& V- U2 p# s6 u
LOGLINEAR, 多维列联表通用模型
5 v# l2 h4 H" p9 T# ~' iLognormal distribution, 对数正态分布
" e/ {$ |0 I( \/ \Lost function, 损失函数% A6 w5 U% R9 j1 I+ }+ J
Low correlation, 低度相关
3 x Q/ q! g I/ l; b% PLower limit, 下限5 J% U) [ G* S+ f
Lowest-attained variance, 最小可达方差
6 Z4 t4 ^; l( Q, \3 TLSD, 最小显著差法的简称( O2 t9 k+ }2 l3 L
Lurking variable, 潜在变量1 Q. s, x, p$ t+ Q- z9 M0 A. K
Main effect, 主效应
8 {) v2 C4 H9 _) gMajor heading, 主辞标目
3 I6 I8 |6 R3 I7 k) ]2 R$ tMarginal density function, 边缘密度函数, ^1 h* o0 u! f [
Marginal probability, 边缘概率
7 |& G. v/ p6 c0 M1 b1 aMarginal probability distribution, 边缘概率分布; b- h3 O, ^( W# Z1 Y
Matched data, 配对资料( d2 B& w& I9 K T. |" f, i- I
Matched distribution, 匹配过分布
; R! s' S6 Q, j* c2 p: b2 T8 y1 {Matching of distribution, 分布的匹配4 `5 O$ t( H, S! h- ?
Matching of transformation, 变换的匹配8 C- ^' n7 n$ k# {
Mathematical expectation, 数学期望
/ _& l0 V6 t/ H. v' ^* {% l! PMathematical model, 数学模型
/ C8 \0 ?" t% w( uMaximum L-estimator, 极大极小L 估计量
+ u3 M9 U5 f& y4 [1 WMaximum likelihood method, 最大似然法
9 s! d2 B0 B" |" r- d; y/ IMean, 均数
/ \& a+ ?8 d& I$ Y! x( @ D8 r3 ]Mean squares between groups, 组间均方
& d5 C3 t( ]% i9 y$ Z6 d- ~Mean squares within group, 组内均方3 |. l3 L- T/ A/ c( E3 D
Means (Compare means), 均值-均值比较
~5 G; P! r% `5 d9 c$ b! Z# x' [Median, 中位数
" j% |& \# p, P1 Q0 T9 mMedian effective dose, 半数效量* V! r: X1 V, Z. Y! r
Median lethal dose, 半数致死量8 u' o7 h, t/ ~% C: `( \: a, m1 C; z
Median polish, 中位数平滑
0 r" F& Z* V6 ]. ]) c, P _0 tMedian test, 中位数检验" f- |$ `$ L9 Q* O: T
Minimal sufficient statistic, 最小充分统计量 J! R& C6 w# k L# G
Minimum distance estimation, 最小距离估计
7 L" g2 W# S# MMinimum effective dose, 最小有效量" ^% o: M/ e0 W6 _' W( B; k
Minimum lethal dose, 最小致死量& t: L* n# \% v
Minimum variance estimator, 最小方差估计量
z' D$ h9 \7 h3 V; G8 p8 vMINITAB, 统计软件包; _4 w: p8 j, w( G3 }; l; w- b
Minor heading, 宾词标目0 ]0 k* ^6 A$ {
Missing data, 缺失值
- a f$ T/ k" ^4 C+ n: HModel specification, 模型的确定4 B8 }) w1 c- y! [( \8 D
Modeling Statistics , 模型统计
; J$ X% ~9 }; S0 F- e. h z, ~# cModels for outliers, 离群值模型0 h8 w& S) m A1 O) `( \6 N; V
Modifying the model, 模型的修正
+ V! O3 Y% e, q+ AModulus of continuity, 连续性模: q" {2 O' C- `* ?) ?0 |* Y* [
Morbidity, 发病率
: T/ C5 M. F4 N4 D, F3 |Most favorable configuration, 最有利构形
- o, m0 {$ u" U+ ]7 D, S$ ]8 Z* rMultidimensional Scaling (ASCAL), 多维尺度/多维标度/ k' e; C0 z2 }
Multinomial Logistic Regression , 多项逻辑斯蒂回归
! u! L# {- `# ]Multiple comparison, 多重比较
$ C5 c3 g8 m; O2 |8 G/ lMultiple correlation , 复相关
0 P; v$ j/ r/ Y& s! NMultiple covariance, 多元协方差+ @# d, v! Y: Y! s6 N/ Z& j
Multiple linear regression, 多元线性回归
7 H6 D! x. Z' \( Y* QMultiple response , 多重选项
. Z2 I2 S" F8 B- w- w7 DMultiple solutions, 多解9 N0 O2 z: ?5 m) \$ l& j) ?
Multiplication theorem, 乘法定理
9 _) G5 J+ {! Y h( H) QMultiresponse, 多元响应
3 b2 l; v3 y" u* \6 F1 U$ I% |Multi-stage sampling, 多阶段抽样5 S0 {. V! A7 w- ^7 [6 m. |- s
Multivariate T distribution, 多元T分布* W. P3 h8 A8 l4 s/ r
Mutual exclusive, 互不相容
$ G6 W7 N. a" O# I/ JMutual independence, 互相独立
8 M1 {2 `3 ]" B5 kNatural boundary, 自然边界
$ f& [9 H& x% uNatural dead, 自然死亡
, g: V2 y- e7 PNatural zero, 自然零% p& {9 D6 L' t$ L7 e$ I" ]- [) X
Negative correlation, 负相关
0 ^. X* [3 }' K3 ^7 r% FNegative linear correlation, 负线性相关; f" l8 }% f* Q# K8 N( M4 v9 P
Negatively skewed, 负偏
# K$ h7 H% D/ f f8 Q) `% _. aNewman-Keuls method, q检验
. r5 i) q- B' c! P0 RNK method, q检验
$ T3 }5 ~. b* D2 K @No statistical significance, 无统计意义
6 L. D" ^6 S; S, ^* [9 J# e, |Nominal variable, 名义变量5 G7 v- i5 `, o% j
Nonconstancy of variability, 变异的非定常性
! }3 }* N* O. O0 }Nonlinear regression, 非线性相关
3 Q A, f7 H3 J! Q: eNonparametric statistics, 非参数统计
: b' y& m( P$ H: K0 vNonparametric test, 非参数检验
) g: s, l+ M# T/ Q' zNonparametric tests, 非参数检验
+ \4 Y' g( B& `$ e. {/ p! G# [Normal deviate, 正态离差' Y1 ]( g& B* n/ u
Normal distribution, 正态分布" W% P2 c; T2 v" A2 {, k
Normal equation, 正规方程组& W' h; {& T; X9 A/ b% W
Normal ranges, 正常范围: ], |' }9 ?& c7 [
Normal value, 正常值5 a# z: h% i. L. ?" v' V4 ]/ d
Nuisance parameter, 多余参数/讨厌参数
9 Z7 N5 } Z6 N) ENull hypothesis, 无效假设 T X, D* `5 G* K- J4 F
Numerical variable, 数值变量
( {9 c( z& M8 g/ l( h2 |. VObjective function, 目标函数: ^5 l( t3 b9 J' T4 c4 o
Observation unit, 观察单位
3 d! n9 D# B4 ?Observed value, 观察值
$ @1 N9 t, e% Q3 n' x5 {3 xOne sided test, 单侧检验0 {7 k. _9 F$ m/ N- @3 r" f+ B
One-way analysis of variance, 单因素方差分析( l2 m/ h' p3 O3 F0 T
Oneway ANOVA , 单因素方差分析
6 Z1 X7 J: q+ n3 ]4 g U; eOpen sequential trial, 开放型序贯设计' t8 Q6 e6 `- e, c
Optrim, 优切尾/ F2 B: X9 `: c; M _* e
Optrim efficiency, 优切尾效率
9 E/ i# I7 g1 C% B, E* _Order statistics, 顺序统计量- [( @+ S3 R! ^' _# T
Ordered categories, 有序分类7 T0 g# v4 @9 v& Z ]
Ordinal logistic regression , 序数逻辑斯蒂回归
2 ~6 ~* n" T# E2 lOrdinal variable, 有序变量
6 `' k; O+ g6 T4 K* q+ x% eOrthogonal basis, 正交基
& @% F( a4 o$ h% D1 ROrthogonal design, 正交试验设计6 o8 c1 J0 ?+ l. m; h- n( S
Orthogonality conditions, 正交条件
* b; ]2 K4 b) ]0 KORTHOPLAN, 正交设计
7 B g) P( o. ? m( }Outlier cutoffs, 离群值截断点
4 H; a$ W( w$ [8 W0 W2 JOutliers, 极端值
A4 q2 O6 V2 [' z9 `1 y% d( pOVERALS , 多组变量的非线性正规相关 : G, f0 o* b+ x
Overshoot, 迭代过度, n( Y! l9 b8 J# \6 ~' P
Paired design, 配对设计* j9 K4 _& H! F5 ~
Paired sample, 配对样本- [) q# J4 _$ f/ o1 R) O8 K
Pairwise slopes, 成对斜率4 e# r4 \& c5 Z
Parabola, 抛物线
7 w/ K, n5 ]/ z' _9 p* Z9 VParallel tests, 平行试验
+ `# o; ?1 w9 k& A7 eParameter, 参数
3 K) c3 f: p. J% L; R& ~7 D6 gParametric statistics, 参数统计
1 L4 w1 J" c! X- l! ?Parametric test, 参数检验
3 o3 V5 f% M. ?1 P y! |Partial correlation, 偏相关 d0 b" M! n4 f# x" L2 G
Partial regression, 偏回归) @# R/ i2 E, l
Partial sorting, 偏排序0 m8 Z1 b% _9 ]1 G
Partials residuals, 偏残差% V$ X3 S" z+ V& e4 e
Pattern, 模式# m+ Z% F+ f- W0 S4 X
Pearson curves, 皮尔逊曲线* t2 P. r# f5 E% r8 X( Q
Peeling, 退层, k0 k8 s: q5 L O$ D9 G! X7 O
Percent bar graph, 百分条形图8 E7 Q& G4 Z1 ?" k1 A2 }6 z
Percentage, 百分比
9 C3 R3 p1 ^+ H' N$ B( ^9 X& fPercentile, 百分位数
- u# Q, C- j( yPercentile curves, 百分位曲线3 ^5 _6 U' x' s! e3 ^/ U* k
Periodicity, 周期性
+ y# @& e/ s: \/ r- V: LPermutation, 排列; T, f( Z4 J! R/ k* y
P-estimator, P估计量: @0 |' O& S) p: ~; T
Pie graph, 饼图
9 N R& a8 @: J4 V: B: BPitman estimator, 皮特曼估计量4 C+ i" y9 e1 a
Pivot, 枢轴量: k' A. A( @" K# y
Planar, 平坦
4 O. x: v0 T( x) }( w- uPlanar assumption, 平面的假设2 I0 K( k- H% m% ^+ q0 A! w
PLANCARDS, 生成试验的计划卡
+ @0 z) z' |- T w4 APoint estimation, 点估计5 ]* L. d! L6 t' n5 g* j
Poisson distribution, 泊松分布) K* e6 l1 b c: `1 Q# ~4 Z2 X
Polishing, 平滑$ P! [4 X0 I' {1 d. Q( e
Polled standard deviation, 合并标准差" h! g, E8 R& A/ _+ ^9 M
Polled variance, 合并方差& o/ w$ P8 J. [0 O
Polygon, 多边图% g2 c5 U5 S# k' S' V' \
Polynomial, 多项式3 u( e* A/ d- Q L/ @% j
Polynomial curve, 多项式曲线# e$ ^8 v( H9 I- A
Population, 总体
4 O7 S+ [, X6 o- m4 \Population attributable risk, 人群归因危险度
! }% r, ], G- f& |$ w$ }Positive correlation, 正相关4 Y! x7 x7 T! z/ `- D$ A2 C( P* y
Positively skewed, 正偏
Q( \! \6 o& h8 s3 x" Q1 t7 x6 j# kPosterior distribution, 后验分布- W" H w/ z0 ~
Power of a test, 检验效能 } u0 {, o R! U) j; R
Precision, 精密度/ f1 Z: Q' G, C7 P
Predicted value, 预测值
; {9 [3 l$ t5 p- h5 {- i* d/ SPreliminary analysis, 预备性分析% l7 t/ |! N2 |- o1 N
Principal component analysis, 主成分分析
) b1 H+ n6 P, ~: x! WPrior distribution, 先验分布! E S- o) r2 N* t
Prior probability, 先验概率0 `/ B& U* W3 Z l/ U5 H. D
Probabilistic model, 概率模型
5 s7 Q3 Y& w$ h7 S5 y, u- Xprobability, 概率
1 Y- z! m$ @: j! u) ~Probability density, 概率密度# w1 Q0 f- l7 I3 A3 \
Product moment, 乘积矩/协方差- g) N7 Y: X# ^/ _/ M D# i* y; n
Profile trace, 截面迹图
& W: r" U2 U( z* z' ]Proportion, 比/构成比
* U5 h! c( P1 JProportion allocation in stratified random sampling, 按比例分层随机抽样
- V# `3 K% g5 x/ |8 ?- q+ GProportionate, 成比例
4 h3 e2 n4 i6 f1 n; g8 U) u' s8 nProportionate sub-class numbers, 成比例次级组含量
! C) e8 g+ i- o+ K& VProspective study, 前瞻性调查! ^+ P; i: {& L2 {
Proximities, 亲近性
2 x. L' ~6 x/ MPseudo F test, 近似F检验2 a6 E7 d" b- p# b# _+ \+ G3 D
Pseudo model, 近似模型
6 O+ Z' L. y y) v' \6 W" RPseudosigma, 伪标准差
7 X+ n- H9 f' {# P. y; UPurposive sampling, 有目的抽样
1 k5 v" \0 I$ a2 o+ K% FQR decomposition, QR分解
" W. K- S8 a2 e- l/ D4 L3 SQuadratic approximation, 二次近似
/ N! c# n8 R" v BQualitative classification, 属性分类
$ J; v# r; p9 n( J! `Qualitative method, 定性方法# N2 l; O G" _3 X4 Q6 Y, ^
Quantile-quantile plot, 分位数-分位数图/Q-Q图
7 X; d$ Z; V* d `: NQuantitative analysis, 定量分析7 q6 E2 [$ M, Z5 ]
Quartile, 四分位数 w( i+ o: F1 A- d
Quick Cluster, 快速聚类
* X" D4 q* I+ W$ A( MRadix sort, 基数排序
3 r8 S2 T6 G$ r* xRandom allocation, 随机化分组0 V v% d# A; t& ?5 ?
Random blocks design, 随机区组设计2 }4 @6 {: g0 P# }: S) V
Random event, 随机事件9 R" Z* ?7 w1 x3 G
Randomization, 随机化; g! `7 X" q1 D$ u' g! W
Range, 极差/全距6 a! o2 Q$ S7 p& b* e/ ?: z
Rank correlation, 等级相关
& d) k3 g2 ]' G! O$ O' fRank sum test, 秩和检验- Z, i* v& R! ^2 k* A0 i
Rank test, 秩检验4 K% D* J( B8 v/ q- h
Ranked data, 等级资料" |1 q# u$ p! n" F8 n2 x( D- g2 v
Rate, 比率% S: \% s3 Q) |/ @& O
Ratio, 比例6 S, b/ H7 M" M6 I3 m: A! N
Raw data, 原始资料
/ w/ w( X$ Z* ]. s7 V# n* MRaw residual, 原始残差
9 g3 f/ q. k1 w2 j ]) L0 g% n9 URayleigh's test, 雷氏检验& G. b$ H9 h s, b6 T+ x4 Y
Rayleigh's Z, 雷氏Z值
# n$ L( c2 g2 ZReciprocal, 倒数
7 Y0 {) p7 v% j! cReciprocal transformation, 倒数变换5 t5 F, T8 p3 z! Q$ A
Recording, 记录4 v$ `3 ?) ? @8 O" v, t
Redescending estimators, 回降估计量
: ^( `. w7 J7 l! wReducing dimensions, 降维2 A, l" Z( G, @7 D4 k7 r+ ]; H
Re-expression, 重新表达
$ b. @, d& ^! B6 J9 Y7 _7 q2 Y' {! C4 }Reference set, 标准组 j ~3 B& G/ L T
Region of acceptance, 接受域 o$ I# |- q5 j; z
Regression coefficient, 回归系数
+ M9 I, N7 h& _. t# x4 M5 FRegression sum of square, 回归平方和
2 k+ ~; [7 l6 R* O+ C sRejection point, 拒绝点0 s/ p5 T, m; Z) ?% F/ l2 @. {- ?; h
Relative dispersion, 相对离散度& r. J9 a( M) @' c. [% U }% Q3 q2 z
Relative number, 相对数
7 b( i9 X# M8 q' gReliability, 可靠性% A6 m% g' s% q+ m( R
Reparametrization, 重新设置参数# r0 F0 b1 D: f
Replication, 重复
, l- s |* T5 c$ [& q; `$ q2 n. RReport Summaries, 报告摘要
, r) ^8 @8 @) U$ gResidual sum of square, 剩余平方和8 |: a: Q4 B) X& d! [+ z/ ^. ]) M
Resistance, 耐抗性
8 V$ X3 M* B& U* }/ i* Y& ~* GResistant line, 耐抗线( G" l, T8 J2 S* z3 B! P3 V8 Y
Resistant technique, 耐抗技术4 Y3 E6 E2 V. V+ N4 \
R-estimator of location, 位置R估计量
1 g: T p# n0 X, oR-estimator of scale, 尺度R估计量
7 M0 R9 f: `$ ]) NRetrospective study, 回顾性调查
5 J7 A& Q& W9 s! HRidge trace, 岭迹
2 c3 D' x* {+ W4 W. q& MRidit analysis, Ridit分析 r1 r: G S6 c. I: G, y$ _
Rotation, 旋转
! c7 u* }8 L7 c" p1 ^$ ERounding, 舍入, c: A/ h2 I# y" u
Row, 行
4 F* Z& D* S- B% j \$ T/ gRow effects, 行效应
! w7 q9 D7 D7 jRow factor, 行因素
* B+ k( b' y$ P8 i9 \% \RXC table, RXC表
5 e' H6 C/ l% gSample, 样本
6 w0 {- W& }( C$ o/ FSample regression coefficient, 样本回归系数1 }" B; S& T6 j }' ~$ U# b
Sample size, 样本量
2 x& r. \! j$ O( v' b) m, {, aSample standard deviation, 样本标准差
0 s8 L5 N9 T4 N% O; n- Y3 a( G3 e0 bSampling error, 抽样误差: t$ C( v4 L* Q0 s$ U
SAS(Statistical analysis system ), SAS统计软件包% B. X! y" h. s
Scale, 尺度/量表4 ~5 F) s: N4 g4 r. B& C
Scatter diagram, 散点图
2 ~" k, y1 c4 ]. gSchematic plot, 示意图/简图2 c) y: Z9 ?! F& v" i8 _
Score test, 计分检验
" ^0 E5 a/ R5 J+ {% x2 tScreening, 筛检" E. K" b8 H2 d% x, w# P6 e7 N
SEASON, 季节分析 * T) }" _. j8 L3 {' }) N2 B% V
Second derivative, 二阶导数0 A8 F. q+ v0 V
Second principal component, 第二主成分5 s2 y! i, q( i1 L; M& [
SEM (Structural equation modeling), 结构化方程模型 ! R- H1 s5 P7 B& C: V! x1 |
Semi-logarithmic graph, 半对数图9 p6 Y [4 _, T7 I& o* F
Semi-logarithmic paper, 半对数格纸- S& t8 o9 _1 d/ h# P G- R1 u
Sensitivity curve, 敏感度曲线
/ @: D6 V+ B4 t& B! kSequential analysis, 贯序分析3 e5 S! ~& a* y+ G3 M# v* [
Sequential data set, 顺序数据集
+ D7 N. ~+ ~& v2 u- b9 P0 c; j% }Sequential design, 贯序设计
1 L L' }7 m$ Q$ bSequential method, 贯序法
2 s O8 e5 Z# e" t6 SSequential test, 贯序检验法
( ?2 y3 |; Y( d/ a+ d. j: @2 b9 l8 K4 F8 OSerial tests, 系列试验
% u/ L0 n- Z& L' k) j; f8 S2 kShort-cut method, 简捷法 1 T4 |1 T6 @% I7 N. u
Sigmoid curve, S形曲线
# ^+ \# T7 `7 C/ i) [2 pSign function, 正负号函数
; d/ O7 [9 G* n/ K3 S3 }; x9 MSign test, 符号检验! [0 ]( r/ `- w/ j$ Q3 Z$ g
Signed rank, 符号秩. m7 n) D4 D9 s( E, c
Significance test, 显著性检验
0 Y* \% _1 G1 \3 w- S% X) ^. hSignificant figure, 有效数字
; Y' n2 o- ^0 L4 D% ?7 ESimple cluster sampling, 简单整群抽样
+ q8 x0 Y+ G2 K. K- r9 ]/ qSimple correlation, 简单相关1 K, R% ~, R5 m1 ^3 Q
Simple random sampling, 简单随机抽样
( w; O3 ?' n; N R( pSimple regression, 简单回归
Z! d% P9 B, `simple table, 简单表
# {6 V9 \6 H' T9 ^2 ^* GSine estimator, 正弦估计量6 i( C/ ~* X k
Single-valued estimate, 单值估计8 v8 Q; W: ~& h' n7 G6 k
Singular matrix, 奇异矩阵
/ p4 u3 b# }" RSkewed distribution, 偏斜分布3 Y6 D" N: G5 t0 @' _3 X
Skewness, 偏度
9 |- M5 Q% V/ w) e& _7 ^9 |Slash distribution, 斜线分布 z& b# Y9 v# U9 A) |# c$ C* D
Slope, 斜率) b+ ?; F9 c- T2 W( i. n1 s
Smirnov test, 斯米尔诺夫检验
6 Z. a" q& K$ z1 HSource of variation, 变异来源
4 B' b- c6 Y- B% d# qSpearman rank correlation, 斯皮尔曼等级相关
" t4 J; ]! T7 {! d+ `Specific factor, 特殊因子
1 a+ K) K/ n- QSpecific factor variance, 特殊因子方差- k; r; v& x0 ?; Z3 D
Spectra , 频谱
/ @; I4 p% M4 b: m0 RSpherical distribution, 球型正态分布 q, @* z/ e: I/ T4 m$ j6 S
Spread, 展布
3 \+ B/ `! x' z+ A$ l3 E. T' o6 ?SPSS(Statistical package for the social science), SPSS统计软件包9 O# w0 y/ y( ?0 _9 I
Spurious correlation, 假性相关
. b6 T4 k( M( m/ q1 eSquare root transformation, 平方根变换
0 A) Q7 _% o/ M2 IStabilizing variance, 稳定方差
7 u. _3 d1 h- Z' V. G6 F( |! M nStandard deviation, 标准差' P/ v; N+ {3 n( }6 j! s
Standard error, 标准误
4 `9 C/ p& t" x; P# a" H5 U% ~2 `& lStandard error of difference, 差别的标准误
0 `: N, u2 ^* X4 Z% x& c. nStandard error of estimate, 标准估计误差
( P& z2 @! I1 K* _. ?: |5 BStandard error of rate, 率的标准误8 ~# _: I% w$ r1 |9 Q* t
Standard normal distribution, 标准正态分布
, H' R) D* }9 CStandardization, 标准化
' j% x; D' }1 X) ^5 Z( F1 e8 IStarting value, 起始值
' W& C7 X [( A- e5 [' K, g X6 YStatistic, 统计量
+ v8 W; R0 |+ X$ {' n* kStatistical control, 统计控制/ b# l. H+ I; i8 M9 S5 ~8 d
Statistical graph, 统计图
P% j1 x9 [) J/ HStatistical inference, 统计推断
Z- R( x9 ]6 \& U% s/ IStatistical table, 统计表& t0 }5 |/ M3 x" {. J
Steepest descent, 最速下降法
3 ]2 l% N% D1 {9 yStem and leaf display, 茎叶图
! j- J5 L6 C1 f0 b5 f( |Step factor, 步长因子
0 X( K4 N' O% ]- f0 x9 X+ BStepwise regression, 逐步回归
6 j5 J/ }4 l6 b7 a( h! p9 E6 HStorage, 存
# O+ o" Z" Z) ~" }8 JStrata, 层（复数）
8 ?9 p n c4 T9 u& gStratified sampling, 分层抽样
\5 ^7 \( \% W4 D9 n+ SStratified sampling, 分层抽样& K6 ~' {1 V7 | E& {5 W& ?
Strength, 强度
" p) e! X o# a! m' p& i+ yStringency, 严密性
5 E& B7 ~2 a( z4 Q5 O; Q, WStructural relationship, 结构关系
+ B7 h8 M& ?: S9 Z% y rStudentized residual, 学生化残差/t化残差. {* u0 }( m+ ^% C1 D ~
Sub-class numbers, 次级组含量
X+ j; @( x* r( s: `; SSubdividing, 分割8 l1 _1 l- q8 ~/ Z# W' M. G
Sufficient statistic, 充分统计量
. c& o/ [+ `; U7 b$ v; LSum of products, 积和6 r) O% m- H" X2 M/ Q
Sum of squares, 离差平方和& B( \- O7 ?% f" G
Sum of squares about regression, 回归平方和
9 \2 t4 A) v: bSum of squares between groups, 组间平方和
( v, S+ m0 _4 }1 F* B% m/ W4 w( bSum of squares of partial regression, 偏回归平方和
8 C1 Q+ H, d1 V; p$ D A. WSure event, 必然事件- E5 L6 \) ^1 J; m3 d* Q5 o1 u
Survey, 调查- V) a2 K# A/ n/ A5 _2 V" z* H- f+ X
Survival, 生存分析% e7 Y: E; C) e) N' L8 O
Survival rate, 生存率' d- f ^+ H0 p8 ~- y6 n) ~
Suspended root gram, 悬吊根图- i+ w8 J2 G: g3 W% _
Symmetry, 对称
* N, I, _1 Q3 ]& [3 OSystematic error, 系统误差
' E! Z% N/ ~& f- K8 N) A* P* zSystematic sampling, 系统抽样3 s. Y/ N; g6 `8 Y5 m7 N0 h
Tags, 标签% b. X# O, [% h2 P6 _& j
Tail area, 尾部面积5 U& u9 m$ I4 ]. u1 j
Tail length, 尾长
! Z9 }3 @! ~0 O+ `Tail weight, 尾重
: b8 M, k, R, _! A `Tangent line, 切线; r5 h |7 H3 o8 I: Y3 x" z( a9 }4 c
Target distribution, 目标分布
+ a, U+ I6 y5 {2 S: I9 NTaylor series, 泰勒级数
5 @ f# v$ B/ A% Y/ E. dTendency of dispersion, 离散趋势
# k/ Y; |! }$ c% V' S% _% R0 aTesting of hypotheses, 假设检验
7 s# P( g7 q9 D; r) D$ JTheoretical frequency, 理论频数# T/ o$ k4 c( c, |# @1 l5 L
Time series, 时间序列
. {3 i5 M2 b: |4 ~: ~Tolerance interval, 容忍区间
9 ~7 H. g) b% _6 h0 W5 x4 M* V6 u/ dTolerance lower limit, 容忍下限4 v, X' S; }0 \6 B3 K2 x
Tolerance upper limit, 容忍上限$ J$ t* c) F- E+ k6 F8 W. ]
Torsion, 扰率% {& l! H) G5 q2 ~6 @
Total sum of square, 总平方和
& o) S! r8 b# V0 q3 A) R) ZTotal variation, 总变异
) G: S5 ?8 G% |$ k3 ] h8 y7 `Transformation, 转换
5 f. @4 I5 `/ sTreatment, 处理
g( i k8 o# K: H0 XTrend, 趋势
7 h! J! K6 _ I" D k/ ~& O6 P: BTrend of percentage, 百分比趋势
) R& q- e! a$ i2 _7 a) VTrial, 试验
% G4 b% l, @8 a# d4 O7 T( T VTrial and error method, 试错法
" k1 F9 r) q( f8 s F* @( YTuning constant, 细调常数
' m ? o" o. e1 y" a' o4 |Two sided test, 双向检验
, o; q- h& Y0 N+ q& v$ c! y& dTwo-stage least squares, 二阶最小平方
( a+ H6 j \! w1 e7 gTwo-stage sampling, 二阶段抽样8 S( Q9 O ]6 F( u8 c8 b) H
Two-tailed test, 双侧检验
9 y+ f) `# R8 l- q, z0 R0 hTwo-way analysis of variance, 双因素方差分析
5 ]! j. k; j* R3 VTwo-way table, 双向表
8 H" F8 R: o% _; q7 P6 Q NType I error, 一类错误/α错误
7 r' |6 y0 y) k7 B/ NType II error, 二类错误/β错误! D# S: R$ I" K0 ]( F) I; s5 C1 t
UMVU, 方差一致最小无偏估计简称
- X! r8 `, s+ Q& uUnbiased estimate, 无偏估计
+ x4 z9 {( K( EUnconstrained nonlinear regression , 无约束非线性回归
% u0 S5 K/ C' N; DUnequal subclass number, 不等次级组含量
9 M0 N3 {) \7 \4 `! ~" n4 P7 J( K% GUngrouped data, 不分组资料
$ N4 v& _5 u- aUniform coordinate, 均匀坐标9 S" B" I6 o# z# N7 } I
Uniform distribution, 均匀分布5 `; S/ A% g! J3 x2 F* m
Uniformly minimum variance unbiased estimate, 方差一致最小无偏估计
" \. }- c8 L+ ]: u4 d% \! B; aUnit, 单元( ]. J) X, p* `: O
Unordered categories, 无序分类! o5 n3 @ D+ m6 O. L, r) b+ x! {. X
Upper limit, 上限
' }2 D+ d% v, L* [( P" JUpward rank, 升秩
; t( M" y& }4 ^, K3 B1 f* RVague concept, 模糊概念' E. s" o0 c2 W. s. h3 f* D' l
Validity, 有效性
2 u4 g, c" I. M- u$ L ^VARCOMP (Variance component estimation), 方差元素估计. N$ z2 B7 ], i7 l8 N( g4 ^' e
Variability, 变异性
4 D1 j$ V2 o( _8 u! iVariable, 变量& u9 L1 B6 g0 T7 g% F \4 L
Variance, 方差0 D5 ?: a( U* \9 L
Variation, 变异
. {/ K: Z4 h4 Y$ V" W3 e. Z" xVarimax orthogonal rotation, 方差最大正交旋转
) i. j0 s% s1 l# }4 NVolume of distribution, 容积
, f. V# k: O, e9 VW test, W检验
& b0 s" m+ v: B! HWeibull distribution, 威布尔分布# w$ e9 S5 ]' Y5 ^+ |
Weight, 权数" C$ Q0 }) ^1 m. z3 g1 A9 h
Weighted Chi-square test, 加权卡方检验/Cochran检验5 D+ H7 ~6 n0 I& T! F6 l
Weighted linear regression method, 加权直线回归3 g& ?% O4 ^6 n! O! B/ A. X
Weighted mean, 加权平均数
7 G# V0 @ L4 F: jWeighted mean square, 加权平均方差+ I+ I& p( l6 q
Weighted sum of square, 加权平方和1 [; u$ K4 ~, f
Weighting coefficient, 权重系数
3 {# q1 z% |! xWeighting method, 加权法
( I2 A. e% H* wW-estimation, W估计量, W, D, _! S' |- y' K
W-estimation of location, 位置W估计量3 h- F' E0 L7 Y) F2 Q. w' T' {& A
Width, 宽度& z) O& G, Z2 B/ V/ {! M; j
Wilcoxon paired test, 威斯康星配对法/配对符号秩和检验
7 t% x% g; Y1 ?, ?9 `8 n0 {Wild point, 野点/狂点
8 |' f8 l6 l* [0 EWild value, 野值/狂值
" P' l0 R7 i5 e0 N+ Z; ^Winsorized mean, 缩尾均值; D( S& M0 z9 |3 K, z
Withdraw, 失访
' U' B9 n1 h0 C( aYouden's index, 尤登指数( [: N! k' p' ^' O; K4 \2 ]" [
Z test, Z检验
8 R. m5 k7 K7 _0 {- J1 q; FZero correlation, 零相关
& z% L/ q8 D# L c; F5 mZ-transformation, Z变换 |
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发表于 2009-1-6 22:05
